GitLab

**Description**
This commit fixes error of missing key 'percentile' in parsing FIO result.

**Description**
Revise the DockerBenchmark base to support image pull, image rm etc.

**Major Revision**
- image pull in _preprocess()
- image clean in _postprocess()
- execute customized commands in _benchmark()
- add unit tests

Benchmarks: Code Revision - Revise metric name generation and default config for disk performance benchmark (#175)

**Description**
This commit revises disk performance benchmark, including:
1) Add missing benchmark name in default config;
2) Avoid using reserved character ':' in metric name.

**Description**
Package frequently-used subprocess invoke into function.

**Description**
This commit adds gpu_sm_copy benchmark and related tests.

**Description**
Remove IB device port info in command to fix bug of IB loopback.

**Major Revision**
- Remove IB device port info in command to fix bug of IB loopback 

**Description**
Add gemm flops microbenchmark for amd.

**Major Revision**
- Add gemm flops microbenchmark for amd.
- Add related example and test file.

**Description**
Extract base class for gemm flops microbenchmark.

**Major Revision**
- extract base class for gemm flops microbenchmark and add related test.
- revise gemm_flops_performance for cuda.

**Description**
Rename `kernel_launch_overhead_event` to `event_overhead`, `kernel_launch_overhead_wall` to `wall_overhead`.

**Description**
Add memory bus bandwidth performance microbenchmark for amd.

**Major Revision**
- Add memory bus bandwidth performance microbenchmark for amd.
- Add related example and test file.

**Description**
This commit adds the benchmark program for GPU-initiated data transfer benchmark.

Benchmarks: Fix Bug - fix bug of microbenmark building cublas and cudnn for amd in build pipeline (#166)

**Description**
Fix bug of microbenmark building cublas and cudnn for amd

**Major Revision**
- remove cuda LANGUAGES in project()
- check CUDAToolkit quiet and then build if found

**Description**
Rename computation_communication_overlap microbenchmark metric .

**Major Revision**
- remove rank info in metric.
- simplify and rename metric.

**Description**
extract base class for memory bandwidth microbenchmark.

**Major Revision**
- revise and optimize cuda_memory_bandwidth_performance
- extract base class for memory bandwidth microbenchmark
- add test for base class

**Description**
This commit adds readwrite I/O pattern for FIO benchmark. Read/write ratio is fixed at 4:1.

**Description**
Generate the summarized output files from all nodes. For each metric, do the reduce operation according to the `reduce_op`

**Major Revision**
- Generate the summarized json file per node:
For microbenchmark, the format is `{benchmark_name}/[{run_count}/]{metric_name}[:rank]`
For modelbenchmark, the format is `{benchmark_name}/{sub_benchmark_name}/[{run_count}/]{metric_name}`
`[]` means optional.
```
{
  "kernel-launch/overhead_event:0": 0.00583,
  "kernel-launch/overhead_event:1": 0.00545,
  "kernel-launch/overhead_event:2": 0.00581,
  "kernel-launch/overhead_event:3": 0.00572,
  "kernel-launch/overhead_event:4": 0.00559,
  "kernel-launch/overhead_event:5": 0.00591,
  "kernel-launch/overhead_event:6": 0.00562,
  "kernel-launch/overhead_event:7": 0.00586,
  "resnet_models/pytorch-resnet50/steptime-train-float32": 544.0827468410134,
  "resnet_models/pytorch-resnet50/throughput-train-float32": 353.7607016465773,
  "resnet_models/pytorch-resnet50/steptime-train-float16": 425.40482617914677,
  "resnet_models/pytorch-resnet50/throughput-train-float16": 454.0142363793973,
  "pytorch-sharding-matmul/0/allreduce": 10.561786651611328,
  "pytorch-sharding-matmul/1/allreduce": 10.561786651611328,
  "pytorch-sharding-matmul/0/allgather": 10.088025093078613,
  "pytorch-sharding-matmul/1/allgather": 10.088025093078613
}
```
- Generate the summarized jsonl file for all nodes, each line is the result from one node in json format.

**Description**
Change the field name `reduce` to `reduce_op`.

**Description**
Set reduce type for current benchmarks' metrics, including model benchmarks and ShardingMatmul.

**Description**
Replace `sum(results) / len(results)` with `statistics.mean(results)`

**Description**
Add reduce function support for output summary.

**Major Revision**
- Add reducer class to maintain all reduce functions.
- Save reduce type of each metric into `BenchmarkResult`
- Fix UT.

**Description**
Add rccl bandwidth microbenchmark for rocm.

**Major Revision**
- Register rccl-bw benchmark.

__Description__
Cherry-pick bug fixes from v0.2.1 to main.

__Major Revisions__
* Fix bug of VGG models failed on A100 GPU with batch_size=128.
* Fix Ansible connection issue when running in localhost.
* Update version in packages and docs.

**Description**
Add the source code of rocm kernel launch overhead benchmark. 

**Major Revision**
- Revise cmake build logic to support both cuda and rocm

**Description**
Support rocm cmake build. 

**Major Revision**
- Add  some envs in rocm_common.cmake to support rocm cmake build.

**Description**
Add NCCL performance microbenchmark.

**Major Revision**
- Add microbenchmark, example, test, config for NCCL

**Description**
Add RDMA Loopback performance microbenchmark.

**Major Revision**
- Add microbenchmark, example, test, config for RDMA Loopback

**Description**
Add disk performance microbenchmark.

**Major Revision**
- Add microbenchmark, example, test, config for disk performance.

**Minor Revision**
- Fix bugs in executor unit test related to default enabled tests.

Add microbenchmark, example, test, config for cuda memory performance and Add cuda-samples(tag with cuda version) as git submodule and update related makefile

* fix bug for nvidia v100
* hard code the supported dict for different arch.

* add config file for ndv4.

* replace torch.optim.AdamW with transformers.AdamW.

Benchmarks: Add Feature - Add DistributedImpl and DistributedBackend arguments for micro benchmark. (#100)

rename bin name and result metric of cublas and cudnn microbenchmark

Fix bugs and refine log in single GPU benchmarks:

* Fix none framework issue
* Fix empty parameter bug
* Remove missed mobilenet_v3 models
* Change benchmark registration log to debug level
* Add pid in logging
* Add missing benchmarks in default config
* Fix deprecated logging warn

* Clean up the cache.

* fix return code reset issue

* Change default shape of sharding-matmul.

* add cuda flops performance benchmark.

* add python related cudnn microbenchmark