TransferBench.cpp

/*
Copyright (c) 2019-2024 Advanced Micro Devices, Inc. All rights reserved.

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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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*/

// This program measures simultaneous copy performance across multiple GPUs
// on the same node
#include <numa.h>     // If not found, try installing libnuma-dev (e.g apt-get install libnuma-dev)
#include <cmath>      // If not found, try installing g++-12      (e.g apt-get install g++-12)
#include <numaif.h>
#include <random>
#include <stack>
#include <thread>

#include "TransferBench.hpp"
#include "GetClosestNumaNode.hpp"

int main(int argc, char **argv)
{
  // Check for NUMA library support
  if (numa_available() == -1)
  {
    printf("[ERROR] NUMA library not supported. Check to see if libnuma has been installed on this system\n");
    exit(1);
  }

  // Display usage instructions and detected topology
  if (argc <= 1)
  {
    int const outputToCsv = EnvVars::GetEnvVar("OUTPUT_TO_CSV", 0);
    if (!outputToCsv) DisplayUsage(argv[0]);
    DisplayTopology(outputToCsv);
    exit(0);
  }

  // Collect environment variables / display current run configuration
  EnvVars ev;

  // Determine number of bytes to run per Transfer
  size_t numBytesPerTransfer = argc > 2 ? atoll(argv[2]) : DEFAULT_BYTES_PER_TRANSFER;
  if (argc > 2)
  {
    // Adjust bytes if unit specified
    char units = argv[2][strlen(argv[2])-1];
    switch (units)
    {
    case 'K': case 'k': numBytesPerTransfer *= 1024; break;
    case 'M': case 'm': numBytesPerTransfer *= 1024*1024; break;
    case 'G': case 'g': numBytesPerTransfer *= 1024*1024*1024; break;
    }
  }
  if (numBytesPerTransfer % 4)
  {
    printf("[ERROR] numBytesPerTransfer (%lu) must be a multiple of 4\n", numBytesPerTransfer);
    exit(1);
  }

  // Check for preset tests
  // - Tests that sweep across possible sets of Transfers
  if (!strcmp(argv[1], "sweep") || !strcmp(argv[1], "rsweep"))
  {
    int numGpuSubExecs = (argc > 3 ? atoi(argv[3]) : 4);
    int numCpuSubExecs = (argc > 4 ? atoi(argv[4]) : 4);

    ev.configMode = CFG_SWEEP;
    RunSweepPreset(ev, numBytesPerTransfer, numGpuSubExecs, numCpuSubExecs, !strcmp(argv[1], "rsweep"));
    exit(0);
  }
  // - Tests that benchmark peer-to-peer performance
  else if (!strcmp(argv[1], "p2p"))
  {
    ev.configMode = CFG_P2P;
    RunPeerToPeerBenchmarks(ev, numBytesPerTransfer / sizeof(float));
    exit(0);
  }
  // - Test SubExecutor scaling
  else if (!strcmp(argv[1], "scaling"))
  {
    int maxSubExecs = (argc > 3 ? atoi(argv[3]) : 32);
    int exeIndex    = (argc > 4 ? atoi(argv[4]) : 0);

    if (exeIndex >= ev.numGpuDevices)
    {
      printf("[ERROR] Cannot execute scaling test with GPU device %d\n", exeIndex);
      exit(1);
    }
    ev.configMode = CFG_SCALE;
    RunScalingBenchmark(ev, numBytesPerTransfer / sizeof(float), exeIndex, maxSubExecs);
    exit(0);
  }
  // - Test all2all benchmark
  else if (!strcmp(argv[1], "a2a"))
  {
    int numSubExecs = (argc > 3 ? atoi(argv[3]) : 4);

    // Force single-stream mode for all-to-all benchmark
    ev.useSingleStream = 1;
    ev.configMode = CFG_A2A;
    RunAllToAllBenchmark(ev, numBytesPerTransfer, numSubExecs);
    exit(0);
  }
  // Health check
  else if (!strcmp(argv[1], "healthcheck")) {
    RunHealthCheck(ev);
    exit(0);
  }
  // - Test schmoo benchmark
  else if (!strcmp(argv[1], "schmoo"))
  {
    if (ev.numGpuDevices < 2)
    {
      printf("[ERROR] Schmoo benchmark requires at least 2 GPUs\n");
      exit(1);
    }
    ev.configMode = CFG_SCHMOO;

    int localIdx    = (argc > 3 ? atoi(argv[3]) : 0);
    int remoteIdx   = (argc > 4 ? atoi(argv[4]) : 1);
    int maxSubExecs = (argc > 5 ? atoi(argv[5]) : 32);

    if (localIdx >= ev.numGpuDevices || remoteIdx >= ev.numGpuDevices)
    {
      printf("[ERROR] Cannot execute schmoo test with local GPU device %d, remote GPU device %d\n", localIdx, remoteIdx);
      exit(1);
    }
    ev.DisplaySchmooEnvVars();

    for (int N = 256; N <= (1<<27); N *= 2)
    {
      int delta = std::max(1, N / ev.samplingFactor);
      int curr = (numBytesPerTransfer == 0) ? N : numBytesPerTransfer / sizeof(float);
      do
      {
        RunSchmooBenchmark(ev, curr * sizeof(float), localIdx, remoteIdx, maxSubExecs);
        if (numBytesPerTransfer != 0) exit(0);
        curr += delta;
      } while (curr < N * 2);
    }
  }
  else if (!strcmp(argv[1], "rwrite"))
  {
    if (ev.numGpuDevices < 2)
    {
      printf("[ERROR] Remote write benchmark requires at least 2 GPUs\n");
      exit(1);
    }
    ev.DisplayRemoteWriteEnvVars();

    int numSubExecs = (argc > 3 ? atoi(argv[3]) : 4);
    int srcIdx      = (argc > 4 ? atoi(argv[4]) : 0);
    int minGpus     = (argc > 5 ? atoi(argv[5]) : 1);
    int maxGpus     = (argc > 6 ? atoi(argv[6]) : ev.numGpuDevices - 1);

    for (int N = 256; N <= (1<<27); N *= 2)
    {
      int delta = std::max(1, N / ev.samplingFactor);
      int curr = (numBytesPerTransfer == 0) ? N : numBytesPerTransfer / sizeof(float);
      do
      {
        RunRemoteWriteBenchmark(ev, curr * sizeof(float), numSubExecs, srcIdx, minGpus, maxGpus);
        if (numBytesPerTransfer != 0) exit(0);
        curr += delta;
      } while (curr < N * 2);
    }
  }
  else if (!strcmp(argv[1], "pcopy"))
  {
    if (ev.numGpuDevices < 2)
    {
      printf("[ERROR] Parallel copy benchmark requires at least 2 GPUs\n");
      exit(1);
    }
    ev.DisplayParallelCopyEnvVars();

    int numSubExecs = (argc > 3 ? atoi(argv[3]) : 8);
    int srcIdx      = (argc > 4 ? atoi(argv[4]) : 0);
    int minGpus     = (argc > 5 ? atoi(argv[5]) : 1);
    int maxGpus     = (argc > 6 ? atoi(argv[6]) : ev.numGpuDevices - 1);

    if (maxGpus > ev.gpuMaxHwQueues && ev.useDmaCopy)
    {
      printf("[ERROR] DMA executor %d attempting %d parallel transfers, however GPU_MAX_HW_QUEUES only set to %d\n",
             srcIdx, maxGpus, ev.gpuMaxHwQueues);
      printf("[ERROR] Aborting to avoid misleading results due to potential serialization of Transfers\n");
      exit(1);
    }

    for (int N = 256; N <= (1<<27); N *= 2)
    {
      int delta = std::max(1, N / ev.samplingFactor);
      int curr = (numBytesPerTransfer == 0) ? N : numBytesPerTransfer / sizeof(float);
      do
      {
        RunParallelCopyBenchmark(ev, curr * sizeof(float), numSubExecs, srcIdx, minGpus, maxGpus);
        if (numBytesPerTransfer != 0) exit(0);
        curr += delta;
      } while (curr < N * 2);
    }
  }
  else if (!strcmp(argv[1], "cmdline"))
  {
    // Print environment variables
    ev.DisplayEnvVars();

    // Read Transfer from command line
    std::string cmdlineTransfer;
    for (int i = 3; i < argc; i++)
      cmdlineTransfer += std::string(argv[i]) + " ";

    char line[MAX_LINE_LEN];
    sprintf(line, "%s", cmdlineTransfer.c_str());
    std::vector<Transfer> transfers;
    ParseTransfers(ev, line, transfers);
    if (transfers.empty()) exit(0);

    // If the number of bytes is specified, use it
    if (numBytesPerTransfer != 0)
    {
      size_t N = numBytesPerTransfer / sizeof(float);
      ExecuteTransfers(ev, 1, N, transfers);
    }
    else
    {
      // Otherwise generate a range of values
      for (int N = 256; N <= (1<<27); N *= 2)
      {
        int delta = std::max(1, N / ev.samplingFactor);
        int curr = N;
        while (curr < N * 2)
        {
          ExecuteTransfers(ev, 1, curr, transfers);
          curr += delta;
        }
      }
    }
    exit(0);
  }

  // Check that Transfer configuration file can be opened
  ev.configMode = CFG_FILE;
  FILE* fp = fopen(argv[1], "r");
  if (!fp)
  {
    printf("[ERROR] Unable to open transfer configuration file: [%s]\n", argv[1]);
    exit(1);
  }

  // Print environment variables and CSV header
  ev.DisplayEnvVars();

  int testNum = 0;
  char line[MAX_LINE_LEN];
  while(fgets(line, MAX_LINE_LEN, fp))
  {
    // Check if line is a comment to be echoed to output (starts with ##)
    if (!ev.outputToCsv && line[0] == '#' && line[1] == '#') printf("%s", line);

    // Parse set of parallel Transfers to execute
    std::vector<Transfer> transfers;
    ParseTransfers(ev, line, transfers);
    if (transfers.empty()) continue;

    // If the number of bytes is specified, use it
    if (numBytesPerTransfer != 0)
    {
      size_t N = numBytesPerTransfer / sizeof(float);
      ExecuteTransfers(ev, ++testNum, N, transfers);
    }
    else
    {
      // Otherwise generate a range of values
      for (int N = 256; N <= (1<<27); N *= 2)
      {
        int delta = std::max(1, N / ev.samplingFactor);
        int curr = N;
        while (curr < N * 2)
        {
          ExecuteTransfers(ev, ++testNum, curr, transfers);
          curr += delta;
        }
      }
    }
  }
  fclose(fp);

  return 0;
}

void ExecuteTransfers(EnvVars const& ev,
                      int const testNum,
                      size_t const N,
                      std::vector<Transfer>& transfers,
                      bool verbose,
                      double* totalBandwidthCpu)
{
  // Check for any Transfers using variable number of sub-executors
  std::vector<int> varTransfers;
  std::vector<int> numUsedSubExec(ev.numGpuDevices, 0);
  std::vector<int> numVarSubExec(ev.numGpuDevices, 0);

  for (int i = 0; i < transfers.size(); i++) {
    Transfer& t = transfers[i];
    t.transferIndex = i;
    t.numBytesActual = (t.numBytes ? t.numBytes : N * sizeof(float));

    if (t.exeType == EXE_GPU_GFX) {
      if (t.numSubExecs == 0) {
        varTransfers.push_back(i);
        numVarSubExec[t.exeIndex]++;
      } else {
        numUsedSubExec[t.exeIndex] += t.numSubExecs;
      }
    } else if (t.numSubExecs == 0) {
      printf("[ERROR] Variable subexecutor count is only supported for GFX executor\n");
      exit(1);
    }
  }

  if (verbose && !ev.outputToCsv) printf("Test %d:\n", testNum);

  TestResults testResults;
  if (varTransfers.size() == 0) {
    testResults = ExecuteTransfersImpl(ev, transfers);
  } else {
    // Determine maximum number of subexecutors
    int maxNumSubExec = 0;
    if (ev.maxNumVarSubExec) {
      maxNumSubExec = ev.maxNumVarSubExec;
    } else {
      HIP_CALL(hipDeviceGetAttribute(&maxNumSubExec, hipDeviceAttributeMultiprocessorCount, 0));
      for (int device = 0; device < ev.numGpuDevices; device++) {
        int numSubExec = 0;
        HIP_CALL(hipDeviceGetAttribute(&numSubExec, hipDeviceAttributeMultiprocessorCount, device));
        int leftOverSubExec = numSubExec - numUsedSubExec[device];
        if (leftOverSubExec < numVarSubExec[device])
          maxNumSubExec = 1;
        else if (numVarSubExec[device] != 0) {
          maxNumSubExec = std::min(maxNumSubExec, leftOverSubExec / numVarSubExec[device]);
        }
      }
    }

    // Loop over subexecs
    std::vector<Transfer> bestTransfers;
    for (int numSubExec = ev.minNumVarSubExec; numSubExec <= maxNumSubExec; numSubExec++) {
      std::vector<Transfer> currTransfers = transfers;
      for (auto idx : varTransfers) {
        currTransfers[idx].numSubExecs = numSubExec;
      }
      TestResults tempResults = ExecuteTransfersImpl(ev, currTransfers);
      if (tempResults.totalBandwidthCpu > testResults.totalBandwidthCpu) {
        bestTransfers = currTransfers;
        testResults = tempResults;
      }
    }
    transfers = bestTransfers;
  }
  if (totalBandwidthCpu) *totalBandwidthCpu = testResults.totalBandwidthCpu;

  if (verbose) {
    ReportResults(ev, transfers, testResults);
  }
}

TestResults ExecuteTransfersImpl(EnvVars const& ev,
                                 std::vector<Transfer>& transfers)
{
  // Map transfers by executor
  TransferMap transferMap;
  for (int i = 0; i < transfers.size(); i++)
  {
    Transfer& transfer = transfers[i];
    transfer.transferIndex = i;
    Executor executor(transfer.exeType, transfer.exeIndex);
    ExecutorInfo& executorInfo = transferMap[executor];
    executorInfo.transfers.push_back(&transfer);
  }

  // Loop over each executor and prepare sub-executors
  std::map<int, Transfer*> transferList;
  for (auto& exeInfoPair : transferMap)
  {
    Executor const& executor = exeInfoPair.first;
    ExecutorInfo& exeInfo    = exeInfoPair.second;
    ExeType const exeType    = executor.first;
    int     const exeIndex   = RemappedIndex(executor.second, IsCpuType(exeType));

    exeInfo.totalTime = 0.0;
    exeInfo.totalSubExecs = 0;

    // Loop over each transfer this executor is involved in
    for (Transfer* transfer : exeInfo.transfers)
    {
      // Allocate source memory
      transfer->srcMem.resize(transfer->numSrcs);
      for (int iSrc = 0; iSrc < transfer->numSrcs; ++iSrc)
      {
        MemType const& srcType  = transfer->srcType[iSrc];
        int     const  srcIndex = RemappedIndex(transfer->srcIndex[iSrc], IsCpuType(srcType));

        // Ensure executing GPU can access source memory
        if (IsGpuType(exeType) && IsGpuType(srcType) && srcIndex != exeIndex)
          EnablePeerAccess(exeIndex, srcIndex);

        AllocateMemory(srcType, srcIndex, transfer->numBytesActual + ev.byteOffset, (void**)&transfer->srcMem[iSrc]);
      }

      // Allocate destination memory
      transfer->dstMem.resize(transfer->numDsts);
      for (int iDst = 0; iDst < transfer->numDsts; ++iDst)
      {
        MemType const& dstType  = transfer->dstType[iDst];
        int     const  dstIndex = RemappedIndex(transfer->dstIndex[iDst], IsCpuType(dstType));

        // Ensure executing GPU can access destination memory
        if (IsGpuType(exeType) && IsGpuType(dstType) && dstIndex != exeIndex)
          EnablePeerAccess(exeIndex, dstIndex);

        AllocateMemory(dstType, dstIndex, transfer->numBytesActual + ev.byteOffset, (void**)&transfer->dstMem[iDst]);
      }

      exeInfo.totalSubExecs += transfer->numSubExecs;
      transferList[transfer->transferIndex] = transfer;
    }

    // Prepare additional requirement for GPU-based executors
    if (IsGpuType(exeType))
    {
      HIP_CALL(hipSetDevice(exeIndex));

      // Single-stream is only supported for GFX-based executors
      int const numStreamsToUse = (exeType == EXE_GPU_DMA || !ev.useSingleStream) ? exeInfo.transfers.size() : 1;
      exeInfo.streams.resize(numStreamsToUse);
      exeInfo.startEvents.resize(numStreamsToUse);
      exeInfo.stopEvents.resize(numStreamsToUse);
      for (int i = 0; i < numStreamsToUse; ++i)
      {
        if (ev.cuMask.size())
        {
#if !defined(__NVCC__)
          HIP_CALL(hipExtStreamCreateWithCUMask(&exeInfo.streams[i], ev.cuMask.size(), ev.cuMask.data()));
#else
          printf("[ERROR] CU Masking in not supported on NVIDIA hardware\n");
          exit(-1);
#endif
        }
        else
        {
          HIP_CALL(hipStreamCreate(&exeInfo.streams[i]));
        }
        HIP_CALL(hipEventCreate(&exeInfo.startEvents[i]));
        HIP_CALL(hipEventCreate(&exeInfo.stopEvents[i]));
      }

      if (exeType == EXE_GPU_GFX)
      {
        // Allocate one contiguous chunk of GPU memory for threadblock parameters
        // This allows support for executing one transfer per stream, or all transfers in a single stream
#if !defined(__NVCC__)
        AllocateMemory(MEM_GPU, exeIndex, exeInfo.totalSubExecs * sizeof(SubExecParam),
                       (void**)&exeInfo.subExecParamGpu);
#else
        AllocateMemory(MEM_MANAGED, exeIndex, exeInfo.totalSubExecs * sizeof(SubExecParam),
                       (void**)&exeInfo.subExecParamGpu);
#endif

        // Check for sufficient subExecutors
        int numDeviceCUs = 0;
        HIP_CALL(hipDeviceGetAttribute(&numDeviceCUs, hipDeviceAttributeMultiprocessorCount, exeIndex));
        if (exeInfo.totalSubExecs > numDeviceCUs)
        {
          printf("[WARN] GFX executor %d requesting %d total subexecutors, however only has %d.  Some Transfers may be serialized\n",
                 exeIndex, exeInfo.totalSubExecs, numDeviceCUs);
        }
      }

      // Check for targeted DMA
      if (exeType == EXE_GPU_DMA)
      {
        bool useRandomDma = false;
        bool useTargetDma = false;

        // Check for sufficient hardware queues
#if !defined(__NVCC_)
        if (exeInfo.transfers.size() > ev.gpuMaxHwQueues)
        {
          printf("[WARN] DMA executor %d attempting %lu parallel transfers, however GPU_MAX_HW_QUEUES only set to %d\n",
                 exeIndex, exeInfo.transfers.size(), ev.gpuMaxHwQueues);
        }
#endif

        for (Transfer* transfer : exeInfo.transfers)
        {
          if (transfer->exeSubIndex != -1 || ev.useHsaDma)
          {
            useTargetDma = (transfer->exeSubIndex != -1);

#if defined(__NVCC__)
            printf("[ERROR] DMA executor subindex not supported on NVIDIA hardware\n");
            exit(-1);
#else
            if (transfer->numSrcs != 1 || transfer->numDsts != 1)
            {
              printf("[ERROR] DMA Transfer must have at exactly one source and one destination");
              exit(1);
            }

            // Collect HSA agent information

            hsa_amd_pointer_info_t info;
            info.size = sizeof(info);

            HSA_CHECK(hsa_amd_pointer_info(transfer->dstMem[0], &info, NULL, NULL, NULL));
            transfer->dstAgent = info.agentOwner;

            HSA_CHECK(hsa_amd_pointer_info(transfer->srcMem[0], &info, NULL, NULL, NULL));
            transfer->srcAgent = info.agentOwner;

            // Create HSA completion signal
            HSA_CHECK(hsa_signal_create(1, 0, NULL, &transfer->signal));

            // Check for valid engine Id
            if (transfer->exeSubIndex < -1 || transfer->exeSubIndex >= 32)
            {
              printf("[ERROR] DMA executor subindex must be between 0 and 31\n");
              exit(1);
            }

            // Check that engine Id exists between agents
            if (useTargetDma) {
              uint32_t engineIdMask = 0;
              HSA_CHECK(hsa_amd_memory_copy_engine_status(transfer->dstAgent,
                                                          transfer->srcAgent,
                                                          &engineIdMask));
              transfer->sdmaEngineId = (hsa_amd_sdma_engine_id_t)(1U << transfer->exeSubIndex);
              if (!(transfer->sdmaEngineId & engineIdMask))
              {
                printf("[ERROR] DMA executor %d.%d does not exist or cannot copy between source %s to destination %s\n",
                       transfer->exeIndex, transfer->exeSubIndex,
                       transfer->SrcToStr().c_str(),
                       transfer->DstToStr().c_str());
                exit(1);
              }
            }
#endif
          }
          else
          {
            useRandomDma = true;
          }
        }
        if (useRandomDma && useTargetDma)
        {
          printf("[WARN] Mixing targeted and untargetted DMA execution on GPU %d may result in resource conflicts\n",
            exeIndex);
        }
      }
    }
  }


  // Prepare input memory and block parameters for current N
  bool isSrcCorrect = true;
  for (auto& exeInfoPair : transferMap)
  {
    Executor const& executor = exeInfoPair.first;
    ExecutorInfo& exeInfo    = exeInfoPair.second;
    ExeType const exeType    = executor.first;
    int     const exeIndex   = RemappedIndex(executor.second, IsCpuType(exeType));

    exeInfo.totalBytes = 0;
    for (int i = 0; i < exeInfo.transfers.size(); ++i)
    {
      // Prepare subarrays each threadblock works on and fill src memory with patterned data
      Transfer* transfer = exeInfo.transfers[i];
      transfer->PrepareSubExecParams(ev);
      isSrcCorrect &= transfer->PrepareSrc(ev);
      exeInfo.totalBytes += transfer->numBytesActual;
    }

    // Copy block parameters to GPU for GPU executors
    if (exeType == EXE_GPU_GFX)
    {
      std::vector<SubExecParam> tempSubExecParam;

      if (!ev.useSingleStream || (ev.blockOrder == ORDER_SEQUENTIAL))
      {
        // Assign Transfers to sequentual threadblocks
        int transferOffset = 0;
        for (Transfer* transfer : exeInfo.transfers)
        {
          transfer->subExecParamGpuPtr = exeInfo.subExecParamGpu + transferOffset;

          transfer->subExecIdx.clear();
          for (int subExecIdx = 0; subExecIdx < transfer->subExecParam.size(); subExecIdx++)
          {
            transfer->subExecIdx.push_back(transferOffset + subExecIdx);
            tempSubExecParam.push_back(transfer->subExecParam[subExecIdx]);
          }
          transferOffset += transfer->numSubExecs;
        }
      }
      else if (ev.blockOrder == ORDER_INTERLEAVED)
      {
        // Interleave threadblocks of different Transfers
        exeInfo.transfers[0]->subExecParamGpuPtr = exeInfo.subExecParamGpu;
        for (int subExecIdx = 0; tempSubExecParam.size() < exeInfo.totalSubExecs; ++subExecIdx)
        {
          for (Transfer* transfer : exeInfo.transfers)
          {
            if (subExecIdx < transfer->numSubExecs)
            {
              transfer->subExecIdx.push_back(tempSubExecParam.size());
              tempSubExecParam.push_back(transfer->subExecParam[subExecIdx]);
            }
          }
        }
      }
      else if (ev.blockOrder == ORDER_RANDOM)
      {
        std::vector<std::pair<int,int>> indices;
        exeInfo.transfers[0]->subExecParamGpuPtr = exeInfo.subExecParamGpu;

        // Build up a list of (transfer,subExecParam) indices, then randomly sort them
        for (int i = 0; i < exeInfo.transfers.size(); i++)
        {
          Transfer* transfer = exeInfo.transfers[i];
          for (int subExecIdx = 0; subExecIdx < transfer->numSubExecs; subExecIdx++)
            indices.push_back(std::make_pair(i, subExecIdx));
        }
        std::shuffle(indices.begin(), indices.end(), *ev.generator);

        // Build randomized threadblock list
        for (auto p : indices)
        {
          Transfer* transfer = exeInfo.transfers[p.first];
          transfer->subExecIdx.push_back(tempSubExecParam.size());
          tempSubExecParam.push_back(transfer->subExecParam[p.second]);
        }
      }

      HIP_CALL(hipSetDevice(exeIndex));
      HIP_CALL(hipMemcpy(exeInfo.subExecParamGpu,
                         tempSubExecParam.data(),
                         tempSubExecParam.size() * sizeof(SubExecParam),
                         hipMemcpyDefault));
      HIP_CALL(hipDeviceSynchronize());
    }
  }

  // Launch kernels (warmup iterations are not counted)
  double totalCpuTime = 0;
  size_t numTimedIterations = 0;
  std::stack<std::thread> threads;
  for (int iteration = -ev.numWarmups; isSrcCorrect; iteration++)
  {
    if (ev.numIterations > 0 && iteration    >= ev.numIterations) break;
    if (ev.numIterations < 0 && totalCpuTime > -ev.numIterations) break;

    // Pause before starting first timed iteration in interactive mode
    if (ev.useInteractive && iteration == 0)
    {
      printf("Memory prepared:\n");

      for (Transfer& transfer : transfers)
      {
        printf("Transfer %03d:\n", transfer.transferIndex);
        for (int iSrc = 0; iSrc < transfer.numSrcs; ++iSrc)
          printf("  SRC %0d: %p\n", iSrc, transfer.srcMem[iSrc]);
        for (int iDst = 0; iDst < transfer.numDsts; ++iDst)
          printf("  DST %0d: %p\n", iDst, transfer.dstMem[iDst]);
      }
      printf("Hit <Enter> to continue: ");
      if (scanf("%*c") != 0)
      {
        printf("[ERROR] Unexpected input\n");
        exit(1);
      }
      printf("\n");
    }

    // Start CPU timing for this iteration
    auto cpuStart = std::chrono::high_resolution_clock::now();

    // Execute all Transfers in parallel
    for (auto& exeInfoPair : transferMap)
    {
      ExecutorInfo& exeInfo = exeInfoPair.second;
      ExeType       exeType = exeInfoPair.first.first;
      int const numTransfersToRun = (exeType == EXE_GPU_GFX && ev.useSingleStream) ? 1 : exeInfo.transfers.size();

      for (int i = 0; i < numTransfersToRun; ++i)
        threads.push(std::thread(RunTransfer, std::ref(ev), iteration, std::ref(exeInfo), i));
    }

    // Wait for all threads to finish
    int const numTransfers = threads.size();
    for (int i = 0; i < numTransfers; i++)
    {
      threads.top().join();
      threads.pop();
    }

    // Stop CPU timing for this iteration
    auto cpuDelta = std::chrono::high_resolution_clock::now() - cpuStart;
    double deltaSec = std::chrono::duration_cast<std::chrono::duration<double>>(cpuDelta).count();

    if (ev.alwaysValidate)
    {
      for (auto transferPair : transferList)
      {
        Transfer* transfer = transferPair.second;
        transfer->ValidateDst(ev);
      }
    }

    if (iteration >= 0)
    {
      ++numTimedIterations;
      totalCpuTime += deltaSec;
    }
  }

  // Pause for interactive mode
  if (isSrcCorrect && ev.useInteractive)
  {
    printf("Transfers complete. Hit <Enter> to continue: ");
    if (scanf("%*c") != 0)
    {
      printf("[ERROR] Unexpected input\n");
      exit(1);
    }
    printf("\n");
  }

  // Validate that each transfer has transferred correctly
  size_t totalBytesTransferred = 0;
  int const numTransfers = transferList.size();
  for (auto transferPair : transferList)
  {
    Transfer* transfer = transferPair.second;
    transfer->ValidateDst(ev);
    totalBytesTransferred += transfer->numBytesActual;
  }

  // Record results
  TestResults testResults;
  testResults.numTimedIterations = numTimedIterations;
  testResults.totalBytesTransferred = totalBytesTransferred;
  testResults.totalDurationMsec = totalCpuTime / (1.0 * numTimedIterations * ev.numSubIterations) * 1000;
  testResults.totalBandwidthCpu = (totalBytesTransferred / 1.0E6) / testResults.totalDurationMsec;

  double maxExeDurationMsec = 0.0;
  if (!isSrcCorrect) goto cleanup;

  for (auto& exeInfoPair : transferMap)
  {
    ExecutorInfo  exeInfo  = exeInfoPair.second;
    ExeType const exeType  = exeInfoPair.first.first;
    int     const exeIndex = exeInfoPair.first.second;
    ExeResult& exeResult   = testResults.exeResults[std::make_pair(exeType, exeIndex)];

    // Compute total time for non GPU executors
    if (exeType != EXE_GPU_GFX || ev.useSingleStream == 0)
    {
      exeInfo.totalTime = 0;
      for (auto const& transfer : exeInfo.transfers)
        exeInfo.totalTime = std::max(exeInfo.totalTime, transfer->transferTime);
    }

    exeResult.totalBytes      = exeInfo.totalBytes;
    exeResult.durationMsec    = exeInfo.totalTime / (1.0 * numTimedIterations * ev.numSubIterations);
    exeResult.bandwidthGbs    = (exeInfo.totalBytes / 1.0E9) / exeResult.durationMsec * 1000.0f;
    exeResult.sumBandwidthGbs = 0;
    maxExeDurationMsec        = std::max(maxExeDurationMsec, exeResult.durationMsec);

    for (auto& transfer: exeInfo.transfers)
    {
      exeResult.transferIdx.push_back(transfer->transferIndex);
      transfer->transferTime /= (1.0 * numTimedIterations * ev.numSubIterations);
      transfer->transferBandwidth = (transfer->numBytesActual / 1.0E9) / transfer->transferTime * 1000.0f;
      transfer->executorBandwidth = exeResult.bandwidthGbs;
      exeResult.sumBandwidthGbs += transfer->transferBandwidth;
    }
  }
  testResults.overheadMsec = testResults.totalDurationMsec - maxExeDurationMsec;

  // Release GPU memory
cleanup:
  for (auto exeInfoPair : transferMap)
  {
    ExecutorInfo& exeInfo  = exeInfoPair.second;
    ExeType const exeType  = exeInfoPair.first.first;
    int     const exeIndex = RemappedIndex(exeInfoPair.first.second, IsCpuType(exeType));

    for (auto& transfer : exeInfo.transfers)
    {
      for (int iSrc = 0; iSrc < transfer->numSrcs; ++iSrc)
      {
        MemType const& srcType = transfer->srcType[iSrc];
        DeallocateMemory(srcType, transfer->srcMem[iSrc], transfer->numBytesActual + ev.byteOffset);
      }
      for (int iDst = 0; iDst < transfer->numDsts; ++iDst)
      {
        MemType const& dstType = transfer->dstType[iDst];
        DeallocateMemory(dstType, transfer->dstMem[iDst], transfer->numBytesActual + ev.byteOffset);
      }
      transfer->subExecParam.clear();

      if (exeType == EXE_GPU_DMA && (transfer->exeSubIndex != -1 || ev.useHsaDma))
      {
#if !defined(__NVCC__)
        HSA_CHECK(hsa_signal_destroy(transfer->signal));
#endif
      }
    }

    if (IsGpuType(exeType))
    {
      int const numStreams = (int)exeInfo.streams.size();
      for (int i = 0; i < numStreams; ++i)
      {
        HIP_CALL(hipEventDestroy(exeInfo.startEvents[i]));
        HIP_CALL(hipEventDestroy(exeInfo.stopEvents[i]));
        HIP_CALL(hipStreamDestroy(exeInfo.streams[i]));
      }

      if (exeType == EXE_GPU_GFX)
      {
#if !defined(__NVCC__)
        DeallocateMemory(MEM_GPU, exeInfo.subExecParamGpu);
#else
        DeallocateMemory(MEM_MANAGED, exeInfo.subExecParamGpu);
#endif
      }
    }
  }

  return testResults;
}

void DisplayUsage(char const* cmdName)
{
  printf("TransferBench v%s\n", TB_VERSION);
  printf("========================================\n");

  if (numa_available() == -1)
  {
    printf("[ERROR] NUMA library not supported. Check to see if libnuma has been installed on this system\n");
    exit(1);
  }
  int numGpuDevices;
  HIP_CALL(hipGetDeviceCount(&numGpuDevices));
  int const numCpuDevices = numa_num_configured_nodes();

  printf("Usage: %s config <N>\n", cmdName);
  printf("  config: Either:\n");
  printf("          - Filename of configFile containing Transfers to execute (see example.cfg for format)\n");
  printf("          - Name of preset config:\n");
  printf("              a2a          - GPU All-To-All benchmark\n");
  printf("                             - 3rd optional arg: # of SubExecs to use\n");
  printf("              cmdline      - Read Transfers from command line arguments (after N)\n");
  printf("              healthcheck  - Simple bandwidth health check (MI300 series only)\n");
  printf("              p2p          - Peer-to-peer benchmark tests\n");
  printf("              rwrite/pcopy - Parallel writes/copies from single GPU to other GPUs\n");
  printf("                             - 3rd optional arg: # GPU SubExecs per Transfer\n");
  printf("                             - 4th optional arg: Root GPU index\n");
  printf("                             - 5th optional arg: Min number of other GPUs to transfer to\n");
  printf("                             - 6th optional arg: Max number of other GPUs to transfer to\n");
  printf("              sweep/rsweep - Sweep/random sweep across possible sets of Transfers\n");
  printf("                             - 3rd optional arg: # GPU SubExecs per Transfer\n");
  printf("                             - 4th optional arg: # CPU SubExecs per Transfer\n");
  printf("              scaling      - GPU GFX SubExec scaling copy test\n");
  printf("                             - 3th optional arg: Max # of SubExecs to use\n");
  printf("                             - 4rd optional arg: GPU index to use as executor\n");
  printf("              schmoo       - Local/RemoteRead/Write/Copy between two GPUs\n");
  printf("  N     : (Optional) Number of bytes to copy per Transfer.\n");
  printf("          If not specified, defaults to %lu bytes. Must be a multiple of 4 bytes\n",
         DEFAULT_BYTES_PER_TRANSFER);
  printf("          If 0 is specified, a range of Ns will be benchmarked\n");
  printf("          May append a suffix ('K', 'M', 'G') for kilobytes / megabytes / gigabytes\n");
  printf("\n");

  EnvVars::DisplayUsage();
}

int RemappedIndex(int const origIdx, bool const isCpuType)
{
  static std::vector<int> remappingCpu;
  static std::vector<int> remappingGpu;

  // Build CPU remapping on first use
  // Skip numa nodes that are not configured
  if (remappingCpu.empty())
  {
    for (int node = 0; node <= numa_max_node(); node++)
      if (numa_bitmask_isbitset(numa_get_mems_allowed(), node))
        remappingCpu.push_back(node);
  }

  // Build remappingGpu on first use
  if (remappingGpu.empty())
  {
    int numGpuDevices;
    HIP_CALL(hipGetDeviceCount(&numGpuDevices));
    remappingGpu.resize(numGpuDevices);

    int const usePcieIndexing = getenv("USE_PCIE_INDEX") ? atoi(getenv("USE_PCIE_INDEX")) : 0;
    if (!usePcieIndexing)
    {
      // For HIP-based indexing no remappingGpu is necessary
      for (int i = 0; i < numGpuDevices; ++i)
        remappingGpu[i] = i;
    }
    else
    {
      // Collect PCIe address for each GPU
      std::vector<std::pair<std::string, int>> mapping;
      char pciBusId[20];
      for (int i = 0; i < numGpuDevices; ++i)
      {
        HIP_CALL(hipDeviceGetPCIBusId(pciBusId, 20, i));
        mapping.push_back(std::make_pair(pciBusId, i));
      }
      // Sort GPUs by PCIe address then use that as mapping
      std::sort(mapping.begin(), mapping.end());
      for (int i = 0; i < numGpuDevices; ++i)
        remappingGpu[i] = mapping[i].second;
    }
  }
  return isCpuType ? remappingCpu[origIdx] : remappingGpu[origIdx];
}

void DisplayTopology(bool const outputToCsv)
{

  int numCpuDevices = numa_num_configured_nodes();
  int numGpuDevices;
  HIP_CALL(hipGetDeviceCount(&numGpuDevices));

  if (outputToCsv)
  {
    printf("NumCpus,%d\n", numCpuDevices);
    printf("NumGpus,%d\n", numGpuDevices);
  }
  else
  {
    printf("\nDetected topology: %d configured CPU NUMA node(s) [%d total]   %d GPU device(s)\n",
           numa_num_configured_nodes(), numa_max_node() + 1, numGpuDevices);
  }

  // Print out detected CPU topology
  if (outputToCsv)
  {
    printf("NUMA");
    for (int j = 0; j < numCpuDevices; j++)
      printf(",NUMA%02d", j);
    printf(",# CPUs,ClosestGPUs,ActualNode\n");
  }
  else
  {
    printf("            |");
    for (int j = 0; j < numCpuDevices; j++)
      printf("NUMA %02d|", j);
    printf(" #Cpus | Closest GPU(s)\n");

    printf("------------+");
    for (int j = 0; j <= numCpuDevices; j++)
      printf("-------+");
    printf("---------------\n");
  }

  for (int i = 0; i < numCpuDevices; i++)
  {
    int nodeI = RemappedIndex(i, true);
    printf("NUMA %02d (%02d)%s", i, nodeI, outputToCsv ? "," : "|");
    for (int j = 0; j < numCpuDevices; j++)
    {
      int nodeJ = RemappedIndex(j, true);
      int numaDist = numa_distance(nodeI, nodeJ);
      if (outputToCsv)
        printf("%d,", numaDist);
      else
        printf(" %5d |", numaDist);
    }

    int numCpus = 0;
    for (int j = 0; j < numa_num_configured_cpus(); j++)
      if (numa_node_of_cpu(j) == nodeI) numCpus++;
    if (outputToCsv)
      printf("%d,", numCpus);
    else
      printf(" %5d | ", numCpus);

#if !defined(__NVCC__)
    bool isFirst = true;
    for (int j = 0; j < numGpuDevices; j++)
    {
      if (GetClosestNumaNode(RemappedIndex(j, false)) == i)
      {
        if (isFirst) isFirst = false;
        else printf(",");
        printf("%d", j);
      }
    }
#endif
    printf("\n");
  }
  printf("\n");

#if defined(__NVCC__)

  for (int i = 0; i < numGpuDevices; i++)
  {
    hipDeviceProp_t prop;
    HIP_CALL(hipGetDeviceProperties(&prop, i));
    printf(" GPU %02d | %s\n", i, prop.name);
  }

  // No further topology detection done for NVIDIA platforms
  return;
#else
    // Figure out DMA engines per GPU
  std::vector<std::set<int>> dmaEngineIdsPerDevice(numGpuDevices);
  {
    std::vector<hsa_agent_t> gpuAgentList;
    std::vector<hsa_agent_t> allAgentList;
    hsa_amd_pointer_info_t info;
    info.size = sizeof(info);

    for (int deviceId = 0; deviceId < numGpuDevices; deviceId++)
    {
      HIP_CALL(hipSetDevice(deviceId));
      int32_t* tempGpuBuffer;
      HIP_CALL(hipMalloc((void**)&tempGpuBuffer, 1024));
      HSA_CHECK(hsa_amd_pointer_info(tempGpuBuffer, &info, NULL, NULL, NULL));
      gpuAgentList.push_back(info.agentOwner);
      allAgentList.push_back(info.agentOwner);
      HIP_CALL(hipFree(tempGpuBuffer));
    }
    for (int deviceId = 0; deviceId < numCpuDevices; deviceId++)
    {
      int32_t* tempCpuBuffer;
      AllocateMemory(MEM_CPU, deviceId, 1024, (void**)&tempCpuBuffer);
      HSA_CHECK(hsa_amd_pointer_info(tempCpuBuffer, &info, NULL, NULL, NULL));
      allAgentList.push_back(info.agentOwner);
      DeallocateMemory(MEM_CPU, tempCpuBuffer, 1024);
    }

    for (int srcDevice = 0; srcDevice < numGpuDevices; srcDevice++)
    {
      dmaEngineIdsPerDevice[srcDevice].clear();
      for (int dstDevice = 0; dstDevice < allAgentList.size(); dstDevice++)
      {
        if (srcDevice == dstDevice) continue;
        uint32_t engineIdMask = 0;
        if (hsa_amd_memory_copy_engine_status(allAgentList[dstDevice],
                                              gpuAgentList[srcDevice],
                                              &engineIdMask) != HSA_STATUS_SUCCESS)
          continue;
        for (int engineId = 0; engineId < 32; engineId++)
        {
          if (engineIdMask & (1U << engineId))
            dmaEngineIdsPerDevice[srcDevice].insert(engineId);
        }
      }
    }
  }

  // Print out detected GPU topology
  if (outputToCsv)
  {
    printf("GPU");
    for (int j = 0; j < numGpuDevices; j++)
      printf(",GPU %02d", j);
    printf(",PCIe Bus ID,ClosestNUMA,DMA engines\n");
  }
  else
  {
    printf("        |");
    for (int j = 0; j < numGpuDevices; j++)
    {
      hipDeviceProp_t prop;
      HIP_CALL(hipGetDeviceProperties(&prop, j));
      std::string fullName = prop.gcnArchName;
      std::string archName = fullName.substr(0, fullName.find(':'));
      printf(" %6s |", archName.c_str());
    }
    printf("\n");
    printf("        |");
    for (int j = 0; j < numGpuDevices; j++)
      printf(" GPU %02d |", j);
    printf(" PCIe Bus ID  | #CUs | Closest NUMA | DMA engines\n");
    for (int j = 0; j <= numGpuDevices; j++)
      printf("--------+");
    printf("--------------+------+-------------+------------\n");
  }

  char pciBusId[20];
  for (int i = 0; i < numGpuDevices; i++)
  {
    int const deviceIdx = RemappedIndex(i, false);
    printf("%sGPU %02d%s", outputToCsv ? "" : " ", i, outputToCsv ? "," : " |");
    for (int j = 0; j < numGpuDevices; j++)
    {
      if (i == j)
      {
        if (outputToCsv)
          printf("-,");
        else
          printf("    -   |");
      }
      else
      {
        uint32_t linkType, hopCount;
        HIP_CALL(hipExtGetLinkTypeAndHopCount(deviceIdx,
                                              RemappedIndex(j, false),
                                              &linkType, &hopCount));
        printf("%s%s-%d%s",
               outputToCsv ? "" : " ",
               linkType == HSA_AMD_LINK_INFO_TYPE_HYPERTRANSPORT ? "  HT" :
               linkType == HSA_AMD_LINK_INFO_TYPE_QPI            ? " QPI" :
               linkType == HSA_AMD_LINK_INFO_TYPE_PCIE           ? "PCIE" :
               linkType == HSA_AMD_LINK_INFO_TYPE_INFINBAND      ? "INFB" :
               linkType == HSA_AMD_LINK_INFO_TYPE_XGMI           ? "XGMI" : "????",
               hopCount, outputToCsv ? "," : " |");
      }
    }
    HIP_CALL(hipDeviceGetPCIBusId(pciBusId, 20, deviceIdx));

    int numDeviceCUs = 0;
    HIP_CALL(hipDeviceGetAttribute(&numDeviceCUs, hipDeviceAttributeMultiprocessorCount, deviceIdx));

    if (outputToCsv)
      printf("%s,%d,%d,", pciBusId, numDeviceCUs, GetClosestNumaNode(deviceIdx));
    else
    {
      printf(" %11s | %4d | %-12d |", pciBusId, numDeviceCUs, GetClosestNumaNode(deviceIdx));

      bool isFirst = true;
      for (auto x : dmaEngineIdsPerDevice[deviceIdx])
      {
        if (isFirst) isFirst = false; else printf(",");
        printf("%d", x);
      }
      printf("\n");
    }
  }

  // Check that large BAR is enabled on all GPUs
  for (int i = 0; i < numGpuDevices; i++) {
    int const deviceIdx = RemappedIndex(i, false);
    int isLargeBar = 0;
    HIP_CALL(hipDeviceGetAttribute(&isLargeBar, hipDeviceAttributeIsLargeBar, deviceIdx));
    if (!isLargeBar)
      printf("[WARN] Large BAR is not enabled for GPU %d in BIOS.  This may result in segfaults\n", i);
  }
#endif
}

void ParseMemType(EnvVars const& ev, std::string const& token,
                  std::vector<MemType>& memTypes, std::vector<int>& memIndices)
{
  char typeChar;
  int offset = 0, devIndex, inc;
  bool found = false;

  memTypes.clear();
  memIndices.clear();
  while (sscanf(token.c_str() + offset, " %c %d%n", &typeChar, &devIndex, &inc) == 2)
  {
    offset += inc;
    MemType memType = CharToMemType(typeChar);

    if (IsCpuType(memType) && (devIndex < 0 || devIndex >= ev.numCpuDevices))
    {
      printf("[ERROR] CPU index must be between 0 and %d (instead of %d)\n", ev.numCpuDevices-1, devIndex);
      exit(1);
    }
    if (IsGpuType(memType) && (devIndex < 0 || devIndex >= ev.numGpuDevices))
    {
      printf("[ERROR] GPU index must be between 0 and %d (instead of %d)\n", ev.numGpuDevices-1, devIndex);
      exit(1);
    }

    found = true;
    if (memType != MEM_NULL)
    {
      memTypes.push_back(memType);
      memIndices.push_back(devIndex);
    }
  }
  if (!found)
  {
    printf("[ERROR] Unable to parse memory type token %s.  Expected one of %s followed by an index\n",
           token.c_str(), MemTypeStr);
    exit(1);
  }
}

void ParseExeType(EnvVars const& ev, std::string const& token,
                  ExeType &exeType, int& exeIndex, int& exeSubIndex)
{
  char typeChar;
  exeSubIndex = -1;
  int numTokensParsed = sscanf(token.c_str(), " %c%d.%d", &typeChar, &exeIndex, &exeSubIndex);
  if (numTokensParsed < 2)
  {
    printf("[ERROR] Unable to parse valid executor token (%s).  Exepected one of %s followed by an index\n",
           token.c_str(), ExeTypeStr);
    exit(1);
  }
  exeType = CharToExeType(typeChar);

  if (IsCpuType(exeType) && (exeIndex < 0 || exeIndex >= ev.numCpuDevices))
  {
    printf("[ERROR] CPU index must be between 0 and %d (instead of %d)\n", ev.numCpuDevices-1, exeIndex);
    exit(1);
  }
  if (IsGpuType(exeType) && (exeIndex < 0 || exeIndex >= ev.numGpuDevices))
  {
    printf("[ERROR] GPU index must be between 0 and %d (instead of %d)\n", ev.numGpuDevices-1, exeIndex);
    exit(1);
  }
  if (exeType == EXE_GPU_GFX && exeSubIndex != -1)
  {
    int const idx = RemappedIndex(exeIndex, false);
    if (ev.xccIdsPerDevice[idx].count(exeSubIndex) == 0)
    {
      printf("[ERROR] GPU %d does not have subIndex %d\n", exeIndex, exeSubIndex);
      exit(1);
    }
  }
}

// Helper function to parse a list of Transfer definitions
void ParseTransfers(EnvVars const& ev, char* line, std::vector<Transfer>& transfers)
{
  // Replace any round brackets or '->' with spaces,
  for (int i = 1; line[i]; i++)
    if (line[i] == '(' || line[i] == ')' || line[i] == '-' || line[i] == '>' ) line[i] = ' ';

  transfers.clear();

  int numTransfers = 0;
  std::istringstream iss(line);
  iss >> numTransfers;
  if (iss.fail()) return;

  std::string exeMem;
  std::string srcMem;
  std::string dstMem;

  // If numTransfers < 0, read 5-tuple (srcMem, exeMem, dstMem, #CUs, #Bytes)
  // otherwise read triples (srcMem, exeMem, dstMem)
  bool const advancedMode = (numTransfers < 0);
  numTransfers = abs(numTransfers);

  int numSubExecs;
  if (!advancedMode)
  {
    iss >> numSubExecs;
    if (numSubExecs < 0 || iss.fail())
    {
      printf("Parsing error: Number of blocks to use (%d) must be non-negative\n", numSubExecs);
      exit(1);
    }
  }

  size_t numBytes = 0;
  for (int i = 0; i < numTransfers; i++)
  {
    Transfer transfer;
    transfer.numBytes = 0;
    transfer.numBytesActual = 0;
    if (!advancedMode)
    {
      iss >> srcMem >> exeMem >> dstMem;
      if (iss.fail())
      {
        printf("Parsing error: Unable to read valid Transfer %d (SRC EXE DST) triplet\n", i+1);
        exit(1);
      }
    }
    else
    {
      std::string numBytesToken;
      iss >> srcMem >> exeMem >> dstMem >> numSubExecs >> numBytesToken;
      if (iss.fail())
      {
        printf("Parsing error: Unable to read valid Transfer %d (SRC EXE DST #CU #Bytes) tuple\n", i+1);
        exit(1);
      }
      if (sscanf(numBytesToken.c_str(), "%lu", &numBytes) != 1)
      {
        printf("Parsing error: '%s' is not a valid expression of numBytes for Transfer %d\n", numBytesToken.c_str(), i+1);
        exit(1);
      }
      char units = numBytesToken.back();
      switch (toupper(units))
      {
      case 'K': numBytes *= 1024; break;
      case 'M': numBytes *= 1024*1024; break;
      case 'G': numBytes *= 1024*1024*1024; break;
      }
    }

    ParseMemType(ev, srcMem, transfer.srcType, transfer.srcIndex);
    ParseMemType(ev, dstMem, transfer.dstType, transfer.dstIndex);
    ParseExeType(ev, exeMem, transfer.exeType, transfer.exeIndex, transfer.exeSubIndex);

    transfer.numSrcs = (int)transfer.srcType.size();
    transfer.numDsts = (int)transfer.dstType.size();
    if (transfer.numSrcs == 0 && transfer.numDsts == 0)
    {
      printf("[ERROR] Transfer must have at least one src or dst\n");
      exit(1);
    }

    if (transfer.exeType == EXE_GPU_DMA && (transfer.numSrcs != 1 || transfer.numDsts != 1))
    {
      printf("[ERROR] GPU DMA executor can only be used for single source + single dst copies\n");
      exit(1);
    }

    transfer.numSubExecs = numSubExecs;
    transfer.numBytes = numBytes;
    transfers.push_back(transfer);
  }
}

void EnablePeerAccess(int const deviceId, int const peerDeviceId)
{
  int canAccess;
  HIP_CALL(hipDeviceCanAccessPeer(&canAccess, deviceId, peerDeviceId));
  if (!canAccess)
  {
    printf("[ERROR] Unable to enable peer access from GPU devices %d to %d\n", peerDeviceId, deviceId);
    exit(1);
  }
  HIP_CALL(hipSetDevice(deviceId));
  hipError_t error = hipDeviceEnablePeerAccess(peerDeviceId, 0);
  if (error != hipSuccess && error != hipErrorPeerAccessAlreadyEnabled)
  {
    printf("[ERROR] Unable to enable peer to peer access from %d to %d (%s)\n",
           deviceId, peerDeviceId, hipGetErrorString(error));
    exit(1);
  }
}

void AllocateMemory(MemType memType, int devIndex, size_t numBytes, void** memPtr)
{
  if (numBytes == 0)
  {
    printf("[ERROR] Unable to allocate 0 bytes\n");
    exit(1);
  }
  *memPtr = nullptr;
  if (IsCpuType(memType))
  {
    // Set numa policy prior to call to hipHostMalloc
    numa_set_preferred(devIndex);

    // Allocate host-pinned memory (should respect NUMA mem policy)
    if (memType == MEM_CPU_FINE)
    {
#if defined (__NVCC__)
      printf("[ERROR] Fine-grained CPU memory not supported on NVIDIA platform\n");
      exit(1);
#else
      HIP_CALL(hipHostMalloc((void **)memPtr, numBytes, hipHostMallocNumaUser));
#endif
    }
    else if (memType == MEM_CPU)
    {
#if defined (__NVCC__)
      if (hipHostMalloc((void **)memPtr, numBytes, 0) != hipSuccess)
#else
      if (hipHostMalloc((void **)memPtr, numBytes, hipHostMallocNumaUser | hipHostMallocNonCoherent) != hipSuccess)
#endif
      {
        printf("[ERROR] Unable to allocate non-coherent host memory on NUMA node %d\n", devIndex);
        exit(1);
      }
    }
    else if (memType == MEM_CPU_UNPINNED)
    {
      *memPtr = numa_alloc_onnode(numBytes, devIndex);
    }

    // Check that the allocated pages are actually on the correct NUMA node
    memset(*memPtr, 0, numBytes);

    CheckPages((char*)*memPtr, numBytes, devIndex);

    // Reset to default numa mem policy
    numa_set_preferred(-1);
  }
  else if (IsGpuType(memType))
  {
    if (memType == MEM_GPU)
    {
      // Allocate GPU memory on appropriate device
      HIP_CALL(hipSetDevice(devIndex));
      HIP_CALL(hipMalloc((void**)memPtr, numBytes));
    }
    else if (memType == MEM_GPU_FINE)
    {
#if defined (__NVCC__)
      printf("[ERROR] Fine-grained GPU memory not supported on NVIDIA platform\n");
      exit(1);
#else
      HIP_CALL(hipSetDevice(devIndex));
      int flag = hipDeviceMallocUncached;
      HIP_CALL(hipExtMallocWithFlags((void**)memPtr, numBytes, flag));
#endif
    }
    else if (memType == MEM_MANAGED)
    {
      HIP_CALL(hipSetDevice(devIndex));
      HIP_CALL(hipMallocManaged((void**)memPtr, numBytes));
    }
    HIP_CALL(hipMemset(*memPtr, 0, numBytes));
    HIP_CALL(hipDeviceSynchronize());
  }
  else
  {
    printf("[ERROR] Unsupported memory type %d\n", memType);
    exit(1);
  }
}

void DeallocateMemory(MemType memType, void* memPtr, size_t const bytes)
{
  if (memType == MEM_CPU || memType == MEM_CPU_FINE)
  {
    if (memPtr == nullptr)
    {
      printf("[ERROR] Attempting to free null CPU pointer for %lu bytes.  Skipping hipHostFree\n", bytes);
      return;
    }
    HIP_CALL(hipHostFree(memPtr));
  }
  else if (memType == MEM_CPU_UNPINNED)
  {
    if (memPtr == nullptr)
    {
      printf("[ERROR] Attempting to free null unpinned CPU pointer for %lu bytes.  Skipping numa_free\n", bytes);
      return;
    }
    numa_free(memPtr, bytes);
  }
  else if (memType == MEM_GPU || memType == MEM_GPU_FINE)
  {
    if (memPtr == nullptr)
    {
      printf("[ERROR] Attempting to free null GPU pointer for %lu bytes. Skipping hipFree\n", bytes);
      return;
    }
    HIP_CALL(hipFree(memPtr));
  }
  else if (memType == MEM_MANAGED)
  {
    if (memPtr == nullptr)
    {
      printf("[ERROR] Attempting to free null managed pointer for %lu bytes. Skipping hipMFree\n", bytes);
      return;
    }
    HIP_CALL(hipFree(memPtr));
  }
}

void CheckPages(char* array, size_t numBytes, int targetId)
{
  unsigned long const pageSize = getpagesize();
  unsigned long const numPages = (numBytes + pageSize - 1) / pageSize;

  std::vector<void *> pages(numPages);
  std::vector<int> status(numPages);

  pages[0] = array;
  for (int i = 1; i < numPages; i++)
  {
    pages[i] = (char*)pages[i-1] + pageSize;
  }

  long const retCode = move_pages(0, numPages, pages.data(), NULL, status.data(), 0);
  if (retCode)
  {
    printf("[ERROR] Unable to collect page info\n");
    exit(1);
  }

  size_t mistakeCount = 0;
  for (int i = 0; i < numPages; i++)
  {
    if (status[i] < 0)
    {
      printf("[ERROR] Unexpected page status %d for page %d\n", status[i], i);
      exit(1);
    }
    if (status[i] != targetId) mistakeCount++;
  }
  if (mistakeCount > 0)
  {
    printf("[ERROR] %lu out of %lu pages for memory allocation were not on NUMA node %d\n", mistakeCount, numPages, targetId);
    exit(1);
  }
}

uint32_t GetId(uint32_t hwId)
{
#if defined(__NVCC_)
  return hwId;
#else
  // Based on instinct-mi200-cdna2-instruction-set-architecture.pdf
  int const shId = (hwId >> 12) &  1;
  int const cuId = (hwId >>  8) & 15;
  int const seId = (hwId >> 13) &  3;
  return (shId << 5) + (cuId << 2) + seId;
#endif
}

void RunTransfer(EnvVars const& ev, int const iteration,
                 ExecutorInfo& exeInfo, int const transferIdx)
{
  Transfer* transfer = exeInfo.transfers[transferIdx];

  if (transfer->exeType == EXE_GPU_GFX)
  {
    // Switch to executing GPU
    int const exeIndex = RemappedIndex(transfer->exeIndex, false);
    HIP_CALL(hipSetDevice(exeIndex));

    hipStream_t& stream     = exeInfo.streams[transferIdx];
    hipEvent_t&  startEvent = exeInfo.startEvents[transferIdx];
    hipEvent_t&  stopEvent  = exeInfo.stopEvents[transferIdx];

    // Figure out how many threadblocks to use.
    // In single stream mode, all the threadblocks for this GPU are launched
    // Otherwise, just launch the threadblocks associated with this single Transfer
    int const numBlocksToRun = ev.useSingleStream ? exeInfo.totalSubExecs : transfer->numSubExecs;
    int const numXCCs = (ev.useXccFilter ? ev.xccIdsPerDevice[exeIndex].size() : 1);
    dim3 const gridSize(numXCCs, numBlocksToRun, 1);
    dim3 const blockSize(ev.gfxBlockSize, 1, 1);

#if defined(__NVCC__)
    HIP_CALL(hipEventRecord(startEvent, stream));
    GpuKernelTable[ev.gfxBlockSize/64 - 1][ev.gfxUnroll - 1]
      <<<gridSize, blockSize, ev.sharedMemBytes, stream>>>(transfer->subExecParamGpuPtr, ev.gfxWaveOrder, ev.numSubIterations);
    HIP_CALL(hipEventRecord(stopEvent, stream));
#else
    hipExtLaunchKernelGGL(GpuKernelTable[ev.gfxBlockSize/64 - 1][ev.gfxUnroll - 1],
                          gridSize, blockSize,
                          ev.sharedMemBytes, stream,
                          startEvent, stopEvent,
                          0, transfer->subExecParamGpuPtr, ev.gfxWaveOrder, ev.numSubIterations);
#endif
    // Synchronize per iteration, unless in single sync mode, in which case
    // synchronize during last warmup / last actual iteration
    HIP_CALL(hipStreamSynchronize(stream));

    if (iteration >= 0)
    {
      // Record GPU timing
      float gpuDeltaMsec;
      HIP_CALL(hipEventElapsedTime(&gpuDeltaMsec, startEvent, stopEvent));

      if (ev.useSingleStream)
      {
        // Figure out individual timings for Transfers that were all launched together
        for (Transfer* currTransfer : exeInfo.transfers)
        {
          long long minStartCycle = std::numeric_limits<long long>::max();
          long long maxStopCycle  = std::numeric_limits<long long>::min();

          std::set<std::pair<int,int>> CUs;
          for (auto subExecIdx : currTransfer->subExecIdx)
          {
            minStartCycle = std::min(minStartCycle, exeInfo.subExecParamGpu[subExecIdx].startCycle);
            maxStopCycle  = std::max(maxStopCycle,  exeInfo.subExecParamGpu[subExecIdx].stopCycle);
            if (ev.showIterations)
              CUs.insert(std::make_pair(exeInfo.subExecParamGpu[subExecIdx].xccId,
                                        GetId(exeInfo.subExecParamGpu[subExecIdx].hwId)));
          }
          int const wallClockRate = ev.wallClockPerDeviceMhz[exeIndex];
          double iterationTimeMs = (maxStopCycle - minStartCycle) / (double)(wallClockRate);
          currTransfer->transferTime += iterationTimeMs;
          if (ev.showIterations)
          {
            currTransfer->perIterationTime.push_back(iterationTimeMs);
            currTransfer->perIterationCUs.push_back(CUs);
          }
        }
        exeInfo.totalTime += gpuDeltaMsec;
      }
      else
      {
        transfer->transferTime += gpuDeltaMsec;
        if (ev.showIterations)
        {
          transfer->perIterationTime.push_back(gpuDeltaMsec);
          std::set<std::pair<int,int>> CUs;
          for (int i = 0; i < transfer->numSubExecs; i++)
            CUs.insert(std::make_pair(transfer->subExecParamGpuPtr[i].xccId,
                                      GetId(transfer->subExecParamGpuPtr[i].hwId)));
          transfer->perIterationCUs.push_back(CUs);
        }
      }
    }
  }
  else if (transfer->exeType == EXE_GPU_DMA)
  {
    int const exeIndex = RemappedIndex(transfer->exeIndex, false);

    int subIterations = 0;
    if (transfer->exeSubIndex == -1 && !ev.useHsaDma) {
      // Switch to executing GPU
      HIP_CALL(hipSetDevice(exeIndex));
      hipStream_t& stream     = exeInfo.streams[transferIdx];
      hipEvent_t&  startEvent = exeInfo.startEvents[transferIdx];
      hipEvent_t&  stopEvent  = exeInfo.stopEvents[transferIdx];

      HIP_CALL(hipEventRecord(startEvent, stream));
      do {
        HIP_CALL(hipMemcpyAsync(transfer->dstMem[0], transfer->srcMem[0],
                                transfer->numBytesActual, hipMemcpyDefault,
                                stream));
      } while (++subIterations != ev.numSubIterations);
      HIP_CALL(hipEventRecord(stopEvent, stream));
      HIP_CALL(hipStreamSynchronize(stream));

      // Record time based on HIP events
      if (iteration >= 0) {
        float gpuDeltaMsec;
        HIP_CALL(hipEventElapsedTime(&gpuDeltaMsec, startEvent, stopEvent));
        transfer->transferTime += gpuDeltaMsec;
        if (ev.showIterations)
          transfer->perIterationTime.push_back(gpuDeltaMsec);
      }
    } else {
#if defined(__NVCC__)
      printf("[ERROR] CUDA does not support targeting specific DMA engines\n");
      exit(1);
#else
      // Use hsa_amd_memory copy (either targeted or untargeted)
      auto cpuStart = std::chrono::high_resolution_clock::now();

      do {
        // Atomically set signal to 1
        HSA_CALL(hsa_signal_store_screlease(transfer->signal, 1));
        if (ev.useHsaDma) {
          HSA_CALL(hsa_amd_memory_async_copy(transfer->dstMem[0], transfer->dstAgent,
                                             transfer->srcMem[0], transfer->srcAgent,
                                             transfer->numBytesActual, 0, NULL,
                                             transfer->signal));
        } else {
          HSA_CALL(hsa_amd_memory_async_copy_on_engine(transfer->dstMem[0], transfer->dstAgent,
                                                       transfer->srcMem[0], transfer->srcAgent,
                                                       transfer->numBytesActual, 0, NULL,
                                                       transfer->signal,
                                                       transfer->sdmaEngineId, true));
        }
        // Wait for SDMA transfer to complete
        while(hsa_signal_wait_scacquire(transfer->signal,
                                        HSA_SIGNAL_CONDITION_LT, 1, UINT64_MAX,
                                        HSA_WAIT_STATE_ACTIVE) >= 1);
      } while (++subIterations < ev.numSubIterations);

      if (iteration >= 0) {
        // Record GPU timing
        auto cpuDelta = std::chrono::high_resolution_clock::now() - cpuStart;
        double deltaMsec = std::chrono::duration_cast<std::chrono::duration<double>>(cpuDelta).count() * 1000.0;
        transfer->transferTime += deltaMsec;
        if (ev.showIterations)
          transfer->perIterationTime.push_back(deltaMsec);
      }
#endif
    }
  }
  else if (transfer->exeType == EXE_CPU) // CPU execution agent
  {
    // Force this thread and all child threads onto correct NUMA node
    int const exeIndex = RemappedIndex(transfer->exeIndex, true);
    if (numa_run_on_node(exeIndex))
    {
      printf("[ERROR] Unable to set CPU to NUMA node %d\n", exeIndex);
      exit(1);
    }

    std::vector<std::thread> childThreads;

    int subIteration = 0;
    auto cpuStart = std::chrono::high_resolution_clock::now();
    do {
      // Launch each subExecutor in child-threads to perform memcopies
      for (int i = 0; i < transfer->numSubExecs; ++i)
        childThreads.push_back(std::thread(CpuReduceKernel, std::ref(transfer->subExecParam[i])));

      // Wait for child-threads to finish
      for (int i = 0; i < transfer->numSubExecs; ++i)
        childThreads[i].join();
      childThreads.clear();
    } while (++subIteration != ev.numSubIterations);

    auto cpuDelta = std::chrono::high_resolution_clock::now() - cpuStart;

    // Record time if not a warmup iteration
    if (iteration >= 0)
    {
      double const delta = (std::chrono::duration_cast<std::chrono::duration<double>>(cpuDelta).count() * 1000.0);
      transfer->transferTime += delta;
      if (ev.showIterations)
        transfer->perIterationTime.push_back(delta);
    }
  }
}

void RunPeerToPeerBenchmarks(EnvVars const& ev, size_t N)
{
  ev.DisplayP2PBenchmarkEnvVars();

  char const separator = ev.outputToCsv ? ',' : ' ';
  printf("Bytes Per Direction%c%lu\n", separator, N * sizeof(float));

  // Collect the number of available CPUs/GPUs on this machine
  int const numCpus    = ev.numCpuDevices;
  int const numGpus    = ev.numGpuDevices;
  int const numDevices = numCpus + numGpus;

  // Enable peer to peer for each GPU
  for (int i = 0; i < numGpus; i++)
    for (int j = 0; j < numGpus; j++)
      if (i != j) EnablePeerAccess(i, j);

  // Perform unidirectional / bidirectional
  for (int isBidirectional = 0; isBidirectional <= 1; isBidirectional++)
  {
    if (ev.p2pMode == 1 && isBidirectional == 1 ||
        ev.p2pMode == 2 && isBidirectional == 0) continue;

    printf("%sdirectional copy peak bandwidth GB/s [%s read / %s write] (GPU-Executor: %s)\n", isBidirectional ? "Bi" : "Uni",
           ev.useRemoteRead ? "Remote" : "Local",
           ev.useRemoteRead ? "Local" : "Remote",
           ev.useDmaCopy    ? "DMA"   : "GFX");

    // Print header
    if (isBidirectional)
    {
      printf("%12s", "SRC\\DST");
    }
    else
    {
      if (ev.useRemoteRead)
        printf("%12s", "SRC\\EXE+DST");
      else
        printf("%12s", "SRC+EXE\\DST");
    }
    if (ev.outputToCsv) printf(",");
    for (int i = 0; i < numCpus; i++)
    {
      printf("%7s %02d", "CPU", i);
      if (ev.outputToCsv) printf(",");
    }
    if (numCpus > 0) printf("   ");
    for (int i = 0; i < numGpus; i++)
    {
      printf("%7s %02d", "GPU", i);
      if (ev.outputToCsv) printf(",");
    }
    printf("\n");

    double avgBwSum[2][2] = {};
    int    avgCount[2][2] = {};

    ExeType const gpuExeType = ev.useDmaCopy ? EXE_GPU_DMA : EXE_GPU_GFX;
    // Loop over all possible src/dst pairs
    for (int src = 0; src < numDevices; src++)
    {
      MemType const srcType  = (src < numCpus ? MEM_CPU : MEM_GPU);
      int     const srcIndex = (srcType == MEM_CPU ? src : src - numCpus);
      MemType const srcTypeActual = ((ev.useFineGrain && srcType == MEM_CPU) ? MEM_CPU_FINE :
                                     (ev.useFineGrain && srcType == MEM_GPU) ? MEM_GPU_FINE :
                                                                               srcType);
      std::vector<std::vector<double>> avgBandwidth(isBidirectional + 1);
      std::vector<std::vector<double>> minBandwidth(isBidirectional + 1);
      std::vector<std::vector<double>> maxBandwidth(isBidirectional + 1);
      std::vector<std::vector<double>> stdDev(isBidirectional + 1);

      if (src == numCpus && src != 0) printf("\n");
      for (int dst = 0; dst < numDevices; dst++)
      {
        MemType const dstType  = (dst < numCpus ? MEM_CPU : MEM_GPU);
        int     const dstIndex = (dstType == MEM_CPU ? dst : dst - numCpus);
        MemType const dstTypeActual = ((ev.useFineGrain && dstType == MEM_CPU) ? MEM_CPU_FINE :
                                       (ev.useFineGrain && dstType == MEM_GPU) ? MEM_GPU_FINE :
                                                                                 dstType);
        // Prepare Transfers
        std::vector<Transfer> transfers(isBidirectional + 1);

        // SRC -> DST
        transfers[0].numBytes = N * sizeof(float);
        transfers[0].srcType.push_back(srcTypeActual);
        transfers[0].dstType.push_back(dstTypeActual);
        transfers[0].srcIndex.push_back(srcIndex);
        transfers[0].dstIndex.push_back(dstIndex);
        transfers[0].numSrcs = transfers[0].numDsts = 1;
        transfers[0].exeType = IsGpuType(ev.useRemoteRead ? dstType : srcType) ? gpuExeType : EXE_CPU;
        transfers[0].exeIndex = (ev.useRemoteRead ? dstIndex : srcIndex);
        transfers[0].exeSubIndex = -1;
        transfers[0].numSubExecs = IsGpuType(transfers[0].exeType) ? ev.numGpuSubExecs : ev.numCpuSubExecs;

        // DST -> SRC
        if (isBidirectional)
        {
          transfers[1].numBytes = N * sizeof(float);
          transfers[1].numSrcs = transfers[1].numDsts = 1;
          transfers[1].srcType.push_back(dstTypeActual);
          transfers[1].dstType.push_back(srcTypeActual);
          transfers[1].srcIndex.push_back(dstIndex);
          transfers[1].dstIndex.push_back(srcIndex);
          transfers[1].exeType = IsGpuType(ev.useRemoteRead ? srcType : dstType) ? gpuExeType : EXE_CPU;
          transfers[1].exeIndex = (ev.useRemoteRead ? srcIndex : dstIndex);
          transfers[1].exeSubIndex = -1;
          transfers[1].numSubExecs = IsGpuType(transfers[1].exeType) ? ev.numGpuSubExecs : ev.numCpuSubExecs;
        }

        bool skipTest = false;

        // Abort if executing on NUMA node with no CPUs
        for (int i = 0; i <= isBidirectional; i++)
        {
          if (transfers[i].exeType == EXE_CPU && ev.numCpusPerNuma[transfers[i].exeIndex] == 0)
          {
            skipTest = true;
            break;
          }

#if defined(__NVCC__)
          // NVIDIA platform cannot access GPU memory directly from CPU executors
          if (transfers[i].exeType == EXE_CPU && (IsGpuType(srcType) || IsGpuType(dstType)))
          {
            skipTest = true;
            break;
          }
#endif
        }

        if (isBidirectional && srcType == dstType && srcIndex == dstIndex) skipTest = true;

        if (!skipTest)
        {
          ExecuteTransfers(ev, 0, N, transfers, false);

          for (int dir = 0; dir <= isBidirectional; dir++)
          {
            double const avgTime = transfers[dir].transferTime;
            double const avgBw   = (transfers[dir].numBytesActual / 1.0E9) / avgTime * 1000.0f;
            avgBandwidth[dir].push_back(avgBw);

            if (!(srcType == dstType && srcIndex == dstIndex))
            {
              avgBwSum[srcType][dstType] += avgBw;
              avgCount[srcType][dstType]++;
            }

            if (ev.showIterations)
            {
              double minTime = transfers[dir].perIterationTime[0];
              double maxTime = transfers[dir].perIterationTime[0];
              double varSum  = 0;
              for (int i = 0; i < transfers[dir].perIterationTime.size(); i++)
              {
                minTime = std::min(minTime, transfers[dir].perIterationTime[i]);
                maxTime = std::max(maxTime, transfers[dir].perIterationTime[i]);
                double const bw  = (transfers[dir].numBytesActual / 1.0E9) / transfers[dir].perIterationTime[i] * 1000.0f;
                double const delta = (avgBw - bw);
                varSum += delta * delta;
              }
              double const minBw = (transfers[dir].numBytesActual / 1.0E9) / maxTime * 1000.0f;
              double const maxBw = (transfers[dir].numBytesActual / 1.0E9) / minTime * 1000.0f;
              double const stdev = sqrt(varSum / transfers[dir].perIterationTime.size());
              minBandwidth[dir].push_back(minBw);
              maxBandwidth[dir].push_back(maxBw);
              stdDev[dir].push_back(stdev);
            }
          }
        }
        else
        {
          for (int dir = 0; dir <= isBidirectional; dir++)
          {
            avgBandwidth[dir].push_back(0);
            minBandwidth[dir].push_back(0);
            maxBandwidth[dir].push_back(0);
            stdDev[dir].push_back(-1.0);
          }
        }
      }

      for (int dir = 0; dir <= isBidirectional; dir++)
      {
        printf("%5s %02d %3s", (srcType == MEM_CPU) ? "CPU" : "GPU", srcIndex, dir ? "<- " : " ->");
        if (ev.outputToCsv) printf(",");

        for (int dst = 0; dst < numDevices; dst++)
        {
          if (dst == numCpus && dst != 0) printf("   ");
          double const avgBw = avgBandwidth[dir][dst];

          if (avgBw == 0.0)
            printf("%10s", "N/A");
          else
            printf("%10.2f", avgBw);
          if (ev.outputToCsv) printf(",");
        }
        printf("\n");

        if (ev.showIterations)
        {
          // minBw
          printf("%5s %02d %3s", (srcType == MEM_CPU) ? "CPU" : "GPU", srcIndex, "min");
          if (ev.outputToCsv) printf(",");
          for (int i = 0; i < numDevices; i++)
          {
            double const minBw = minBandwidth[dir][i];
            if (i == numCpus && i != 0) printf("   ");
            if (minBw == 0.0)
              printf("%10s", "N/A");
            else
              printf("%10.2f", minBw);
            if (ev.outputToCsv) printf(",");
          }
          printf("\n");

          // maxBw
          printf("%5s %02d %3s", (srcType == MEM_CPU) ? "CPU" : "GPU", srcIndex, "max");
          if (ev.outputToCsv) printf(",");
          for (int i = 0; i < numDevices; i++)
          {
            double const maxBw = maxBandwidth[dir][i];
            if (i == numCpus && i != 0) printf("   ");
            if (maxBw == 0.0)
              printf("%10s", "N/A");
            else
              printf("%10.2f", maxBw);
            if (ev.outputToCsv) printf(",");
          }
          printf("\n");

          // stddev
          printf("%5s %02d %3s", (srcType == MEM_CPU) ? "CPU" : "GPU", srcIndex, " sd");
          if (ev.outputToCsv) printf(",");
          for (int i = 0; i < numDevices; i++)
          {
            double const sd = stdDev[dir][i];
            if (i == numCpus && i != 0) printf("   ");
            if (sd == -1.0)
              printf("%10s", "N/A");
            else
              printf("%10.2f", sd);
            if (ev.outputToCsv) printf(",");
          }
          printf("\n");
        }
        fflush(stdout);
      }

      if (isBidirectional)
      {
        printf("%5s %02d %3s", (srcType == MEM_CPU) ? "CPU" : "GPU", srcIndex, "<->");
        if (ev.outputToCsv) printf(",");
        for (int dst = 0; dst < numDevices; dst++)
        {
          double const sumBw = avgBandwidth[0][dst] + avgBandwidth[1][dst];
          if (dst == numCpus && dst != 0) printf("   ");
          if (sumBw == 0.0)
            printf("%10s", "N/A");
          else
            printf("%10.2f", sumBw);
          if (ev.outputToCsv) printf(",");
        }
        printf("\n");
        if (src < numDevices - 1) printf("\n");
      }
    }

    if (!ev.outputToCsv)
    {
      printf("                         ");
      for (int srcType : {MEM_CPU, MEM_GPU})
        for (int dstType : {MEM_CPU, MEM_GPU})
          printf("  %cPU->%cPU", srcType == MEM_CPU ? 'C' : 'G', dstType == MEM_CPU ? 'C' : 'G');
      printf("\n");

      printf("Averages (During %s):",  isBidirectional ? " BiDir" : "UniDir");
      for (int srcType : {MEM_CPU, MEM_GPU})
        for (int dstType : {MEM_CPU, MEM_GPU})
        {
          if (avgCount[srcType][dstType])
            printf("%10.2f", avgBwSum[srcType][dstType] / avgCount[srcType][dstType]);
          else
            printf("%10s", "N/A");
        }
      printf("\n\n");
    }
  }
}

void RunScalingBenchmark(EnvVars const& ev, size_t N, int const exeIndex, int const maxSubExecs)
{
  ev.DisplayEnvVars();

  // Collect the number of available CPUs/GPUs on this machine
  int const numCpus    = ev.numCpuDevices;
  int const numGpus    = ev.numGpuDevices;
  int const numDevices = numCpus + numGpus;

  // Enable peer to peer for each GPU
  for (int i = 0; i < numGpus; i++)
    for (int j = 0; j < numGpus; j++)
      if (i != j) EnablePeerAccess(i, j);

  char separator = (ev.outputToCsv ? ',' : ' ');

  std::vector<Transfer> transfers(1);
  Transfer& t = transfers[0];
  t.numBytes = N * sizeof(float);
  t.numSrcs  = 1;
  t.numDsts  = 1;
  t.exeType  = EXE_GPU_GFX;
  t.exeIndex = exeIndex;
  t.exeSubIndex = -1;
  t.srcType.resize(1, MEM_GPU);
  t.dstType.resize(1, MEM_GPU);
  t.srcIndex.resize(1);
  t.dstIndex.resize(1);

  printf("GPU-GFX Scaling benchmark:\n");
  printf("==========================\n");
  printf("- Copying %lu bytes from GPU %d to other devices\n", t.numBytes, exeIndex);
  printf("- All numbers reported as GB/sec\n\n");

  printf("NumCUs");
  for (int i = 0; i < numDevices; i++)
    printf("%c  %s%02d     ", separator, i < numCpus ? "CPU" : "GPU", i < numCpus ? i : i - numCpus);
  printf("\n");

  std::vector<std::pair<double, int>> bestResult(numDevices);
  for (int numSubExec = 1; numSubExec <= maxSubExecs; numSubExec++)
  {
    t.numSubExecs = numSubExec;
    printf("%4d  ", numSubExec);

    for (int i = 0; i < numDevices; i++)
    {
      t.dstType[0]  = i < numCpus ? MEM_CPU : MEM_GPU;
      t.dstIndex[0] = i < numCpus ? i : i - numCpus;

      ExecuteTransfers(ev, 0, N, transfers, false);
      printf("%c%7.2f     ", separator, t.transferBandwidth);

      if (t.transferBandwidth > bestResult[i].first)
      {
        bestResult[i].first  = t.transferBandwidth;
        bestResult[i].second = numSubExec;
      }
    }
    printf("\n");
  }

  printf(" Best ");
  for (int i = 0; i < numDevices; i++)
  {
    printf("%c%7.2f(%3d)", separator, bestResult[i].first, bestResult[i].second);
  }
  printf("\n");
}

void RunAllToAllBenchmark(EnvVars const& ev, size_t const numBytesPerTransfer, int const numSubExecs)
{
  ev.DisplayA2AEnvVars();

  // Collect the number of GPU devices to use
  int const numGpus = ev.numGpuDevices;

  // Enable peer to peer for each GPU
  for (int i = 0; i < numGpus; i++)
    for (int j = 0; j < numGpus; j++)
      if (i != j) EnablePeerAccess(i, j);

  char separator = (ev.outputToCsv ? ',' : ' ');

  Transfer transfer;
  transfer.numBytes    = numBytesPerTransfer;
  transfer.numSubExecs = numSubExecs;
  transfer.numSrcs     = ev.a2aMode == 2 ? 0 : 1;
  transfer.numDsts     = ev.a2aMode == 1 ? 0 : 1;
  transfer.exeType     = (ev.useDmaCopy && transfer.numSrcs == 1 && transfer.numDsts == 1) ? EXE_GPU_DMA : EXE_GPU_GFX;
  transfer.exeSubIndex = -1;
  transfer.srcType.resize(1, ev.useFineGrain ? MEM_GPU_FINE : MEM_GPU);
  transfer.dstType.resize(1, ev.useFineGrain ? MEM_GPU_FINE : MEM_GPU);
  transfer.srcIndex.resize(1);
  transfer.dstIndex.resize(1);

  std::vector<Transfer> transfers;
  for (int i = 0; i < numGpus; i++)
  {
    transfer.srcIndex[0] = i;
    for (int j = 0; j < numGpus; j++)
    {
      transfer.dstIndex[0] = j;
      transfer.exeIndex    = (ev.useRemoteRead ? j : i);

      if (ev.a2aDirect)
      {
        if (i == j) continue;

#if !defined(__NVCC__)
        uint32_t linkType, hopCount;
        HIP_CALL(hipExtGetLinkTypeAndHopCount(RemappedIndex(i, false),
                                              RemappedIndex(j, false),
                                              &linkType, &hopCount));
        if (hopCount != 1) continue;
#endif
      }
      transfers.push_back(transfer);
    }
  }

  printf("GPU-GFX All-To-All benchmark:\n");
  printf("==========================\n");
  printf("- Copying %lu bytes between %s pairs of GPUs using %d CUs (%lu Transfers)\n",
         numBytesPerTransfer, ev.a2aDirect ? "directly connected" : "all", numSubExecs, transfers.size());
  if (transfers.size() == 0) return;

  double totalBandwidthCpu = 0;
  ExecuteTransfers(ev, 0, numBytesPerTransfer / sizeof(float), transfers, !ev.hideEnv, &totalBandwidthCpu);

  printf("\nSummary:\n");
  printf("==========================================================\n");
  printf("SRC\\DST ");
  for (int dst = 0; dst < numGpus; dst++)
    printf("%cGPU %02d    ", separator, dst);
  printf("   %cSTotal     %cActual\n", separator, separator);

  std::map<std::pair<int, int>, int> reIndex;
  for (int i = 0; i < transfers.size(); i++)
  {
    Transfer const& t = transfers[i];
    reIndex[std::make_pair(t.srcIndex[0], t.dstIndex[0])] = i;
  }

  double totalBandwidthGpu = 0.0;
  double minExecutorBandwidth = std::numeric_limits<double>::max();
  double maxExecutorBandwidth = 0.0;
  std::vector<double> colTotalBandwidth(numGpus+1, 0.0);
  for (int src = 0; src < numGpus; src++)
  {
    double rowTotalBandwidth = 0;
    double executorBandwidth = 0;
    printf("GPU %02d", src);
    for (int dst = 0; dst < numGpus; dst++)
    {
      if (reIndex.count(std::make_pair(src, dst)))
      {
        Transfer const& transfer = transfers[reIndex[std::make_pair(src,dst)]];
        colTotalBandwidth[dst]  += transfer.transferBandwidth;
        rowTotalBandwidth       += transfer.transferBandwidth;
        totalBandwidthGpu       += transfer.transferBandwidth;
        executorBandwidth        = std::max(executorBandwidth, transfer.executorBandwidth);
        printf("%c%8.3f  ", separator, transfer.transferBandwidth);
      }
      else
      {
        printf("%c%8s  ", separator, "N/A");
      }
    }
    printf("   %c%8.3f   %c%8.3f\n", separator, rowTotalBandwidth, separator, executorBandwidth);
    minExecutorBandwidth = std::min(minExecutorBandwidth, executorBandwidth);
    maxExecutorBandwidth = std::max(maxExecutorBandwidth, executorBandwidth);
    colTotalBandwidth[numGpus] += rowTotalBandwidth;
  }
  printf("\nRTotal");
  for (int dst = 0; dst < numGpus; dst++)
  {
    printf("%c%8.3f  ", separator, colTotalBandwidth[dst]);
  }
  printf("   %c%8.3f   %c%8.3f   %c%8.3f\n", separator, colTotalBandwidth[numGpus],
         separator, minExecutorBandwidth, separator, maxExecutorBandwidth);
  printf("\n");

  printf("Average   bandwidth (GPU Timed): %8.3f GB/s\n", totalBandwidthGpu / transfers.size());
  printf("Aggregate bandwidth (GPU Timed): %8.3f GB/s\n", totalBandwidthGpu);
  printf("Aggregate bandwidth (CPU Timed): %8.3f GB/s\n", totalBandwidthCpu);
}

void Transfer::PrepareSubExecParams(EnvVars const& ev)
{
  // Each subExecutor needs to know src/dst pointers and how many elements to transfer
  // Figure out the sub-array each subExecutor works on for this Transfer
  // - Partition N as evenly as possible, but try to keep subarray sizes as multiples of BLOCK_BYTES bytes,
  //   except the very last one, for alignment reasons
  size_t const N              = this->numBytesActual / sizeof(float);
  int    const initOffset     = ev.byteOffset / sizeof(float);
  int    const targetMultiple = ev.blockBytes / sizeof(float);

  // In some cases, there may not be enough data for all subExectors
  int const maxSubExecToUse = std::min((size_t)(N + targetMultiple - 1) / targetMultiple, (size_t)this->numSubExecs);
  this->subExecParam.clear();
  this->subExecParam.resize(this->numSubExecs);

  size_t assigned = 0;
  for (int i = 0; i < this->numSubExecs; ++i)
  {
    SubExecParam& p  = this->subExecParam[i];
    p.numSrcs        = this->numSrcs;
    p.numDsts        = this->numDsts;

    if (ev.gfxSingleTeam && this->exeType == EXE_GPU_GFX)
    {
      p.N           = N;
      p.teamSize    = this->numSubExecs;
      p.teamIdx     = i;
      for (int iSrc = 0; iSrc < this->numSrcs; ++iSrc) p.src[iSrc] = this->srcMem[iSrc] + initOffset;
      for (int iDst = 0; iDst < this->numDsts; ++iDst) p.dst[iDst] = this->dstMem[iDst] + initOffset;
    }
    else
    {
      int    const subExecLeft = std::max(0, maxSubExecToUse - i);
      size_t const leftover    = N - assigned;
      size_t const roundedN    = (leftover + targetMultiple - 1) / targetMultiple;

      p.N           = subExecLeft ? std::min(leftover, ((roundedN / subExecLeft) * targetMultiple)) : 0;
      p.teamSize    = 1;
      p.teamIdx     = 0;
      for (int iSrc = 0; iSrc < this->numSrcs; ++iSrc) p.src[iSrc] = this->srcMem[iSrc] + initOffset + assigned;
      for (int iDst = 0; iDst < this->numDsts; ++iDst) p.dst[iDst] = this->dstMem[iDst] + initOffset + assigned;

      assigned += p.N;
    }

    p.preferredXccId = -1;
    if (ev.useXccFilter && this->exeType == EXE_GPU_GFX)
    {
      std::uniform_int_distribution<int> distribution(0, ev.xccIdsPerDevice[this->exeIndex].size() - 1);

      // Use this tranfer's executor subIndex if set
      if (this->exeSubIndex != -1)
      {
        p.preferredXccId = this->exeSubIndex;
      }
      else if (this->numDsts >= 1 && IsGpuType(this->dstType[0]))
      {
        p.preferredXccId = ev.prefXccTable[this->exeIndex][this->dstIndex[0]];
      }

      if (p.preferredXccId == -1)
      {
        p.preferredXccId = distribution(*ev.generator);
      }
    }

    if (ev.enableDebug)
    {
      printf("Transfer %02d SE:%02d: %10lu floats: %10lu to %10lu\n",
             this->transferIndex, i, p.N, assigned, assigned + p.N);
    }

    p.startCycle = 0;
    p.stopCycle  = 0;
  }

  this->transferTime = 0.0;
  this->perIterationTime.clear();
}

void Transfer::PrepareReference(EnvVars const& ev, std::vector<float>& buffer, int bufferIdx)
{
  size_t N = buffer.size();
  if (bufferIdx >= 0)
  {
    size_t patternLen = ev.fillPattern.size();
    if (patternLen > 0)
    {
      for (size_t i = 0; i < N; ++i)
        buffer[i] = ev.fillPattern[i % patternLen];
    }
    else
    {
      for (size_t i = 0; i < N; ++i)
        buffer[i] = PrepSrcValue(bufferIdx, i);
    }
  }
  else // Destination buffer
  {
    if (this->numSrcs == 0)
    {
      // Note: 0x75757575 = 13323083.0
      memset(buffer.data(), MEMSET_CHAR, N * sizeof(float));
    }
    else
    {
      PrepareReference(ev, buffer, 0);

      if (this->numSrcs > 1)
      {
        std::vector<float> temp(N);
        for (int srcIdx = 1; srcIdx < this->numSrcs; ++srcIdx)
        {
          PrepareReference(ev, temp, srcIdx);
          for (int i = 0; i < N; ++i)
          {
            buffer[i] += temp[i];
          }
        }
      }
    }
  }
}

bool Transfer::PrepareSrc(EnvVars const& ev)
{
  if (this->numSrcs == 0) return true;
  size_t const N = this->numBytesActual / sizeof(float);
  int const initOffset = ev.byteOffset / sizeof(float);

  std::vector<float> reference(N);
  for (int srcIdx = 0; srcIdx < this->numSrcs; ++srcIdx)
  {
    float* srcPtr = this->srcMem[srcIdx] + initOffset;
    PrepareReference(ev, reference, srcIdx);

    // Initialize source memory array with reference pattern
    if (IsGpuType(this->srcType[srcIdx]))
    {
      int const deviceIdx = RemappedIndex(this->srcIndex[srcIdx], false);
      HIP_CALL(hipSetDevice(deviceIdx));
      if (ev.usePrepSrcKernel)
        PrepSrcDataKernel<<<32, ev.gfxBlockSize>>>(srcPtr, N, srcIdx);
      else
        HIP_CALL(hipMemcpy(srcPtr, reference.data(), this->numBytesActual, hipMemcpyDefault));
      HIP_CALL(hipDeviceSynchronize());
    }
    else if (IsCpuType(this->srcType[srcIdx]))
    {
      memcpy(srcPtr, reference.data(), this->numBytesActual);
    }

    // Perform check just to make sure that data has been copied properly
    float* srcCheckPtr = srcPtr;
    std::vector<float> srcCopy(N);
    if (IsGpuType(this->srcType[srcIdx]))
    {
      if (!ev.validateDirect)
      {
        HIP_CALL(hipMemcpy(srcCopy.data(), srcPtr, this->numBytesActual, hipMemcpyDefault));
        HIP_CALL(hipDeviceSynchronize());
        srcCheckPtr = srcCopy.data();
      }
    }

    for (size_t i = 0; i < N; ++i)
    {
      if (reference[i] != srcCheckPtr[i])
      {
        printf("\n[ERROR] Unexpected mismatch at index %lu of source array %d:\n", i, srcIdx);
#if !defined(__NVCC__)
        float const val = this->srcMem[srcIdx][initOffset + i];
        printf("[ERROR] SRC %02d   value: %10.5f [%08X] Direct: %10.5f [%08X]\n",
               srcIdx, srcCheckPtr[i], *(unsigned int*)&srcCheckPtr[i], val, *(unsigned int*)&val);
#else
        printf("[ERROR] SRC %02d   value: %10.5f [%08X]\n", srcIdx, srcCheckPtr[i], *(unsigned int*)&srcCheckPtr[i]);
#endif
        printf("[ERROR] EXPECTED value: %10.5f [%08X]\n", reference[i], *(unsigned int*)&reference[i]);
        printf("[ERROR] Failed Transfer details: #%d: %s -> [%c%d:%d] -> %s\n",
               this->transferIndex,
               this->SrcToStr().c_str(),
               ExeTypeStr[this->exeType], this->exeIndex,
               this->numSubExecs,
               this->DstToStr().c_str());
        printf("[ERROR] Possible cause is misconfigured IOMMU (AMD Instinct cards require amd_iommu=on and iommu=pt)\n");
        printf("[ERROR] Please see https://community.amd.com/t5/knowledge-base/iommu-advisory-for-amd-instinct/ta-p/484601 for more details\n");
        if (!ev.continueOnError)
          exit(1);
        return false;
      }
    }
  }
  return true;
}

void Transfer::ValidateDst(EnvVars const& ev)
{
  if (this->numDsts == 0) return;
  size_t const N = this->numBytesActual / sizeof(float);
  int const initOffset = ev.byteOffset / sizeof(float);

  std::vector<float> reference(N);
  PrepareReference(ev, reference, -1);

  std::vector<float> hostBuffer(N);
  for (int dstIdx = 0; dstIdx < this->numDsts; ++dstIdx)
  {
    float* output;
    if (IsCpuType(this->dstType[dstIdx]) || ev.validateDirect)
    {
      output = this->dstMem[dstIdx] + initOffset;
    }
    else
    {
      int const deviceIdx = RemappedIndex(this->dstIndex[dstIdx], false);
      HIP_CALL(hipSetDevice(deviceIdx));
      HIP_CALL(hipMemcpy(hostBuffer.data(), this->dstMem[dstIdx] + initOffset, this->numBytesActual, hipMemcpyDefault));
      HIP_CALL(hipDeviceSynchronize());
      output = hostBuffer.data();
    }

    for (size_t i = 0; i < N; ++i)
    {
      if (reference[i] != output[i])
      {
        printf("\n[ERROR] Unexpected mismatch at index %lu of destination array %d:\n", i, dstIdx);
        for (int srcIdx = 0; srcIdx < this->numSrcs; ++srcIdx)
        {
          float srcVal;
          HIP_CALL(hipMemcpy(&srcVal, this->srcMem[srcIdx] + initOffset + i, sizeof(float), hipMemcpyDefault));
#if !defined(__NVCC__)
          float val = this->srcMem[srcIdx][initOffset + i];
          printf("[ERROR] SRC %02dD  value: %10.5f [%08X] Direct: %10.5f [%08X]\n",
                 srcIdx, srcVal, *(unsigned int*)&srcVal, val, *(unsigned int*)&val);
#else
          printf("[ERROR] SRC %02d   value: %10.5f [%08X]\n", srcIdx, srcVal, *(unsigned int*)&srcVal);
#endif
        }
        printf("[ERROR] EXPECTED value: %10.5f [%08X]\n", reference[i], *(unsigned int*)&reference[i]);
#if !defined(__NVCC__)
        float dstVal = this->dstMem[dstIdx][initOffset + i];
        printf("[ERROR] DST %02d   value: %10.5f [%08X] Direct: %10.5f [%08X]\n",
               dstIdx, output[i], *(unsigned int*)&output[i], dstVal, *(unsigned int*)&dstVal);
#else
        printf("[ERROR] DST %02d   value: %10.5f [%08X]\n", dstIdx, output[i], *(unsigned int*)&output[i]);
#endif
        printf("[ERROR] Failed Transfer details: #%d: %s -> [%c%d:%d] -> %s\n",
               this->transferIndex,
               this->SrcToStr().c_str(),
               ExeTypeStr[this->exeType], this->exeIndex,
               this->numSubExecs,
               this->DstToStr().c_str());
        if (!ev.continueOnError)
          exit(1);
        else
          break;
      }
    }
  }
}

std::string Transfer::SrcToStr() const
{
  if (numSrcs == 0) return "N";
  std::stringstream ss;
  for (int i = 0; i < numSrcs; ++i)
    ss << MemTypeStr[srcType[i]] << srcIndex[i];
  return ss.str();
}

std::string Transfer::DstToStr() const
{
  if (numDsts == 0) return "N";
  std::stringstream ss;
  for (int i = 0; i < numDsts; ++i)
    ss << MemTypeStr[dstType[i]] << dstIndex[i];
  return ss.str();
}

void RunSchmooBenchmark(EnvVars const& ev, size_t const numBytesPerTransfer, int const localIdx, int const remoteIdx, int const maxSubExecs)
{
  char memType = ev.useFineGrain ? 'F' : 'G';
  printf("Bytes to transfer: %lu Local GPU: %d Remote GPU: %d\n", numBytesPerTransfer, localIdx, remoteIdx);
  printf("       | Local Read  | Local Write | Local Copy  | Remote Read | Remote Write| Remote Copy |\n");
  printf("  #CUs |%c%02d->G%02d->N00|N00->G%02d->%c%02d|%c%02d->G%02d->%c%02d|%c%02d->G%02d->N00|N00->G%02d->%c%02d|%c%02d->G%02d->%c%02d|\n",
         memType, localIdx, localIdx,
         localIdx, memType, localIdx,
         memType, localIdx, localIdx, memType, localIdx,
         memType, remoteIdx, localIdx,
         localIdx, memType, remoteIdx,
         memType, localIdx, localIdx, memType, remoteIdx);
  printf("|------|-------------|-------------|-------------|-------------|-------------|-------------|\n");

  std::vector<Transfer> transfers(1);
  Transfer& t   = transfers[0];
  t.exeType     = EXE_GPU_GFX;
  t.exeIndex    = localIdx;
  t.exeSubIndex = -1;
  t.numBytes    = numBytesPerTransfer;

  for (int numCUs = 1; numCUs <= maxSubExecs; numCUs++)
  {
    t.numSubExecs = numCUs;

    // Local Read
    t.numSrcs = 1;
    t.numDsts = 0;
    t.srcType.resize(t.numSrcs);
    t.dstType.resize(t.numDsts);
    t.srcIndex.resize(t.numSrcs);
    t.dstIndex.resize(t.numDsts);
    t.srcType[0]  = (ev.useFineGrain ? MEM_GPU_FINE : MEM_GPU);
    t.srcIndex[0] = localIdx;
    ExecuteTransfers(ev, 0, 0, transfers, false);
    double const localRead = (t.numBytesActual / 1.0E9) / t.transferTime * 1000.0f;

    // Local Write
    t.numSrcs = 0;
    t.numDsts = 1;
    t.srcType.resize(t.numSrcs);
    t.dstType.resize(t.numDsts);
    t.srcIndex.resize(t.numSrcs);
    t.dstIndex.resize(t.numDsts);
    t.dstType[0]  = (ev.useFineGrain ? MEM_GPU_FINE : MEM_GPU);
    t.dstIndex[0] = localIdx;
    ExecuteTransfers(ev, 0, 0, transfers, false);
    double const localWrite = (t.numBytesActual / 1.0E9) / t.transferTime * 1000.0f;

    // Local Copy
    t.numSrcs = 1;
    t.numDsts = 1;
    t.srcType.resize(t.numSrcs);
    t.dstType.resize(t.numDsts);
    t.srcIndex.resize(t.numSrcs);
    t.dstIndex.resize(t.numDsts);
    t.srcType[0]  = (ev.useFineGrain ? MEM_GPU_FINE : MEM_GPU);
    t.srcIndex[0] = localIdx;
    t.dstType[0]  = (ev.useFineGrain ? MEM_GPU_FINE : MEM_GPU);
    t.dstIndex[0] = localIdx;
    ExecuteTransfers(ev, 0, 0, transfers, false);
    double const localCopy = (t.numBytesActual / 1.0E9) / t.transferTime * 1000.0f;

    // Remote Read
    t.numSrcs = 1;
    t.numDsts = 0;
    t.srcType.resize(t.numSrcs);
    t.dstType.resize(t.numDsts);
    t.srcIndex.resize(t.numSrcs);
    t.dstIndex.resize(t.numDsts);
    t.srcType[0]  = (ev.useFineGrain ? MEM_GPU_FINE : MEM_GPU);
    t.srcIndex[0] = remoteIdx;
    ExecuteTransfers(ev, 0, 0, transfers, false);
    double const remoteRead = (t.numBytesActual / 1.0E9) / t.transferTime * 1000.0f;

    // Remote Write
    t.numSrcs = 0;
    t.numDsts = 1;
    t.srcType.resize(t.numSrcs);
    t.dstType.resize(t.numDsts);
    t.srcIndex.resize(t.numSrcs);
    t.dstIndex.resize(t.numDsts);
    t.dstType[0]  = (ev.useFineGrain ? MEM_GPU_FINE : MEM_GPU);
    t.dstIndex[0] = remoteIdx;
    ExecuteTransfers(ev, 0, 0, transfers, false);
    double const remoteWrite = (t.numBytesActual / 1.0E9) / t.transferTime * 1000.0f;

    // Remote Copy
    t.numSrcs = 1;
    t.numDsts = 1;
    t.srcType.resize(t.numSrcs);
    t.dstType.resize(t.numDsts);
    t.srcIndex.resize(t.numSrcs);
    t.dstIndex.resize(t.numDsts);
    t.srcType[0]  = (ev.useFineGrain ? MEM_GPU_FINE : MEM_GPU);
    t.srcIndex[0] = localIdx;
    t.dstType[0]  = (ev.useFineGrain ? MEM_GPU_FINE : MEM_GPU);
    t.dstIndex[0] = remoteIdx;
    ExecuteTransfers(ev, 0, 0, transfers, false);
    double const remoteCopy = (t.numBytesActual / 1.0E9) / t.transferTime * 1000.0f;

    printf("   %3d   %11.3f   %11.3f   %11.3f   %11.3f   %11.3f   %11.3f  \n",
           numCUs, localRead, localWrite, localCopy, remoteRead, remoteWrite, remoteCopy);
  }
}

void RunRemoteWriteBenchmark(EnvVars const& ev, size_t const numBytesPerTransfer, int numSubExecs, int const srcIdx, int minGpus, int maxGpus)
{
  printf("Bytes to %s: %lu from GPU %d using %d CUs [Sweeping %d to %d parallel writes]\n",
         ev.useRemoteRead ? "read" : "write", numBytesPerTransfer, srcIdx, numSubExecs, minGpus, maxGpus);

  char sep = (ev.outputToCsv ? ',' : ' ');

  for (int i = 0; i < ev.numGpuDevices; i++)
  {
    if (i == srcIdx) continue;
    printf("   GPU %-3d  %c", i, sep);
  }
  printf("\n");
  if (!ev.outputToCsv)
  {
    for (int i = 0; i < ev.numGpuDevices-1; i++)
    {
      printf("-------------");
    }
    printf("\n");
  }

  for (int p = minGpus; p <= maxGpus; p++)
  {
    for (int bitmask = 0; bitmask < (1<<ev.numGpuDevices); bitmask++)
    {
      if (bitmask & (1<<srcIdx)) continue;
      if (__builtin_popcount(bitmask) == p)
      {
        std::vector<Transfer> transfers;
        for (int i = 0; i < ev.numGpuDevices; i++)
        {
          if (bitmask & (1<<i))
          {
            Transfer t;
            t.exeType     = EXE_GPU_GFX;
            t.exeSubIndex = -1;
            t.numSubExecs = numSubExecs;
            t.numBytes    = numBytesPerTransfer;

            if (ev.useRemoteRead)
            {
              t.numSrcs  = 1;
              t.numDsts  = 0;
              t.exeIndex = i;
              t.srcType.resize(1);
              t.srcType[0]  = (ev.useFineGrain ? MEM_GPU_FINE : MEM_GPU);
              t.srcIndex.resize(1);
              t.srcIndex[0] = srcIdx;
            }
            else
            {
              t.numSrcs     = 0;
              t.numDsts     = 1;
              t.exeIndex    = srcIdx;
              t.dstType.resize(1);
              t.dstType[0]  = (ev.useFineGrain ? MEM_GPU_FINE : MEM_GPU);
              t.dstIndex.resize(1);
              t.dstIndex[0] = i;
            }
            transfers.push_back(t);
          }
        }
        ExecuteTransfers(ev, 0, 0, transfers, false);

        int counter = 0;
        for (int i = 0; i < ev.numGpuDevices; i++)
        {
          if (bitmask & (1<<i))
            printf("  %8.3f  %c", transfers[counter++].transferBandwidth, sep);
          else if (i != srcIdx)
            printf("            %c", sep);
        }

        printf(" %d %d", p, numSubExecs);
        for (auto i = 0; i < transfers.size(); i++)
        {
          printf(" (%s %c%d %s)",
                 transfers[i].SrcToStr().c_str(),
                 ExeTypeStr[transfers[i].exeType], transfers[i].exeIndex,
                 transfers[i].DstToStr().c_str());
        }
        printf("\n");
      }
    }
  }
}

void RunParallelCopyBenchmark(EnvVars const& ev, size_t const numBytesPerTransfer, int numSubExecs, int const srcIdx, int minGpus, int maxGpus)
{
  if (ev.useDmaCopy)
    printf("Bytes to copy: %lu from GPU %d using DMA [Sweeping %d to %d parallel writes]\n",
           numBytesPerTransfer, srcIdx, minGpus, maxGpus);
  else
    printf("Bytes to copy: %lu from GPU %d using GFX (%d CUs) [Sweeping %d to %d parallel writes]\n",
           numBytesPerTransfer, srcIdx, numSubExecs, minGpus, maxGpus);

  char sep = (ev.outputToCsv ? ',' : ' ');

  for (int i = 0; i < ev.numGpuDevices; i++)
  {
    if (i == srcIdx) continue;
    printf("   GPU %-3d  %c", i, sep);
  }
  printf("\n");
  if (!ev.outputToCsv)
  {
    for (int i = 0; i < ev.numGpuDevices-1; i++)
    {
      printf("-------------");
    }
    printf("\n");
  }

  for (int p = minGpus; p <= maxGpus; p++)
  {
    for (int bitmask = 0; bitmask < (1<<ev.numGpuDevices); bitmask++)
    {
      if (bitmask & (1<<srcIdx)) continue;
      if (__builtin_popcount(bitmask) == p)
      {
        std::vector<Transfer> transfers;
        for (int i = 0; i < ev.numGpuDevices; i++)
        {
          if (bitmask & (1<<i))
          {
            Transfer t;
            t.exeType     = ev.useDmaCopy ? EXE_GPU_DMA : EXE_GPU_GFX;
            t.exeSubIndex = -1;
            t.numSubExecs = ev.useDmaCopy ? 1 : numSubExecs;
            t.numBytes    = numBytesPerTransfer;

            t.numSrcs     = 1;
            t.numDsts     = 1;
            t.exeIndex    = srcIdx;
            t.srcType.resize(1);
            t.srcType[0]  = (ev.useFineGrain ? MEM_GPU_FINE : MEM_GPU);
            t.srcIndex.resize(1);
            t.srcIndex[0] = srcIdx;
            t.dstType.resize(1);
            t.dstType[0]  = (ev.useFineGrain ? MEM_GPU_FINE : MEM_GPU);
            t.dstIndex.resize(1);
            t.dstIndex[0] = i;

            transfers.push_back(t);
          }
        }
        ExecuteTransfers(ev, 0, 0, transfers, false);

        int counter = 0;
        for (int i = 0; i < ev.numGpuDevices; i++)
        {
          if (bitmask & (1<<i))
            printf("  %8.3f  %c", transfers[counter++].transferBandwidth, sep);
          else if (i != srcIdx)
            printf("            %c", sep);
        }

        printf(" %d %d", p, numSubExecs);
        for (auto i = 0; i < transfers.size(); i++)
        {
          printf(" (%s %c%d %s)",
                 transfers[i].SrcToStr().c_str(),
                 ExeTypeStr[transfers[i].exeType], transfers[i].exeIndex,
                 transfers[i].DstToStr().c_str());
        }
        printf("\n");
      }
    }
  }
}

void RunSweepPreset(EnvVars const& ev, size_t const numBytesPerTransfer, int const numGpuSubExecs, int const numCpuSubExecs, bool const isRandom)
{
  ev.DisplaySweepEnvVars();

  // Compute how many possible Transfers are permitted (unique SRC/EXE/DST triplets)
  std::vector<std::pair<ExeType, int>> exeList;
  for (auto exe : ev.sweepExe)
  {
    ExeType const exeType = CharToExeType(exe);
    if (IsGpuType(exeType))
    {
      for (int exeIndex = 0; exeIndex < ev.numGpuDevices; ++exeIndex)
        exeList.push_back(std::make_pair(exeType, exeIndex));
    }
    else if (IsCpuType(exeType))
    {
      for (int exeIndex = 0; exeIndex < ev.numCpuDevices; ++exeIndex)
      {
        // Skip NUMA nodes that have no CPUs (e.g. CXL)
        if (ev.numCpusPerNuma[exeIndex] == 0) continue;
        exeList.push_back(std::make_pair(exeType, exeIndex));
      }
    }
  }
  int numExes = exeList.size();

  std::vector<std::pair<MemType, int>> srcList;
  for (auto src : ev.sweepSrc)
  {
    MemType const srcType = CharToMemType(src);
    int const numDevices = (srcType == MEM_NULL) ? 1 : IsGpuType(srcType) ? ev.numGpuDevices : ev.numCpuDevices;

    for (int srcIndex = 0; srcIndex < numDevices; ++srcIndex)
      srcList.push_back(std::make_pair(srcType, srcIndex));
  }
  int numSrcs = srcList.size();


  std::vector<std::pair<MemType, int>> dstList;
  for (auto dst : ev.sweepDst)
  {
    MemType const dstType = CharToMemType(dst);
    int const numDevices = (dstType == MEM_NULL) ? 1 : IsGpuType(dstType) ? ev.numGpuDevices : ev.numCpuDevices;

    for (int dstIndex = 0; dstIndex < numDevices; ++dstIndex)
      dstList.push_back(std::make_pair(dstType, dstIndex));
  }
  int numDsts = dstList.size();

  // Build array of possibilities, respecting any additional restrictions (e.g. XGMI hop count)
  struct TransferInfo
  {
    MemType srcType; int srcIndex;
    ExeType exeType; int exeIndex;
    MemType dstType; int dstIndex;
  };

  // If either XGMI minimum is non-zero, or XGMI maximum is specified and non-zero then both links must be XGMI
  bool const useXgmiOnly = (ev.sweepXgmiMin > 0 || ev.sweepXgmiMax > 0);

  std::vector<TransferInfo> possibleTransfers;
  TransferInfo tinfo;
  for (int i = 0; i < numExes; ++i)
  {
    // Skip CPU executors if XGMI link must be used
    if (useXgmiOnly && !IsGpuType(exeList[i].first)) continue;
    tinfo.exeType  = exeList[i].first;
    tinfo.exeIndex = exeList[i].second;

    bool isXgmiSrc  = false;
    int  numHopsSrc = 0;
    for (int j = 0; j < numSrcs; ++j)
    {
      if (IsGpuType(exeList[i].first) && IsGpuType(srcList[j].first))
      {
        if (exeList[i].second != srcList[j].second)
        {
#if defined(__NVCC__)
          isXgmiSrc = false;
#else
          uint32_t exeToSrcLinkType, exeToSrcHopCount;
          HIP_CALL(hipExtGetLinkTypeAndHopCount(RemappedIndex(exeList[i].second, false),
                                                RemappedIndex(srcList[j].second, false),
                                                &exeToSrcLinkType,
                                                &exeToSrcHopCount));
          isXgmiSrc = (exeToSrcLinkType == HSA_AMD_LINK_INFO_TYPE_XGMI);
          if (isXgmiSrc) numHopsSrc = exeToSrcHopCount;
#endif
        }
        else
        {
          isXgmiSrc = true;
          numHopsSrc = 0;
        }

        // Skip this SRC if it is not XGMI but only XGMI links may be used
        if (useXgmiOnly && !isXgmiSrc) continue;

        // Skip this SRC if XGMI distance is already past limit
        if (ev.sweepXgmiMax >= 0 && isXgmiSrc && numHopsSrc > ev.sweepXgmiMax) continue;
      }
      else if (srcList[j].first != MEM_NULL && useXgmiOnly) continue;

      tinfo.srcType  = srcList[j].first;
      tinfo.srcIndex = srcList[j].second;

      bool isXgmiDst = false;
      int  numHopsDst = 0;
      for (int k = 0; k < numDsts; ++k)
      {
        if (IsGpuType(exeList[i].first) && IsGpuType(dstList[k].first))
        {
          if (exeList[i].second != dstList[k].second)
          {
#if defined(__NVCC__)
            isXgmiSrc = false;
#else
            uint32_t exeToDstLinkType, exeToDstHopCount;
            HIP_CALL(hipExtGetLinkTypeAndHopCount(RemappedIndex(exeList[i].second, false),
                                                  RemappedIndex(dstList[k].second, false),
                                                  &exeToDstLinkType,
                                                  &exeToDstHopCount));
            isXgmiDst = (exeToDstLinkType == HSA_AMD_LINK_INFO_TYPE_XGMI);
            if (isXgmiDst) numHopsDst = exeToDstHopCount;
#endif
          }
          else
          {
            isXgmiDst = true;
            numHopsDst = 0;
          }
        }

        // Skip this DST if it is not XGMI but only XGMI links may be used
        if (dstList[k].first != MEM_NULL && useXgmiOnly && !isXgmiDst) continue;

        // Skip this DST if total XGMI distance (SRC + DST) is less than min limit
        if (ev.sweepXgmiMin > 0 && (numHopsSrc + numHopsDst < ev.sweepXgmiMin)) continue;

        // Skip this DST if total XGMI distance (SRC + DST) is greater than max limit
        if (ev.sweepXgmiMax >= 0 && (numHopsSrc + numHopsDst) > ev.sweepXgmiMax) continue;

#if defined(__NVCC__)
        // Skip CPU executors on GPU memory on NVIDIA platform
        if (IsCpuType(exeList[i].first) && (IsGpuType(dstList[j].first) || IsGpuType(dstList[k].first)))
          continue;
#endif

        tinfo.dstType  = dstList[k].first;
        tinfo.dstIndex = dstList[k].second;

        // Skip if there is no src and dst
        if (tinfo.srcType == MEM_NULL && tinfo.dstType == MEM_NULL) continue;

        possibleTransfers.push_back(tinfo);
      }
    }
  }

  int const numPossible = (int)possibleTransfers.size();
  int maxParallelTransfers = (ev.sweepMax == 0 ? numPossible : ev.sweepMax);

  if (ev.sweepMin > numPossible)
  {
    printf("No valid test configurations exist\n");
    return;
  }

  if (ev.outputToCsv)
  {
    printf("\nTest#,Transfer#,NumBytes,Src,Exe,Dst,CUs,BW(GB/s),Time(ms),"
           "ExeToSrcLinkType,ExeToDstLinkType,SrcAddr,DstAddr\n");
  }

  int numTestsRun = 0;
  int M = ev.sweepMin;
  std::uniform_int_distribution<int> randSize(1, numBytesPerTransfer / sizeof(float));
  std::uniform_int_distribution<int> distribution(ev.sweepMin, maxParallelTransfers);

  // Log sweep to configuration file
  FILE *fp = fopen("lastSweep.cfg", "w");
  if (!fp)
  {
    printf("[ERROR] Unable to open lastSweep.cfg.  Check permissions\n");
    exit(1);
  }

  // Create bitmask of numPossible triplets, of which M will be chosen
  std::string bitmask(M, 1);  bitmask.resize(numPossible, 0);
  auto cpuStart = std::chrono::high_resolution_clock::now();
  while (1)
  {
    if (isRandom)
    {
      // Pick random number of simultaneous transfers to execute
      // NOTE: This currently skews distribution due to some #s having more possibilities than others
      M = distribution(*ev.generator);

      // Generate a random bitmask
      for (int i = 0; i < numPossible; i++)
        bitmask[i] = (i < M) ? 1 : 0;
      std::shuffle(bitmask.begin(), bitmask.end(), *ev.generator);
    }

    // Convert bitmask to list of Transfers
    std::vector<Transfer> transfers;
    for (int value = 0; value < numPossible; ++value)
    {
      if (bitmask[value])
      {
        // Convert integer value to (SRC->EXE->DST) triplet
        Transfer transfer;
        transfer.numSrcs        = (possibleTransfers[value].srcType == MEM_NULL ? 0 : 1);
        transfer.numDsts        = (possibleTransfers[value].dstType == MEM_NULL ? 0 : 1);
        transfer.srcType        = {possibleTransfers[value].srcType};
        transfer.srcIndex       = {possibleTransfers[value].srcIndex};
        transfer.exeType        = possibleTransfers[value].exeType;
        transfer.exeIndex       = possibleTransfers[value].exeIndex;
        transfer.exeSubIndex    = -1;
        transfer.dstType        = {possibleTransfers[value].dstType};
        transfer.dstIndex       = {possibleTransfers[value].dstIndex};
        transfer.numSubExecs    = IsGpuType(transfer.exeType) ? numGpuSubExecs : numCpuSubExecs;
        transfer.numBytes       = ev.sweepRandBytes ? randSize(*ev.generator) * sizeof(float) : 0;
        transfers.push_back(transfer);
      }
    }

    LogTransfers(fp, ++numTestsRun, transfers);
    ExecuteTransfers(ev, numTestsRun, numBytesPerTransfer / sizeof(float), transfers);

    // Check for test limit
    if (numTestsRun == ev.sweepTestLimit)
    {
      printf("Test limit reached\n");
      break;
    }

    // Check for time limit
    auto cpuDelta = std::chrono::high_resolution_clock::now() - cpuStart;
    double totalCpuTime = std::chrono::duration_cast<std::chrono::duration<double>>(cpuDelta).count();
    if (ev.sweepTimeLimit && totalCpuTime > ev.sweepTimeLimit)
    {
      printf("Time limit exceeded\n");
      break;
    }

    // Increment bitmask if not random sweep
    if (!isRandom && !std::prev_permutation(bitmask.begin(), bitmask.end()))
    {
      M++;
      // Check for completion
      if (M > maxParallelTransfers)
      {
        printf("Sweep complete\n");
        break;
      }
      for (int i = 0; i < numPossible; i++)
        bitmask[i] = (i < M) ? 1 : 0;
    }
  }
  fclose(fp);
}

void LogTransfers(FILE *fp, int const testNum, std::vector<Transfer> const& transfers)
{
  fprintf(fp, "# Test %d\n", testNum);
  fprintf(fp, "%d", -1 * (int)transfers.size());
  for (auto const& transfer : transfers)
  {
    fprintf(fp, " (%c%d->%c%d->%c%d %d %lu)",
            MemTypeStr[transfer.srcType[0]], transfer.srcIndex[0],
            ExeTypeStr[transfer.exeType],    transfer.exeIndex,
            MemTypeStr[transfer.dstType[0]], transfer.dstIndex[0],
            transfer.numSubExecs,
            transfer.numBytes);
  }
  fprintf(fp, "\n");
  fflush(fp);
}

std::string PtrVectorToStr(std::vector<float*> const& strVector, int const initOffset)
{
  std::stringstream ss;
  for (int i = 0; i < strVector.size(); ++i)
  {
    if (i) ss << " ";
    ss << (strVector[i] + initOffset);
  }
  return ss.str();
}

void ReportResults(EnvVars const& ev, std::vector<Transfer> const& transfers, TestResults const results)
{
  char sep = ev.outputToCsv ? ',' : '|';
  size_t numTimedIterations = results.numTimedIterations;

  // Loop over each executor
  for (auto exeInfoPair : results.exeResults) {
    ExeResult const& exeResult = exeInfoPair.second;
    ExeType exeType  = exeInfoPair.first.first;
    int     exeIndex = exeInfoPair.first.second;

    printf(" Executor: %3s %02d %c %7.3f GB/s %c %8.3f ms %c %12lu bytes %c %-7.3f GB/s (sum)\n",
           ExeTypeName[exeType], exeIndex, sep, exeResult.bandwidthGbs, sep,
           exeResult.durationMsec, sep, exeResult.totalBytes, sep, exeResult.sumBandwidthGbs);

    for (int idx : exeResult.transferIdx) {
      Transfer const& t = transfers[idx];

      char exeSubIndexStr[32] = "";
      if (ev.useXccFilter || t.exeType == EXE_GPU_DMA) {
        if (t.exeSubIndex == -1)
          sprintf(exeSubIndexStr, ".*");
        else
          sprintf(exeSubIndexStr, ".%d", t.exeSubIndex);
      }
      printf("     Transfer %02d  %c %7.3f GB/s %c %8.3f ms %c %12lu bytes %c %s -> %s%02d%s:%03d -> %s\n",
             t.transferIndex, sep,
             t.transferBandwidth, sep,
             t.transferTime, sep,
             t.numBytesActual, sep,
             t.SrcToStr().c_str(),
             ExeTypeName[t.exeType], t.exeIndex,
             exeSubIndexStr,
             t.numSubExecs,
             t.DstToStr().c_str());

      // Show per-iteration timing information
      if (ev.showIterations) {

        std::set<std::pair<double, int>> times;
        double stdDevTime = 0;
        double stdDevBw = 0;
        for (int i = 0; i < numTimedIterations; i++) {
          times.insert(std::make_pair(t.perIterationTime[i], i+1));
          double const varTime = fabs(t.transferTime - t.perIterationTime[i]);
          stdDevTime += varTime * varTime;

          double iterBandwidthGbs = (t.numBytesActual / 1.0E9) / t.perIterationTime[i] * 1000.0f;
          double const varBw = fabs(iterBandwidthGbs - t.transferBandwidth);
          stdDevBw += varBw * varBw;
        }
        stdDevTime = sqrt(stdDevTime / numTimedIterations);
        stdDevBw = sqrt(stdDevBw / numTimedIterations);

        for (auto time : times) {
          double iterDurationMsec = time.first;
          double iterBandwidthGbs = (t.numBytesActual / 1.0E9) / iterDurationMsec * 1000.0f;
          printf("      Iter %03d    %c %7.3f GB/s %c %8.3f ms %c", time.second, sep, iterBandwidthGbs, sep, iterDurationMsec, sep);

          std::set<int> usedXccs;
          if (time.second - 1 < t.perIterationCUs.size()) {
            printf(" CUs:");
            for (auto x : t.perIterationCUs[time.second - 1]) {
              printf(" %02d:%02d", x.first, x.second);
              usedXccs.insert(x.first);
            }
          }
          printf(" XCCs:");
          for (auto x : usedXccs)
            printf(" %02d", x);
          printf("\n");
        }
        printf("      StandardDev %c %7.3f GB/s %c %8.3f ms %c\n", sep, stdDevBw, sep, stdDevTime, sep);
      }
    }
  }

  printf(" Aggregate (CPU)  %c %7.3f GB/s %c %8.3f ms %c %12lu bytes %c Overhead: %.3f ms\n", sep,
         results.totalBandwidthCpu, sep, results.totalDurationMsec, sep, results.totalBytesTransferred, sep, results.overheadMsec);
}

void RunHealthCheck(EnvVars ev)
{
  // Check for supported platforms
#if defined(__NVCC__)
  printf("[WARN] healthcheck preset not supported on NVIDIA hardware\n");
  return;
#else

  bool hasFail = false;

  // Force use of single stream
  ev.useSingleStream = 1;

  for (int gpuId = 0; gpuId < ev.numGpuDevices; gpuId++) {
    hipDeviceProp_t prop;
    HIP_CALL(hipGetDeviceProperties(&prop, gpuId));
    std::string fullName = prop.gcnArchName;
    std::string archName = fullName.substr(0, fullName.find(':'));
    if (!(archName == "gfx940" || archName == "gfx941" || archName == "gfx942"))
    {
      printf("[WARN] healthcheck preset is currently only supported on MI300 series hardware\n");
      exit(1);
    }
  }

  // Pass limits
  double udirLimit = getenv("LIMIT_UDIR") ? atof(getenv("LIMIT_UDIR")) : (int)(48 * 0.95);
  double bdirLimit = getenv("LIMIT_BDIR") ? atof(getenv("LIMIT_BDIR")) : (int)(96 * 0.95);
  double a2aLimit  = getenv("LIMIT_A2A")  ? atof(getenv("LIMIT_A2A"))  : (int)(45 * 0.95);

  // Run CPU to GPU

  // Run unidirectional read from CPU to GPU
  printf("Testing unidirectional reads from CPU ");
  {
    std::vector<std::pair<int, double>> fails;
    for (int gpuId = 0; gpuId < ev.numGpuDevices; gpuId++) {
      printf("."); fflush(stdout);
      std::vector<Transfer> transfers(1);
      Transfer& t = transfers[0];
      t.exeType     = EXE_GPU_GFX;
      t.exeIndex    = gpuId;
      t.numBytes    = 64*1024*1024;
      t.numBytesActual = 64*1024*1024;
      t.numSrcs     = 1;
      t.srcType.push_back(MEM_CPU);
      t.srcIndex.push_back(GetClosestNumaNode(gpuId));
      t.numDsts     = 0;
      t.dstType.clear();
      t.dstIndex.clear();

    // Loop over number of CUs to use
      bool passed = false;
      double bestResult = 0;
      for (int cu = 7; cu <= 10; cu++) {
        t.numSubExecs = cu;
        TestResults tesResults = ExecuteTransfersImpl(ev, transfers);
        bestResult = std::max(bestResult, t.transferBandwidth);
        if (t.transferBandwidth >= udirLimit) {
          passed = true;
          break;
      }
      }
      if (!passed) fails.push_back(std::make_pair(gpuId, bestResult));
    }
    if (fails.size() == 0) {
      printf("PASS\n");
    } else {
      hasFail = true;
      printf("FAIL (%lu test(s))\n", fails.size());
      for (auto p : fails) {
        printf(" GPU %02d: Measured: %6.2f GB/s      Criteria: %6.2f GB/s\n", p.first, p.second, udirLimit);
      }
    }
  }

  // Run unidirectional write from GPU to CPU
  printf("Testing unidirectional writes to  CPU ");
  {
    std::vector<std::pair<int, double>> fails;
    for (int gpuId = 0; gpuId < ev.numGpuDevices; gpuId++) {
      printf("."); fflush(stdout);
      std::vector<Transfer> transfers(1);
      Transfer& t = transfers[0];
      t.exeType     = EXE_GPU_GFX;
      t.exeIndex    = gpuId;
      t.numBytes    = 64*1024*1024;
      t.numBytesActual = 64*1024*1024;
      t.numDsts     = 1;
      t.dstType.push_back(MEM_CPU);
      t.dstIndex.push_back(GetClosestNumaNode(gpuId));
      t.numSrcs     = 0;
      t.srcType.clear();
      t.srcIndex.clear();

      // Loop over number of CUs to use
      bool passed = false;
      double bestResult = 0;
      for (int cu = 7; cu <= 10; cu++) {
        t.numSubExecs = cu;

        TestResults tesResults = ExecuteTransfersImpl(ev, transfers);
        bestResult = std::max(bestResult, t.transferBandwidth);
        if (t.transferBandwidth >= udirLimit) {
          passed = true;
          break;
        }
      }
      if (!passed) fails.push_back(std::make_pair(gpuId, bestResult));
    }
    if (fails.size() == 0) {
      printf("PASS\n");
    } else {
      hasFail = true;
      printf("FAIL (%lu test(s))\n", fails.size());
      for (auto p : fails) {
        printf(" GPU %02d: Measured: %6.2f GB/s      Criteria: %6.2f GB/s\n", p.first, p.second, udirLimit);
      }
    }
  }

  // Run bidirectional tests
  printf("Testing bidirectional  reads + writes ");
  {
    std::vector<std::pair<int, double>> fails;
    for (int gpuId = 0; gpuId < ev.numGpuDevices; gpuId++) {
      printf("."); fflush(stdout);
      std::vector<Transfer> transfers(2);
      Transfer& t0 = transfers[0];
      Transfer& t1 = transfers[1];

      t0.exeType     = EXE_GPU_GFX;
      t0.exeIndex    = gpuId;
      t0.numBytes    = 64*1024*1024;
      t0.numBytesActual = 64*1024*1024;
      t0.numSrcs     = 1;
      t0.srcType.push_back(MEM_CPU);
      t0.srcIndex.push_back(GetClosestNumaNode(gpuId));
      t0.numDsts     = 0;
      t0.dstType.clear();
      t0.dstIndex.clear();

      t1.exeType     = EXE_GPU_GFX;
      t1.exeIndex    = gpuId;
      t1.numBytes    = 64*1024*1024;
      t1.numBytesActual = 64*1024*1024;
      t1.numDsts     = 1;
      t1.dstType.push_back(MEM_CPU);
      t1.dstIndex.push_back(GetClosestNumaNode(gpuId));
      t1.numSrcs     = 0;
      t1.srcType.clear();
      t1.srcIndex.clear();

      // Loop over number of CUs to use
      bool passed = false;
      double bestResult = 0;
      for (int cu = 7; cu <= 10; cu++) {
        t0.numSubExecs = cu;
        t1.numSubExecs = cu;

        TestResults tesResults = ExecuteTransfersImpl(ev, transfers);
        double sum = t0.transferBandwidth + t1.transferBandwidth;
        bestResult = std::max(bestResult, sum);
        if (sum >= bdirLimit) {
          passed = true;
          break;
        }
      }
      if (!passed) fails.push_back(std::make_pair(gpuId, bestResult));
    }
    if (fails.size() == 0) {
      printf("PASS\n");
    } else {
      hasFail = true;
      printf("FAIL (%lu test(s))\n", fails.size());
      for (auto p : fails) {
        printf(" GPU %02d: Measured: %6.2f GB/s      Criteria: %6.2f GB/s\n", p.first, p.second, bdirLimit);
      }
    }
  }

  // Run XGMI tests:
  printf("Testing all-to-all XGMI copies        "); fflush(stdout);
  {
    ev.gfxUnroll = 2;
    std::vector<Transfer> transfers;
    for (int i = 0; i < ev.numGpuDevices; i++) {
      for (int j = 0; j < ev.numGpuDevices; j++) {
        if (i == j) continue;
        Transfer t;
        t.exeType = EXE_GPU_GFX;
        t.exeIndex = i;
        t.numBytes = t.numBytesActual = 64*1024*1024;
        t.numSrcs = 1;
        t.numDsts = 1;
        t.numSubExecs = 8;
        t.srcType.push_back(MEM_GPU_FINE);
        t.dstType.push_back(MEM_GPU_FINE);
        t.srcIndex.push_back(i);
        t.dstIndex.push_back(j);
        transfers.push_back(t);
      }
    }
    TestResults tesResults = ExecuteTransfersImpl(ev, transfers);
    std::vector<std::pair<std::pair<int,int>, double>> fails;
    int transferIdx = 0;
    for (int i = 0; i < ev.numGpuDevices; i++) {
      printf("."); fflush(stdout);
      for (int j = 0; j < ev.numGpuDevices; j++) {
        if (i == j) continue;
        Transfer const& t = transfers[transferIdx];
        if (t.transferBandwidth < a2aLimit) {
          fails.push_back(std::make_pair(std::make_pair(i,j), t.transferBandwidth));
        }
        transferIdx++;
      }
    }
    if (fails.size() == 0) {
      printf("PASS\n");
    } else {
      hasFail = true;
      printf("FAIL (%lu test(s))\n", fails.size());
      for (auto p : fails) {
        printf(" GPU %02d to GPU %02d: %6.2f GB/s      Criteria: %6.2f GB/s\n", p.first.first, p.first.second, p.second, a2aLimit);
      }
    }
  }

  exit(hasFail ? 1 : 0);
#endif
}