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"...mmaction/datasets/pipelines/formatting.py" did not exist on "44c28b2bb33d6ce9f2b02e1e6e0dd7e694c108c6"
Commit 7926888f authored by wangkx1's avatar wangkx1
Browse files

update ollama_use_funcs

parent 28e95ed5
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ollama/gpu/gpu_darwin.go deleted 100644 → 0
View file @ 28e95ed5
//go:build darwin
package gpu
/*
#cgo CFLAGS: -x objective-c
#cgo LDFLAGS: -framework Foundation -framework CoreGraphics -framework Metal
#include "gpu_info_darwin.h"
*/
import "C"
import (
"runtime"
"github.com/ollama/ollama/format"
)
const (
metalMinimumMemory = 512 * format.MebiByte
)
func GetGPUInfo() GpuInfoList {
mem, _ := GetCPUMem()
if runtime.GOARCH == "amd64" {
return []GpuInfo{
{
Library: "cpu",
Variant: GetCPUCapability(),
memInfo: mem,
},
}
}
info := GpuInfo{
Library: "metal",
ID: "0",
}
info.TotalMemory = uint64(C.getRecommendedMaxVRAM())
// TODO is there a way to gather actual allocated video memory? (currentAllocatedSize doesn't work)
info.FreeMemory = info.TotalMemory
info.MinimumMemory = metalMinimumMemory
return []GpuInfo{info}
}
func GetCPUInfo() GpuInfoList {
mem, _ := GetCPUMem()
return []GpuInfo{
{
Library: "cpu",
Variant: GetCPUCapability(),
memInfo: mem,
},
}
}
func GetCPUMem() (memInfo, error) {
return memInfo{
TotalMemory: uint64(C.getPhysicalMemory()),
FreeMemory: uint64(C.getFreeMemory()),
// FreeSwap omitted as Darwin uses dynamic paging
}, nil
}
func (l GpuInfoList) GetVisibleDevicesEnv() (string, string) {
// No-op on darwin
return "", ""
}
ollama/gpu/gpu_info.h deleted 100644 → 0
View file @ 28e95ed5
#ifndef __APPLE__
#ifndef __GPU_INFO_H__
#define __GPU_INFO_H__
#include <stdint.h>
#include <stdio.h>
#include <stdlib.h>
#ifndef _WIN32
#include <dlfcn.h>
#define LOAD_LIBRARY(lib, flags) dlopen(lib, flags)
#define LOAD_SYMBOL(handle, sym) dlsym(handle, sym)
#define LOAD_ERR() strdup(dlerror())
#define UNLOAD_LIBRARY(handle) dlclose(handle)
#else
#include <windows.h>
#define LOAD_LIBRARY(lib, flags) LoadLibrary(lib)
#define LOAD_SYMBOL(handle, sym) GetProcAddress(handle, sym)
#define UNLOAD_LIBRARY(handle) FreeLibrary(handle)
#define LOAD_ERR() ({\
LPSTR messageBuffer = NULL; \
size_t size = FormatMessageA(FORMAT_MESSAGE_ALLOCATE_BUFFER | FORMAT_MESSAGE_FROM_SYSTEM | FORMAT_MESSAGE_IGNORE_INSERTS, \
NULL, GetLastError(), MAKELANGID(LANG_NEUTRAL, SUBLANG_DEFAULT), (LPSTR)&messageBuffer, 0, NULL); \
char *resp = strdup(messageBuffer); \
LocalFree(messageBuffer); \
resp; \
})
#endif
#define LOG(verbose, ...) \
do { \
if (verbose) { \
fprintf(stderr, __VA_ARGS__); \
} \
} while (0)
#ifdef __cplusplus
extern "C" {
#endif
#define GPU_ID_LEN 64
#define GPU_NAME_LEN 96
typedef struct mem_info {
char *err; // If non-nill, caller responsible for freeing
char gpu_id[GPU_ID_LEN];
char gpu_name[GPU_NAME_LEN];
uint64_t total;
uint64_t free;
uint64_t used;
// Compute Capability
int major;
int minor;
int patch;
} mem_info_t;
void cpu_check_ram(mem_info_t *resp);
#ifdef __cplusplus
}
#endif
#include "gpu_info_cudart.h"
#include "gpu_info_nvcuda.h"
#include "gpu_info_nvml.h"
#include "gpu_info_oneapi.h"
#endif // __GPU_INFO_H__
#endif // __APPLE__
ollama/gpu/gpu_info_cudart.c deleted 100644 → 0
View file @ 28e95ed5
#ifndef __APPLE__ // TODO - maybe consider nvidia support on intel macs?
#include <string.h>
#include "gpu_info_cudart.h"
void cudart_init(char *cudart_lib_path, cudart_init_resp_t *resp) {
cudartReturn_t ret;
resp->err = NULL;
resp->num_devices = 0;
const int buflen = 256;
char buf[buflen + 1];
int i;
struct lookup {
char *s;
void **p;
} l[] = {
{"cudaSetDevice", (void *)&resp->ch.cudaSetDevice},
{"cudaDeviceSynchronize", (void *)&resp->ch.cudaDeviceSynchronize},
{"cudaDeviceReset", (void *)&resp->ch.cudaDeviceReset},
{"cudaMemGetInfo", (void *)&resp->ch.cudaMemGetInfo},
{"cudaGetDeviceCount", (void *)&resp->ch.cudaGetDeviceCount},
{"cudaDeviceGetAttribute", (void *)&resp->ch.cudaDeviceGetAttribute},
{"cudaDriverGetVersion", (void *)&resp->ch.cudaDriverGetVersion},
{"cudaGetDeviceProperties", (void *)&resp->ch.cudaGetDeviceProperties},
{NULL, NULL},
};
resp->ch.handle = LOAD_LIBRARY(cudart_lib_path, RTLD_LAZY);
if (!resp->ch.handle) {
char *msg = LOAD_ERR();
LOG(resp->ch.verbose, "library %s load err: %s\n", cudart_lib_path, msg);
snprintf(buf, buflen,
"Unable to load %s library to query for Nvidia GPUs: %s",
cudart_lib_path, msg);
free(msg);
resp->err = strdup(buf);
return;
}
for (i = 0; l[i].s != NULL; i++) {
*l[i].p = LOAD_SYMBOL(resp->ch.handle, l[i].s);
if (!*(l[i].p)) {
char *msg = LOAD_ERR();
LOG(resp->ch.verbose, "dlerr: %s\n", msg);
UNLOAD_LIBRARY(resp->ch.handle);
resp->ch.handle = NULL;
snprintf(buf, buflen, "symbol lookup for %s failed: %s", l[i].s,
msg);
free(msg);
resp->err = strdup(buf);
return;
}
}
ret = (*resp->ch.cudaSetDevice)(0);
if (ret != CUDART_SUCCESS) {
LOG(resp->ch.verbose, "cudaSetDevice err: %d\n", ret);
UNLOAD_LIBRARY(resp->ch.handle);
resp->ch.handle = NULL;
if (ret == CUDA_ERROR_INSUFFICIENT_DRIVER) {
resp->err = strdup("your nvidia driver is too old or missing. If you have a CUDA GPU please upgrade to run ollama");
return;
}
snprintf(buf, buflen, "cudart init failure: %d", ret);
resp->err = strdup(buf);
return;
}
int version = 0;
cudartDriverVersion_t driverVersion;
driverVersion.major = 0;
driverVersion.minor = 0;
// Report driver version if we're in verbose mode, ignore errors
ret = (*resp->ch.cudaDriverGetVersion)(&version);
if (ret != CUDART_SUCCESS) {
LOG(resp->ch.verbose, "cudaDriverGetVersion failed: %d\n", ret);
} else {
driverVersion.major = version / 1000;
driverVersion.minor = (version - (driverVersion.major * 1000)) / 10;
LOG(resp->ch.verbose, "CUDA driver version: %d-%d\n", driverVersion.major, driverVersion.minor);
}
ret = (*resp->ch.cudaGetDeviceCount)(&resp->num_devices);
if (ret != CUDART_SUCCESS) {
LOG(resp->ch.verbose, "cudaGetDeviceCount err: %d\n", ret);
UNLOAD_LIBRARY(resp->ch.handle);
resp->ch.handle = NULL;
snprintf(buf, buflen, "unable to get device count: %d", ret);
resp->err = strdup(buf);
return;
}
}
void cudart_bootstrap(cudart_handle_t h, int i, mem_info_t *resp) {
resp->err = NULL;
cudartMemory_t memInfo = {0,0,0};
cudartReturn_t ret;
const int buflen = 256;
char buf[buflen + 1];
if (h.handle == NULL) {
resp->err = strdup("cudart handle isn't initialized");
return;
}
ret = (*h.cudaSetDevice)(i);
if (ret != CUDART_SUCCESS) {
snprintf(buf, buflen, "cudart device failed to initialize");
resp->err = strdup(buf);
return;
}
cudaDeviceProp_t props;
ret = (*h.cudaGetDeviceProperties)(&props, i);
if (ret != CUDART_SUCCESS) {
LOG(h.verbose, "[%d] device properties lookup failure: %d\n", i, ret);
snprintf(&resp->gpu_id[0], GPU_ID_LEN, "%d", i);
resp->major = 0;
resp->minor = 0;
} else {
int allNull = 1;
for (int j = 0; j < 16; j++) {
if (props.uuid.bytes[j] != 0) {
allNull = 0;
break;
}
}
if (allNull != 0) {
snprintf(&resp->gpu_id[0], GPU_ID_LEN, "%d", i);
} else {
// GPU-d110a105-ac29-1d54-7b49-9c90440f215b
snprintf(&resp->gpu_id[0], GPU_ID_LEN,
"GPU-%02x%02x%02x%02x-%02x%02x-%02x%02x-%02x%02x-%02x%02x%02x%02x%02x%02x",
props.uuid.bytes[0],
props.uuid.bytes[1],
props.uuid.bytes[2],
props.uuid.bytes[3],
props.uuid.bytes[4],
props.uuid.bytes[5],
props.uuid.bytes[6],
props.uuid.bytes[7],
props.uuid.bytes[8],
props.uuid.bytes[9],
props.uuid.bytes[10],
props.uuid.bytes[11],
props.uuid.bytes[12],
props.uuid.bytes[13],
props.uuid.bytes[14],
props.uuid.bytes[15]
);
}
resp->major = props.major;
resp->minor = props.minor;
// TODO add other useful properties from props
}
ret = (*h.cudaMemGetInfo)(&memInfo.free, &memInfo.total);
if (ret != CUDART_SUCCESS) {
snprintf(buf, buflen, "cudart device memory info lookup failure %d", ret);
resp->err = strdup(buf);
return;
}
resp->total = memInfo.total;
resp->free = memInfo.free;
resp->used = memInfo.used;
LOG(h.verbose, "[%s] CUDA totalMem %lu\n", resp->gpu_id, resp->total);
LOG(h.verbose, "[%s] CUDA freeMem %lu\n", resp->gpu_id, resp->free);
LOG(h.verbose, "[%s] CUDA usedMem %lu\n", resp->gpu_id, resp->used);
LOG(h.verbose, "[%s] Compute Capability %d.%d\n", resp->gpu_id, resp->major, resp->minor);
}
void cudart_release(cudart_handle_t h) {
LOG(h.verbose, "releasing cudart library\n");
UNLOAD_LIBRARY(h.handle);
h.handle = NULL;
}
#endif // __APPLE__
\ No newline at end of file
ollama/gpu/gpu_info_cudart.h deleted 100644 → 0
View file @ 28e95ed5
#ifndef __APPLE__
#ifndef __GPU_INFO_CUDART_H__
#define __GPU_INFO_CUDART_H__
#include "gpu_info.h"
// Just enough typedef's to dlopen/dlsym for memory information
typedef enum cudartReturn_enum {
CUDART_SUCCESS = 0,
CUDART_ERROR_INVALID_VALUE = 1,
CUDART_ERROR_MEMORY_ALLOCATION = 2,
CUDART_ERROR_INSUFFICIENT_DRIVER = 35,
// Other values omitted for now...
} cudartReturn_t;
typedef enum cudartDeviceAttr_enum {
cudartDevAttrComputeCapabilityMajor = 75,
cudartDevAttrComputeCapabilityMinor = 76,
// TODO - not yet wired up but may be useful for Jetson or other
// integrated GPU scenarios with shared memory
cudaDevAttrIntegrated = 18
} cudartDeviceAttr_t;
typedef void *cudartDevice_t; // Opaque is sufficient
typedef struct cudartMemory_st {
size_t total;
size_t free;
size_t used;
} cudartMemory_t;
typedef struct cudartDriverVersion {
int major;
int minor;
} cudartDriverVersion_t;
typedef struct cudaUUID {
unsigned char bytes[16];
} cudaUUID_t;
typedef struct cudaDeviceProp {
char name[256]; /**< ASCII string identifying device */
cudaUUID_t uuid; /**< 16-byte unique identifier */
char luid[8]; /**< 8-byte locally unique identifier. Value is undefined on TCC and non-Windows platforms */
unsigned int luidDeviceNodeMask; /**< LUID device node mask. Value is undefined on TCC and non-Windows platforms */
size_t totalGlobalMem; /**< Global memory available on device in bytes */
size_t sharedMemPerBlock; /**< Shared memory available per block in bytes */
int regsPerBlock; /**< 32-bit registers available per block */
int warpSize; /**< Warp size in threads */
size_t memPitch; /**< Maximum pitch in bytes allowed by memory copies */
int maxThreadsPerBlock; /**< Maximum number of threads per block */
int maxThreadsDim[3]; /**< Maximum size of each dimension of a block */
int maxGridSize[3]; /**< Maximum size of each dimension of a grid */
int clockRate; /**< Clock frequency in kilohertz */
size_t totalConstMem; /**< Constant memory available on device in bytes */
int major; /**< Major compute capability */
int minor; /**< Minor compute capability */
size_t textureAlignment; /**< Alignment requirement for textures */
size_t texturePitchAlignment; /**< Pitch alignment requirement for texture references bound to pitched memory */
int deviceOverlap; /**< Device can concurrently copy memory and execute a kernel. Deprecated. Use instead asyncEngineCount. */
int multiProcessorCount; /**< Number of multiprocessors on device */
int kernelExecTimeoutEnabled; /**< Specified whether there is a run time limit on kernels */
int integrated; /**< Device is integrated as opposed to discrete */
int canMapHostMemory; /**< Device can map host memory with cudaHostAlloc/cudaHostGetDevicePointer */
int computeMode; /**< Compute mode (See ::cudaComputeMode) */
int maxTexture1D; /**< Maximum 1D texture size */
int maxTexture1DMipmap; /**< Maximum 1D mipmapped texture size */
int maxTexture1DLinear; /**< Deprecated, do not use. Use cudaDeviceGetTexture1DLinearMaxWidth() or cuDeviceGetTexture1DLinearMaxWidth() instead. */
int maxTexture2D[2]; /**< Maximum 2D texture dimensions */
int maxTexture2DMipmap[2]; /**< Maximum 2D mipmapped texture dimensions */
int maxTexture2DLinear[3]; /**< Maximum dimensions (width, height, pitch) for 2D textures bound to pitched memory */
int maxTexture2DGather[2]; /**< Maximum 2D texture dimensions if texture gather operations have to be performed */
int maxTexture3D[3]; /**< Maximum 3D texture dimensions */
int maxTexture3DAlt[3]; /**< Maximum alternate 3D texture dimensions */
int maxTextureCubemap; /**< Maximum Cubemap texture dimensions */
int maxTexture1DLayered[2]; /**< Maximum 1D layered texture dimensions */
int maxTexture2DLayered[3]; /**< Maximum 2D layered texture dimensions */
int maxTextureCubemapLayered[2];/**< Maximum Cubemap layered texture dimensions */
int maxSurface1D; /**< Maximum 1D surface size */
int maxSurface2D[2]; /**< Maximum 2D surface dimensions */
int maxSurface3D[3]; /**< Maximum 3D surface dimensions */
int maxSurface1DLayered[2]; /**< Maximum 1D layered surface dimensions */
int maxSurface2DLayered[3]; /**< Maximum 2D layered surface dimensions */
int maxSurfaceCubemap; /**< Maximum Cubemap surface dimensions */
int maxSurfaceCubemapLayered[2];/**< Maximum Cubemap layered surface dimensions */
size_t surfaceAlignment; /**< Alignment requirements for surfaces */
int concurrentKernels; /**< Device can possibly execute multiple kernels concurrently */
int ECCEnabled; /**< Device has ECC support enabled */
int pciBusID; /**< PCI bus ID of the device */
int pciDeviceID; /**< PCI device ID of the device */
int pciDomainID; /**< PCI domain ID of the device */
int tccDriver; /**< 1 if device is a Tesla device using TCC driver, 0 otherwise */
int asyncEngineCount; /**< Number of asynchronous engines */
int unifiedAddressing; /**< Device shares a unified address space with the host */
int memoryClockRate; /**< Peak memory clock frequency in kilohertz */
int memoryBusWidth; /**< Global memory bus width in bits */
int l2CacheSize; /**< Size of L2 cache in bytes */
int persistingL2CacheMaxSize; /**< Device's maximum l2 persisting lines capacity setting in bytes */
int maxThreadsPerMultiProcessor;/**< Maximum resident threads per multiprocessor */
int streamPrioritiesSupported; /**< Device supports stream priorities */
int globalL1CacheSupported; /**< Device supports caching globals in L1 */
int localL1CacheSupported; /**< Device supports caching locals in L1 */
size_t sharedMemPerMultiprocessor; /**< Shared memory available per multiprocessor in bytes */
int regsPerMultiprocessor; /**< 32-bit registers available per multiprocessor */
int managedMemory; /**< Device supports allocating managed memory on this system */
int isMultiGpuBoard; /**< Device is on a multi-GPU board */
int multiGpuBoardGroupID; /**< Unique identifier for a group of devices on the same multi-GPU board */
int hostNativeAtomicSupported; /**< Link between the device and the host supports native atomic operations */
int singleToDoublePrecisionPerfRatio; /**< Ratio of single precision performance (in floating-point operations per second) to double precision performance */
int pageableMemoryAccess; /**< Device supports coherently accessing pageable memory without calling cudaHostRegister on it */
int concurrentManagedAccess; /**< Device can coherently access managed memory concurrently with the CPU */
int computePreemptionSupported; /**< Device supports Compute Preemption */
int canUseHostPointerForRegisteredMem; /**< Device can access host registered memory at the same virtual address as the CPU */
int cooperativeLaunch; /**< Device supports launching cooperative kernels via ::cudaLaunchCooperativeKernel */
int cooperativeMultiDeviceLaunch; /**< Deprecated, cudaLaunchCooperativeKernelMultiDevice is deprecated. */
size_t sharedMemPerBlockOptin; /**< Per device maximum shared memory per block usable by special opt in */
int pageableMemoryAccessUsesHostPageTables; /**< Device accesses pageable memory via the host's page tables */
int directManagedMemAccessFromHost; /**< Host can directly access managed memory on the device without migration. */
int maxBlocksPerMultiProcessor; /**< Maximum number of resident blocks per multiprocessor */
int accessPolicyMaxWindowSize; /**< The maximum value of ::cudaAccessPolicyWindow::num_bytes. */
size_t reservedSharedMemPerBlock; /**< Shared memory reserved by CUDA driver per block in bytes */
} cudaDeviceProp_t;
typedef struct cudart_handle {
void *handle;
uint16_t verbose;
cudartReturn_t (*cudaSetDevice)(int device);
cudartReturn_t (*cudaDeviceSynchronize)(void);
cudartReturn_t (*cudaDeviceReset)(void);
cudartReturn_t (*cudaMemGetInfo)(size_t *, size_t *);
cudartReturn_t (*cudaGetDeviceCount)(int *);
cudartReturn_t (*cudaDeviceGetAttribute)(int* value, cudartDeviceAttr_t attr, int device);
cudartReturn_t (*cudaDriverGetVersion) (int *driverVersion);
cudartReturn_t (*cudaGetDeviceProperties) (cudaDeviceProp_t* prop, int device);
} cudart_handle_t;
typedef struct cudart_init_resp {
char *err; // If err is non-null handle is invalid
cudart_handle_t ch;
int num_devices;
} cudart_init_resp_t;
void cudart_init(char *cudart_lib_path, cudart_init_resp_t *resp);
void cudart_bootstrap(cudart_handle_t ch, int device_id, mem_info_t *resp);
// TODO - if we keep this library longer term, add cudart_get_free
void cudart_release(cudart_handle_t ch);
#endif // __GPU_INFO_CUDART_H__
#endif // __APPLE__
ollama/gpu/gpu_info_darwin.h deleted 100644 → 0
View file @ 28e95ed5
#import <Metal/Metal.h>
#include <stdint.h>
uint64_t getRecommendedMaxVRAM();
uint64_t getPhysicalMemory();
uint64_t getFreeMemory();
ollama/gpu/gpu_info_darwin.m deleted 100644 → 0
View file @ 28e95ed5
#import <Foundation/Foundation.h>
#import <mach/mach.h>
#include "gpu_info_darwin.h"
uint64_t getRecommendedMaxVRAM() {
id<MTLDevice> device = MTLCreateSystemDefaultDevice();
uint64_t result = device.recommendedMaxWorkingSetSize;
CFRelease(device);
return result;
}
// getPhysicalMemory returns the total physical memory in bytes
uint64_t getPhysicalMemory() {
return [NSProcessInfo processInfo].physicalMemory;
}
// getFreeMemory returns the total free memory in bytes, including inactive
// memory that can be reclaimed by the system.
uint64_t getFreeMemory() {
mach_port_t host_port = mach_host_self();
mach_msg_type_number_t host_size = sizeof(vm_statistics64_data_t) / sizeof(integer_t);
vm_size_t pagesize;
vm_statistics64_data_t vm_stat;
host_page_size(host_port, &pagesize);
if (host_statistics64(host_port, HOST_VM_INFO64, (host_info64_t)&vm_stat, &host_size) != KERN_SUCCESS) {
return 0;
}
uint64_t free_memory = (uint64_t)vm_stat.free_count * pagesize;
free_memory += (uint64_t)vm_stat.speculative_count * pagesize;
free_memory += (uint64_t)vm_stat.inactive_count * pagesize;
return free_memory;
}
ollama/gpu/gpu_info_nvcuda.c deleted 100644 → 0
View file @ 28e95ed5
#ifndef __APPLE__ // TODO - maybe consider nvidia support on intel macs?
#include <string.h>
#include "gpu_info_nvcuda.h"
void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp) {
CUresult ret;
resp->err = NULL;
resp->num_devices = 0;
resp->cudaErr = CUDA_SUCCESS;
const int buflen = 256;
char buf[buflen + 1];
int i;
struct lookup {
char *s;
void **p;
} l[] = {
{"cuInit", (void *)&resp->ch.cuInit},
{"cuDriverGetVersion", (void *)&resp->ch.cuDriverGetVersion},
{"cuDeviceGetCount", (void *)&resp->ch.cuDeviceGetCount},
{"cuDeviceGet", (void *)&resp->ch.cuDeviceGet},
{"cuDeviceGetAttribute", (void *)&resp->ch.cuDeviceGetAttribute},
{"cuDeviceGetUuid", (void *)&resp->ch.cuDeviceGetUuid},
{"cuDeviceGetName", (void *)&resp->ch.cuDeviceGetName},
{"cuCtxCreate_v3", (void *)&resp->ch.cuCtxCreate_v3},
{"cuMemGetInfo_v2", (void *)&resp->ch.cuMemGetInfo_v2},
{"cuCtxDestroy", (void *)&resp->ch.cuCtxDestroy},
{NULL, NULL},
};
resp->ch.handle = LOAD_LIBRARY(nvcuda_lib_path, RTLD_LAZY);
if (!resp->ch.handle) {
char *msg = LOAD_ERR();
LOG(resp->ch.verbose, "library %s load err: %s\n", nvcuda_lib_path, msg);
snprintf(buf, buflen,
"Unable to load %s library to query for Nvidia GPUs: %s",
nvcuda_lib_path, msg);
free(msg);
resp->err = strdup(buf);
resp->cudaErr = -1;
return;
}
for (i = 0; l[i].s != NULL; i++) {
*l[i].p = LOAD_SYMBOL(resp->ch.handle, l[i].s);
if (!*(l[i].p)) {
char *msg = LOAD_ERR();
LOG(resp->ch.verbose, "dlerr: %s\n", msg);
UNLOAD_LIBRARY(resp->ch.handle);
resp->ch.handle = NULL;
snprintf(buf, buflen, "symbol lookup for %s failed: %s", l[i].s,
msg);
free(msg);
resp->err = strdup(buf);
resp->cudaErr = -1;
return;
}
}
ret = (*resp->ch.cuInit)(0);
if (ret != CUDA_SUCCESS) {
LOG(resp->ch.verbose, "cuInit err: %d\n", ret);
UNLOAD_LIBRARY(resp->ch.handle);
resp->ch.handle = NULL;
snprintf(buf, buflen, "cuda driver library init failure: %d", ret);
resp->err = strdup(buf);
resp->cudaErr = ret;
return;
}
int version = 0;
resp->ch.driver_major = 0;
resp->ch.driver_minor = 0;
// Report driver version if we're in verbose mode, ignore errors
ret = (*resp->ch.cuDriverGetVersion)(&version);
if (ret != CUDA_SUCCESS) {
LOG(resp->ch.verbose, "cuDriverGetVersion failed: %d\n", ret);
} else {
resp->ch.driver_major = version / 1000;
resp->ch.driver_minor = (version - (resp->ch.driver_major * 1000)) / 10;
LOG(resp->ch.verbose, "CUDA driver version: %d.%d\n", resp->ch.driver_major, resp->ch.driver_minor);
}
ret = (*resp->ch.cuDeviceGetCount)(&resp->num_devices);
if (ret != CUDA_SUCCESS) {
LOG(resp->ch.verbose, "cuDeviceGetCount err: %d\n", ret);
UNLOAD_LIBRARY(resp->ch.handle);
resp->ch.handle = NULL;
snprintf(buf, buflen, "unable to get device count: %d", ret);
resp->err = strdup(buf);
resp->cudaErr = ret;
return;
}
}
const int buflen = 256;
void nvcuda_bootstrap(nvcuda_handle_t h, int i, mem_info_t *resp) {
resp->err = NULL;
nvcudaMemory_t memInfo = {0,0};
CUresult ret;
CUdevice device = -1;
CUcontext ctx = NULL;
char buf[buflen + 1];
CUuuid uuid = {0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0};
if (h.handle == NULL) {
resp->err = strdup("cuda driver library handle isn't initialized");
return;
}
ret = (*h.cuDeviceGet)(&device, i);
if (ret != CUDA_SUCCESS) {
snprintf(buf, buflen, "cuda driver library device failed to initialize");
resp->err = strdup(buf);
return;
}
int major = 0;
int minor = 0;
ret = (*h.cuDeviceGetAttribute)(&major, CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MAJOR, device);
if (ret != CUDA_SUCCESS) {
LOG(h.verbose, "[%d] device major lookup failure: %d\n", i, ret);
} else {
ret = (*h.cuDeviceGetAttribute)(&minor, CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MINOR, device);
if (ret != CUDA_SUCCESS) {
LOG(h.verbose, "[%d] device minor lookup failure: %d\n", i, ret);
} else {
resp->minor = minor;
resp->major = major;
}
}
ret = (*h.cuDeviceGetUuid)(&uuid, device);
if (ret != CUDA_SUCCESS) {
LOG(h.verbose, "[%d] device uuid lookup failure: %d\n", i, ret);
snprintf(&resp->gpu_id[0], GPU_ID_LEN, "%d", i);
} else {
// GPU-d110a105-ac29-1d54-7b49-9c90440f215b
snprintf(&resp->gpu_id[0], GPU_ID_LEN,
"GPU-%02x%02x%02x%02x-%02x%02x-%02x%02x-%02x%02x-%02x%02x%02x%02x%02x%02x",
uuid.bytes[0],
uuid.bytes[1],
uuid.bytes[2],
uuid.bytes[3],
uuid.bytes[4],
uuid.bytes[5],
uuid.bytes[6],
uuid.bytes[7],
uuid.bytes[8],
uuid.bytes[9],
uuid.bytes[10],
uuid.bytes[11],
uuid.bytes[12],
uuid.bytes[13],
uuid.bytes[14],
uuid.bytes[15]
);
}
ret = (*h.cuDeviceGetName)(&resp->gpu_name[0], GPU_NAME_LEN, device);
if (ret != CUDA_SUCCESS) {
LOG(h.verbose, "[%d] device name lookup failure: %d\n", i, ret);
resp->gpu_name[0] = '\0';
}
// To get memory we have to set (and release) a context
ret = (*h.cuCtxCreate_v3)(&ctx, NULL, 0, 0, device);
if (ret != CUDA_SUCCESS) {
snprintf(buf, buflen, "cuda driver library failed to get device context %d", ret);
resp->err = strdup(buf);
return;
}
ret = (*h.cuMemGetInfo_v2)(&memInfo.free, &memInfo.total);
if (ret != CUDA_SUCCESS) {
snprintf(buf, buflen, "cuda driver library device memory info lookup failure %d", ret);
resp->err = strdup(buf);
// Best effort on failure...
(*h.cuCtxDestroy)(ctx);
return;
}
resp->total = memInfo.total;
resp->free = memInfo.free;
LOG(h.verbose, "[%s] CUDA totalMem %lu mb\n", resp->gpu_id, resp->total / 1024 / 1024);
LOG(h.verbose, "[%s] CUDA freeMem %lu mb\n", resp->gpu_id, resp->free / 1024 / 1024);
LOG(h.verbose, "[%s] Compute Capability %d.%d\n", resp->gpu_id, resp->major, resp->minor);
ret = (*h.cuCtxDestroy)(ctx);
if (ret != CUDA_SUCCESS) {
LOG(1, "cuda driver library failed to release device context %d", ret);
}
}
void nvcuda_get_free(nvcuda_handle_t h, int i, uint64_t *free, uint64_t *total) {
CUresult ret;
CUcontext ctx = NULL;
CUdevice device = -1;
*free = 0;
*total = 0;
ret = (*h.cuDeviceGet)(&device, i);
if (ret != CUDA_SUCCESS) {
LOG(1, "cuda driver library device failed to initialize");
return;
}
// To get memory we have to set (and release) a context
ret = (*h.cuCtxCreate_v3)(&ctx, NULL, 0, 0, device);
if (ret != CUDA_SUCCESS) {
LOG(1, "cuda driver library failed to get device context %d", ret);
return;
}
ret = (*h.cuMemGetInfo_v2)(free, total);
if (ret != CUDA_SUCCESS) {
LOG(1, "cuda driver library device memory info lookup failure %d", ret);
// Best effort on failure...
(*h.cuCtxDestroy)(ctx);
return;
}
ret = (*h.cuCtxDestroy)(ctx);
if (ret != CUDA_SUCCESS) {
LOG(1, "cuda driver library failed to release device context %d", ret);
}
}
void nvcuda_release(nvcuda_handle_t h) {
LOG(h.verbose, "releasing cuda driver library\n");
UNLOAD_LIBRARY(h.handle);
// TODO and other context release logic?
h.handle = NULL;
}
#endif // __APPLE__
\ No newline at end of file
ollama/gpu/gpu_info_nvcuda.h deleted 100644 → 0
View file @ 28e95ed5
#ifndef __APPLE__
#ifndef __GPU_INFO_NVCUDA_H__
#define __GPU_INFO_NVCUDA_H__
#include "gpu_info.h"
// Just enough typedef's to dlopen/dlsym for memory information
typedef enum cudaError_enum {
CUDA_SUCCESS = 0,
CUDA_ERROR_INVALID_VALUE = 1,
CUDA_ERROR_OUT_OF_MEMORY = 2,
CUDA_ERROR_NOT_INITIALIZED = 3,
CUDA_ERROR_INSUFFICIENT_DRIVER = 35,
CUDA_ERROR_NO_DEVICE = 100,
CUDA_ERROR_SYSTEM_DRIVER_MISMATCH = 803,
CUDA_ERROR_UNKNOWN = 999,
// Other values omitted for now...
} CUresult;
typedef enum CUdevice_attribute_enum {
CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MAJOR = 75,
CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MINOR = 76,
// TODO - not yet wired up but may be useful for Jetson or other
// integrated GPU scenarios with shared memory
CU_DEVICE_ATTRIBUTE_INTEGRATED = 18
} CUdevice_attribute;
typedef void *nvcudaDevice_t; // Opaque is sufficient
typedef struct nvcudaMemory_st {
uint64_t total;
uint64_t free;
} nvcudaMemory_t;
typedef struct nvcudaDriverVersion {
int major;
int minor;
} nvcudaDriverVersion_t;
typedef struct CUuuid_st {
unsigned char bytes[16];
} CUuuid;
typedef int CUdevice;
typedef void* CUcontext;
typedef struct nvcuda_handle {
void *handle;
uint16_t verbose;
int driver_major;
int driver_minor;
CUresult (*cuInit)(unsigned int Flags);
CUresult (*cuDriverGetVersion)(int *driverVersion);
CUresult (*cuDeviceGetCount)(int *);
CUresult (*cuDeviceGet)(CUdevice* device, int ordinal);
CUresult (*cuDeviceGetAttribute)(int* pi, CUdevice_attribute attrib, CUdevice dev);
CUresult (*cuDeviceGetUuid)(CUuuid* uuid, CUdevice dev); // signature compatible with cuDeviceGetUuid_v2
CUresult (*cuDeviceGetName)(char *name, int len, CUdevice dev);
// Context specific aspects
CUresult (*cuCtxCreate_v3)(CUcontext* pctx, void *params, int len, unsigned int flags, CUdevice dev);
CUresult (*cuMemGetInfo_v2)(uint64_t* free, uint64_t* total);
CUresult (*cuCtxDestroy)(CUcontext ctx);
} nvcuda_handle_t;
typedef struct nvcuda_init_resp {
char *err; // If err is non-null handle is invalid
nvcuda_handle_t ch;
int num_devices;
CUresult cudaErr;
} nvcuda_init_resp_t;
void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp);
void nvcuda_bootstrap(nvcuda_handle_t ch, int device_id, mem_info_t *resp);
void nvcuda_get_free(nvcuda_handle_t ch, int device_id, uint64_t *free, uint64_t *total);
void nvcuda_release(nvcuda_handle_t ch);
#endif // __GPU_INFO_NVCUDA_H__
#endif // __APPLE__
ollama/gpu/gpu_info_nvml.c deleted 100644 → 0
View file @ 28e95ed5
#ifndef __APPLE__ // TODO - maybe consider nvidia support on intel macs?
#include <string.h>
#include "gpu_info_nvml.h"
void nvml_init(char *nvml_lib_path, nvml_init_resp_t *resp) {
nvmlReturn_t ret;
resp->err = NULL;
const int buflen = 256;
char buf[buflen + 1];
int i;
struct lookup {
char *s;
void **p;
} l[] = {
{"nvmlInit_v2", (void *)&resp->ch.nvmlInit_v2},
{"nvmlShutdown", (void *)&resp->ch.nvmlShutdown},
{"nvmlDeviceGetHandleByIndex", (void *)&resp->ch.nvmlDeviceGetHandleByIndex},
{"nvmlDeviceGetMemoryInfo", (void *)&resp->ch.nvmlDeviceGetMemoryInfo},
{NULL, NULL},
};
resp->ch.handle = LOAD_LIBRARY(nvml_lib_path, RTLD_LAZY);
if (!resp->ch.handle) {
char *msg = LOAD_ERR();
LOG(resp->ch.verbose, "library %s load err: %s\n", nvml_lib_path, msg);
snprintf(buf, buflen,
"Unable to load %s library to query for Nvidia GPUs: %s",
nvml_lib_path, msg);
free(msg);
resp->err = strdup(buf);
return;
}
// TODO once we've squashed the remaining corner cases remove this log
// LOG(resp->ch.verbose, "wiring nvidia management library functions in %s\n", nvml_lib_path);
for (i = 0; l[i].s != NULL; i++) {
// TODO once we've squashed the remaining corner cases remove this log
// LOG(resp->ch.verbose, "dlsym: %s\n", l[i].s);
*l[i].p = LOAD_SYMBOL(resp->ch.handle, l[i].s);
if (!*(l[i].p)) {
resp->ch.handle = NULL;
char *msg = LOAD_ERR();
LOG(resp->ch.verbose, "dlerr: %s\n", msg);
UNLOAD_LIBRARY(resp->ch.handle);
snprintf(buf, buflen, "symbol lookup for %s failed: %s", l[i].s,
msg);
free(msg);
resp->err = strdup(buf);
return;
}
}
ret = (*resp->ch.nvmlInit_v2)();
if (ret != NVML_SUCCESS) {
LOG(resp->ch.verbose, "nvmlInit_v2 err: %d\n", ret);
UNLOAD_LIBRARY(resp->ch.handle);
resp->ch.handle = NULL;
snprintf(buf, buflen, "nvml vram init failure: %d", ret);
resp->err = strdup(buf);
return;
}
}
void nvml_get_free(nvml_handle_t h, int device_id, uint64_t *free, uint64_t *total, uint64_t *used) {
nvmlDevice_t device;
nvmlMemory_t memInfo = {0};
nvmlReturn_t ret;
ret = (*h.nvmlDeviceGetHandleByIndex)(device_id, &device);
if (ret != NVML_SUCCESS) {
LOG(1, "unable to get device handle %d: %d", device_id, ret);
*free = 0;
return;
}
ret = (*h.nvmlDeviceGetMemoryInfo)(device, &memInfo);
if (ret != NVML_SUCCESS) {
LOG(1, "device memory info lookup failure %d: %d", device_id, ret);
*free = 0;
return;
}
*free = memInfo.free;
*total = memInfo.total;
*used = memInfo.used;
}
void nvml_release(nvml_handle_t h) {
LOG(h.verbose, "releasing nvml library\n");
nvmlReturn_t ret;
ret = (*h.nvmlShutdown)();
if (ret != NVML_SUCCESS) {
LOG(1, "error during nvmlShutdown %d", ret);
}
UNLOAD_LIBRARY(h.handle);
h.handle = NULL;
}
#endif // __APPLE__
\ No newline at end of file
ollama/gpu/gpu_info_nvml.h deleted 100644 → 0
View file @ 28e95ed5
#ifndef __APPLE__
#ifndef __GPU_INFO_NVML_H__
#define __GPU_INFO_NVML_H__
#include "gpu_info.h"
// Just enough typedef's to dlopen/dlsym for memory information
typedef enum nvmlReturn_enum {
NVML_SUCCESS = 0,
// Other values omitted for now...
} nvmlReturn_t;
typedef void *nvmlDevice_t; // Opaque is sufficient
typedef struct nvmlMemory_st {
unsigned long long total;
unsigned long long free;
unsigned long long used;
} nvmlMemory_t;
typedef enum nvmlBrandType_enum
{
NVML_BRAND_UNKNOWN = 0,
} nvmlBrandType_t;
typedef struct nvml_handle {
void *handle;
uint16_t verbose;
nvmlReturn_t (*nvmlInit_v2)(void);
nvmlReturn_t (*nvmlShutdown)(void);
nvmlReturn_t (*nvmlDeviceGetHandleByIndex)(unsigned int, nvmlDevice_t *);
nvmlReturn_t (*nvmlDeviceGetMemoryInfo)(nvmlDevice_t, nvmlMemory_t *);
} nvml_handle_t;
typedef struct nvml_init_resp {
char *err; // If err is non-null handle is invalid
nvml_handle_t ch;
} nvml_init_resp_t;
typedef struct nvml_compute_capability {
char *err;
int major;
int minor;
} nvml_compute_capability_t;
void nvml_init(char *nvml_lib_path, nvml_init_resp_t *resp);
void nvml_get_free(nvml_handle_t ch, int device_id, uint64_t *free, uint64_t *total, uint64_t *used);
void nvml_release(nvml_handle_t ch);
#endif // __GPU_INFO_NVML_H__
#endif // __APPLE__
\ No newline at end of file
ollama/gpu/gpu_info_oneapi.c deleted 100644 → 0
View file @ 28e95ed5
#ifndef __APPLE__
#include "gpu_info_oneapi.h"
#include <string.h>
void oneapi_init(char *oneapi_lib_path, oneapi_init_resp_t *resp) {
ze_result_t ret;
resp->err = NULL;
resp->oh.devices = NULL;
resp->oh.num_devices = NULL;
resp->oh.drivers = NULL;
resp->oh.num_drivers = 0;
const int buflen = 256;
char buf[buflen + 1];
int i, d;
struct lookup {
char *s;
void **p;
} l[] = {
{"zesInit", (void *)&resp->oh.zesInit},
{"zesDriverGet", (void *)&resp->oh.zesDriverGet},
{"zesDeviceGet", (void *)&resp->oh.zesDeviceGet},
{"zesDeviceGetProperties", (void *)&resp->oh.zesDeviceGetProperties},
{"zesDeviceEnumMemoryModules",
(void *)&resp->oh.zesDeviceEnumMemoryModules},
{"zesMemoryGetProperties", (void *)&resp->oh.zesMemoryGetProperties},
{"zesMemoryGetState", (void *)&resp->oh.zesMemoryGetState},
{NULL, NULL},
};
resp->oh.handle = LOAD_LIBRARY(oneapi_lib_path, RTLD_LAZY);
if (!resp->oh.handle) {
char *msg = LOAD_ERR();
snprintf(buf, buflen,
"Unable to load %s library to query for Intel GPUs: %s\n",
oneapi_lib_path, msg);
free(msg);
resp->err = strdup(buf);
return;
}
// TODO once we've squashed the remaining corner cases remove this log
LOG(resp->oh.verbose,
"wiring Level-Zero management library functions in %s\n",
oneapi_lib_path);
for (i = 0; l[i].s != NULL; i++) {
// TODO once we've squashed the remaining corner cases remove this log
LOG(resp->oh.verbose, "dlsym: %s\n", l[i].s);
*l[i].p = LOAD_SYMBOL(resp->oh.handle, l[i].s);
if (!*(l[i].p)) {
resp->oh.handle = NULL;
char *msg = LOAD_ERR();
LOG(resp->oh.verbose, "dlerr: %s\n", msg);
UNLOAD_LIBRARY(resp->oh.handle);
snprintf(buf, buflen, "symbol lookup for %s failed: %s", l[i].s, msg);
free(msg);
resp->err = strdup(buf);
return;
}
}
LOG(resp->oh.verbose, "calling zesInit\n");
ret = (*resp->oh.zesInit)(0);
if (ret != ZE_RESULT_SUCCESS) {
LOG(resp->oh.verbose, "zesInit err: %x\n", ret);
snprintf(buf, buflen, "oneapi vram init failure: %x", ret);
resp->err = strdup(buf);
oneapi_release(resp->oh);
return;
}
LOG(resp->oh.verbose, "calling zesDriverGet\n");
ret = (*resp->oh.zesDriverGet)(&resp->oh.num_drivers, NULL);
if (ret != ZE_RESULT_SUCCESS) {
LOG(resp->oh.verbose, "zesDriverGet err: %x\n", ret);
snprintf(buf, buflen, "unable to get driver count: %x", ret);
resp->err = strdup(buf);
oneapi_release(resp->oh);
return;
}
LOG(resp->oh.verbose, "oneapi driver count: %d\n", resp->oh.num_drivers);
resp->oh.drivers = malloc(resp->oh.num_drivers * sizeof(zes_driver_handle_t));
resp->oh.num_devices = malloc(resp->oh.num_drivers * sizeof(uint32_t));
memset(&resp->oh.num_devices[0], 0, resp->oh.num_drivers * sizeof(uint32_t));
resp->oh.devices =
malloc(resp->oh.num_drivers * sizeof(zes_device_handle_t *));
ret = (*resp->oh.zesDriverGet)(&resp->oh.num_drivers, &resp->oh.drivers[0]);
if (ret != ZE_RESULT_SUCCESS) {
LOG(resp->oh.verbose, "zesDriverGet err: %x\n", ret);
snprintf(buf, buflen, "unable to get driver count: %x", ret);
resp->err = strdup(buf);
oneapi_release(resp->oh);
return;
}
for (d = 0; d < resp->oh.num_drivers; d++) {
LOG(resp->oh.verbose, "calling zesDeviceGet count %d: %p\n", d, resp->oh.drivers[d]);
ret = (*resp->oh.zesDeviceGet)(resp->oh.drivers[d],
&resp->oh.num_devices[d], NULL);
if (ret != ZE_RESULT_SUCCESS) {
LOG(resp->oh.verbose, "zesDeviceGet err: %x\n", ret);
snprintf(buf, buflen, "unable to get device count: %x", ret);
resp->err = strdup(buf);
oneapi_release(resp->oh);
return;
}
resp->oh.devices[d] =
malloc(resp->oh.num_devices[d] * sizeof(zes_device_handle_t));
ret = (*resp->oh.zesDeviceGet)(
resp->oh.drivers[d], &resp->oh.num_devices[d], resp->oh.devices[d]);
if (ret != ZE_RESULT_SUCCESS) {
LOG(resp->oh.verbose, "zesDeviceGet err: %x\n", ret);
snprintf(buf, buflen, "unable to get device count: %x", ret);
resp->err = strdup(buf);
oneapi_release(resp->oh);
return;
}
}
return;
}
void oneapi_check_vram(oneapi_handle_t h, int driver, int device,
mem_info_t *resp) {
ze_result_t ret;
resp->err = NULL;
uint64_t totalMem = 0;
uint64_t usedMem = 0;
const int buflen = 256;
char buf[buflen + 1];
int i, d, m;
if (h.handle == NULL) {
resp->err = strdup("Level-Zero handle not initialized");
return;
}
if (driver > h.num_drivers || device > h.num_devices[driver]) {
resp->err = strdup("driver of device index out of bounds");
return;
}
resp->total = 0;
resp->free = 0;
zes_device_ext_properties_t ext_props;
ext_props.stype = ZES_STRUCTURE_TYPE_DEVICE_EXT_PROPERTIES;
ext_props.pNext = NULL;
zes_device_properties_t props;
props.stype = ZES_STRUCTURE_TYPE_DEVICE_PROPERTIES;
props.pNext = &ext_props;
ret = (*h.zesDeviceGetProperties)(h.devices[driver][device], &props);
if (ret != ZE_RESULT_SUCCESS) {
snprintf(buf, buflen, "unable to get device properties: %d", ret);
resp->err = strdup(buf);
return;
}
snprintf(&resp->gpu_name[0], GPU_NAME_LEN, "%s", props.modelName);
// TODO this needs to map to ONEAPI_DEVICE_SELECTOR syntax
// (this is probably wrong...)
// TODO - the driver isn't included - what if there are multiple drivers?
snprintf(&resp->gpu_id[0], GPU_ID_LEN, "%d", device);
if (h.verbose) {
// When in verbose mode, report more information about
// the card we discover.
LOG(h.verbose, "[%d:%d] oneAPI device name: %s\n", driver, device,
props.modelName);
LOG(h.verbose, "[%d:%d] oneAPI brand: %s\n", driver, device,
props.brandName);
LOG(h.verbose, "[%d:%d] oneAPI vendor: %s\n", driver, device,
props.vendorName);
LOG(h.verbose, "[%d:%d] oneAPI S/N: %s\n", driver, device,
props.serialNumber);
LOG(h.verbose, "[%d:%d] oneAPI board number: %s\n", driver, device,
props.boardNumber);
}
// TODO
// Compute Capability equivalent in resp->major, resp->minor, resp->patch
uint32_t memCount = 0;
ret = (*h.zesDeviceEnumMemoryModules)(h.devices[driver][device], &memCount,
NULL);
if (ret != ZE_RESULT_SUCCESS) {
snprintf(buf, buflen, "unable to enumerate Level-Zero memory modules: %x",
ret);
resp->err = strdup(buf);
return;
}
LOG(h.verbose, "discovered %d Level-Zero memory modules\n", memCount);
zes_mem_handle_t *mems = malloc(memCount * sizeof(zes_mem_handle_t));
(*h.zesDeviceEnumMemoryModules)(h.devices[driver][device], &memCount, mems);
for (m = 0; m < memCount; m++) {
zes_mem_state_t state;
state.stype = ZES_STRUCTURE_TYPE_MEM_STATE;
state.pNext = NULL;
ret = (*h.zesMemoryGetState)(mems[m], &state);
if (ret != ZE_RESULT_SUCCESS) {
snprintf(buf, buflen, "unable to get memory state: %x", ret);
resp->err = strdup(buf);
free(mems);
return;
}
resp->total += state.size;
resp->free += state.free;
}
free(mems);
}
void oneapi_release(oneapi_handle_t h) {
int d;
LOG(h.verbose, "releasing oneapi library\n");
for (d = 0; d < h.num_drivers; d++) {
if (h.devices != NULL && h.devices[d] != NULL) {
free(h.devices[d]);
}
}
if (h.devices != NULL) {
free(h.devices);
h.devices = NULL;
}
if (h.num_devices != NULL) {
free(h.num_devices);
h.num_devices = NULL;
}
if (h.drivers != NULL) {
free(h.drivers);
h.drivers = NULL;
}
h.num_drivers = 0;
UNLOAD_LIBRARY(h.handle);
h.handle = NULL;
}
int oneapi_get_device_count(oneapi_handle_t h, int driver) {
if (h.handle == NULL || h.num_devices == NULL) {
return 0;
}
if (driver > h.num_drivers) {
return 0;
}
return (int)h.num_devices[driver];
}
#endif // __APPLE__
ollama/gpu/gpu_info_oneapi.h deleted 100644 → 0
View file @ 28e95ed5
#ifndef __APPLE__
#ifndef __GPU_INFO_ONEAPI_H__
#define __GPU_INFO_ONEAPI_H__
#include "gpu_info.h"
#define ZE_MAX_DEVICE_NAME 256
#define ZE_MAX_DEVICE_UUID_SIZE 16
#define ZES_STRING_PROPERTY_SIZE 64
#define ZE_BIT(_i) (1 << _i)
// Just enough typedef's to dlopen/dlsym for memory information
typedef enum ze_result_t {
ZE_RESULT_SUCCESS = 0,
// Other values omitted for now...
} ze_result_t;
typedef uint8_t ze_bool_t;
typedef struct _zes_driver_handle_t *zes_driver_handle_t;
typedef struct _zes_device_handle_t *zes_device_handle_t;
typedef struct _zes_mem_handle_t *zes_mem_handle_t;
typedef enum _ze_structure_type_t {
ZE_STRUCTURE_TYPE_FORCE_UINT32 = 0x7fffffff
} ze_structure_type_t;
typedef enum _zes_structure_type_t {
ZES_STRUCTURE_TYPE_DEVICE_PROPERTIES = 0x1,
ZES_STRUCTURE_TYPE_MEM_PROPERTIES = 0xb,
ZES_STRUCTURE_TYPE_MEM_STATE = 0x1e,
ZES_STRUCTURE_TYPE_DEVICE_EXT_PROPERTIES = 0x2d,
ZES_STRUCTURE_TYPE_FORCE_UINT32 = 0x7fffffff
} zes_structure_type_t;
typedef enum _zes_mem_type_t {
ZES_MEM_TYPE_FORCE_UINT32 = 0x7fffffff
} zes_mem_type_t;
typedef enum _zes_mem_loc_t {
ZES_MEM_LOC_SYSTEM = 0,
ZES_MEM_LOC_DEVICE = 1,
ZES_MEM_LOC_FORCE_UINT32 = 0x7fffffff
} zes_mem_loc_t;
typedef enum _zes_mem_health_t {
ZES_MEM_HEALTH_FORCE_UINT32 = 0x7fffffff
} zes_mem_health_t;
typedef struct _ze_device_uuid_t {
uint8_t id[ZE_MAX_DEVICE_UUID_SIZE];
} ze_device_uuid_t;
typedef struct _zes_uuid_t {
uint8_t id[ZE_MAX_DEVICE_UUID_SIZE];
} zes_uuid_t;
typedef enum _ze_device_type_t {
ZE_DEVICE_TYPE_GPU = 1,
ZE_DEVICE_TYPE_CPU = 2,
ZE_DEVICE_TYPE_FPGA = 3,
ZE_DEVICE_TYPE_MCA = 4,
ZE_DEVICE_TYPE_VPU = 5,
ZE_DEVICE_TYPE_FORCE_UINT32 = 0x7fffffff
} ze_device_type_t;
typedef enum _zes_device_type_t {
ZES_DEVICE_TYPE_GPU = 1,
ZES_DEVICE_TYPE_CPU = 2,
ZES_DEVICE_TYPE_FPGA = 3,
ZES_DEVICE_TYPE_MCA = 4,
ZES_DEVICE_TYPE_VPU = 5,
ZES_DEVICE_TYPE_FORCE_UINT32 = 0x7fffffff
} zes_device_type_t;
typedef uint32_t ze_device_property_flags_t;
typedef enum _ze_device_property_flag_t {
ZE_DEVICE_PROPERTY_FLAG_INTEGRATED = ZE_BIT(0),
ZE_DEVICE_PROPERTY_FLAG_SUBDEVICE = ZE_BIT(1),
ZE_DEVICE_PROPERTY_FLAG_ECC = ZE_BIT(2),
ZE_DEVICE_PROPERTY_FLAG_ONDEMANDPAGING = ZE_BIT(3),
ZE_DEVICE_PROPERTY_FLAG_FORCE_UINT32 = 0x7fffffff
} ze_device_property_flag_t;
typedef uint32_t zes_device_property_flags_t;
typedef enum _zes_device_property_flag_t {
ZES_DEVICE_PROPERTY_FLAG_INTEGRATED = ZE_BIT(0),
ZES_DEVICE_PROPERTY_FLAG_SUBDEVICE = ZE_BIT(1),
ZES_DEVICE_PROPERTY_FLAG_ECC = ZE_BIT(2),
ZES_DEVICE_PROPERTY_FLAG_ONDEMANDPAGING = ZE_BIT(3),
ZES_DEVICE_PROPERTY_FLAG_FORCE_UINT32 = 0x7fffffff
} zes_device_property_flag_t;
typedef struct _ze_device_properties_t {
ze_structure_type_t stype;
void *pNext;
ze_device_type_t type;
uint32_t vendorId;
uint32_t deviceId;
ze_device_property_flags_t flags;
uint32_t subdeviceId;
uint32_t coreClockRate;
uint64_t maxMemAllocSize;
uint32_t maxHardwareContexts;
uint32_t maxCommandQueuePriority;
uint32_t numThreadsPerEU;
uint32_t physicalEUSimdWidth;
uint32_t numEUsPerSubslice;
uint32_t numSubslicesPerSlice;
uint32_t numSlices;
uint64_t timerResolution;
uint32_t timestampValidBits;
uint32_t kernelTimestampValidBits;
ze_device_uuid_t uuid;
char name[ZE_MAX_DEVICE_NAME];
} ze_device_properties_t;
typedef struct _zes_device_properties_t {
zes_structure_type_t stype;
void *pNext;
ze_device_properties_t core;
uint32_t numSubdevices;
char serialNumber[ZES_STRING_PROPERTY_SIZE];
char boardNumber[ZES_STRING_PROPERTY_SIZE];
char brandName[ZES_STRING_PROPERTY_SIZE];
char modelName[ZES_STRING_PROPERTY_SIZE];
char vendorName[ZES_STRING_PROPERTY_SIZE];
char driverVersion[ZES_STRING_PROPERTY_SIZE];
} zes_device_properties_t;
typedef struct _zes_device_ext_properties_t {
zes_structure_type_t stype;
void *pNext;
zes_uuid_t uuid;
zes_device_type_t type;
zes_device_property_flags_t flags;
} zes_device_ext_properties_t;
typedef struct _zes_mem_properties_t {
zes_structure_type_t stype;
void *pNext;
zes_mem_type_t type;
ze_bool_t onSubdevice;
uint32_t subdeviceId;
zes_mem_loc_t location;
uint64_t physicalSize;
int32_t busWidth;
int32_t numChannels;
} zes_mem_properties_t;
typedef struct _zes_mem_state_t {
zes_structure_type_t stype;
const void *pNext;
zes_mem_health_t health;
uint64_t free;
uint64_t size;
} zes_mem_state_t;
typedef struct oneapi_handle {
void *handle;
uint16_t verbose;
uint32_t num_drivers;
zes_driver_handle_t *drivers;
uint32_t *num_devices;
zes_device_handle_t **devices;
// TODO Driver major, minor information
// int driver_major;
// int driver_minor;
ze_result_t (*zesInit)(int);
ze_result_t (*zesDriverGet)(uint32_t *pCount, zes_driver_handle_t *phDrivers);
ze_result_t (*zesDeviceGet)(zes_driver_handle_t hDriver, uint32_t *pCount,
zes_device_handle_t *phDevices);
ze_result_t (*zesDeviceGetProperties)(zes_device_handle_t hDevice,
zes_device_properties_t *pProperties);
ze_result_t (*zesDeviceEnumMemoryModules)(zes_device_handle_t hDevice,
uint32_t *pCount,
zes_mem_handle_t *phMemory);
ze_result_t (*zesMemoryGetProperties)(zes_mem_handle_t hMemory,
zes_mem_properties_t *pProperties);
ze_result_t (*zesMemoryGetState)(zes_mem_handle_t hMemory,
zes_mem_state_t *pState);
} oneapi_handle_t;
typedef struct oneapi_init_resp {
char *err; // If err is non-null handle is invalid
oneapi_handle_t oh;
} oneapi_init_resp_t;
typedef struct oneapi_version_resp {
ze_result_t status;
char *str; // Contains version or error string if status != 0
} oneapi_version_resp_t;
void oneapi_init(char *oneapi_lib_path, oneapi_init_resp_t *resp);
void oneapi_check_vram(oneapi_handle_t h, int driver, int device,
mem_info_t *resp);
void oneapi_release(oneapi_handle_t h);
int oneapi_get_device_count(oneapi_handle_t h, int driver);
#endif // __GPU_INFO_INTEL_H__
#endif // __APPLE__
ollama/gpu/gpu_linux.go deleted 100644 → 0
View file @ 28e95ed5
package gpu
import (
"bufio"
"fmt"
"os"
"strings"
"github.com/ollama/ollama/format"
)
var CudartGlobs = []string{
"/usr/local/cuda/lib64/libcudart.so*",
"/usr/lib/x86_64-linux-gnu/nvidia/current/libcudart.so*",
"/usr/lib/x86_64-linux-gnu/libcudart.so*",
"/usr/lib/wsl/lib/libcudart.so*",
"/usr/lib/wsl/drivers/*/libcudart.so*",
"/opt/cuda/lib64/libcudart.so*",
"/usr/local/cuda*/targets/aarch64-linux/lib/libcudart.so*",
"/usr/lib/aarch64-linux-gnu/nvidia/current/libcudart.so*",
"/usr/lib/aarch64-linux-gnu/libcudart.so*",
"/usr/local/cuda/lib*/libcudart.so*",
"/usr/lib*/libcudart.so*",
"/usr/local/lib*/libcudart.so*",
}
var NvmlGlobs = []string{}
var NvcudaGlobs = []string{
"/usr/local/cuda*/targets/*/lib/libcuda.so*",
"/usr/lib/*-linux-gnu/nvidia/current/libcuda.so*",
"/usr/lib/*-linux-gnu/libcuda.so*",
"/usr/lib/wsl/lib/libcuda.so*",
"/usr/lib/wsl/drivers/*/libcuda.so*",
"/opt/cuda/lib*/libcuda.so*",
"/usr/local/cuda/lib*/libcuda.so*",
"/usr/lib*/libcuda.so*",
"/usr/local/lib*/libcuda.so*",
}
var OneapiGlobs = []string{
"/usr/lib/x86_64-linux-gnu/libze_intel_gpu.so*",
"/usr/lib*/libze_intel_gpu.so*",
}
var (
CudartMgmtName = "libcudart.so*"
NvcudaMgmtName = "libcuda.so*"
NvmlMgmtName = "" // not currently wired on linux
OneapiMgmtName = "libze_intel_gpu.so"
)
func GetCPUMem() (memInfo, error) {
var mem memInfo
var total, available, free, buffers, cached, freeSwap uint64
f, err := os.Open("/proc/meminfo")
if err != nil {
return mem, err
}
defer f.Close()
s := bufio.NewScanner(f)
for s.Scan() {
line := s.Text()
switch {
case strings.HasPrefix(line, "MemTotal:"):
_, err = fmt.Sscanf(line, "MemTotal:%d", &total)
case strings.HasPrefix(line, "MemAvailable:"):
_, err = fmt.Sscanf(line, "MemAvailable:%d", &available)
case strings.HasPrefix(line, "MemFree:"):
_, err = fmt.Sscanf(line, "MemFree:%d", &free)
case strings.HasPrefix(line, "Buffers:"):
_, err = fmt.Sscanf(line, "Buffers:%d", &buffers)
case strings.HasPrefix(line, "Cached:"):
_, err = fmt.Sscanf(line, "Cached:%d", &cached)
case strings.HasPrefix(line, "SwapFree:"):
_, err = fmt.Sscanf(line, "SwapFree:%d", &freeSwap)
default:
continue
}
if err != nil {
return mem, err
}
}
mem.TotalMemory = total * format.KibiByte
mem.FreeSwap = freeSwap * format.KibiByte
if available > 0 {
mem.FreeMemory = available * format.KibiByte
} else {
mem.FreeMemory = (free + buffers + cached) * format.KibiByte
}
return mem, nil
}
ollama/gpu/gpu_oneapi.go deleted 100644 → 0
View file @ 28e95ed5
//go:build linux || windows
package gpu
import (
"log/slog"
"strings"
)
func oneapiGetVisibleDevicesEnv(gpuInfo []GpuInfo) (string, string) {
ids := []string{}
for _, info := range gpuInfo {
if info.Library != "oneapi" {
// TODO shouldn't happen if things are wired correctly...
slog.Debug("oneapiGetVisibleDevicesEnv skipping over non-sycl device", "library", info.Library)
continue
}
ids = append(ids, info.ID)
}
return "ONEAPI_DEVICE_SELECTOR", "level_zero:" + strings.Join(ids, ",")
}
ollama/gpu/gpu_test.go deleted 100644 → 0
View file @ 28e95ed5
package gpu
import (
"runtime"
"testing"
"github.com/stretchr/testify/assert"
"github.com/stretchr/testify/require"
)
func TestBasicGetGPUInfo(t *testing.T) {
info := GetGPUInfo()
assert.NotEmpty(t, len(info))
assert.Contains(t, "cuda rocm cpu metal", info[0].Library)
if info[0].Library != "cpu" {
assert.Greater(t, info[0].TotalMemory, uint64(0))
assert.Greater(t, info[0].FreeMemory, uint64(0))
}
}
func TestCPUMemInfo(t *testing.T) {
info, err := GetCPUMem()
require.NoError(t, err)
switch runtime.GOOS {
case "darwin":
t.Skip("CPU memory not populated on darwin")
case "linux", "windows":
assert.Greater(t, info.TotalMemory, uint64(0))
assert.Greater(t, info.FreeMemory, uint64(0))
default:
return
}
}
// TODO - add some logic to figure out card type through other means and actually verify we got back what we expected
ollama/gpu/gpu_windows.go deleted 100644 → 0
View file @ 28e95ed5
package gpu
import (
"fmt"
"syscall"
"unsafe"
)
type MEMORYSTATUSEX struct {
length uint32
MemoryLoad uint32
TotalPhys uint64
AvailPhys uint64
TotalPageFile uint64
AvailPageFile uint64
TotalVirtual uint64
AvailVirtual uint64
AvailExtendedVirtual uint64
}
var (
k32 = syscall.NewLazyDLL("kernel32.dll")
globalMemoryStatusExProc = k32.NewProc("GlobalMemoryStatusEx")
sizeofMemoryStatusEx = uint32(unsafe.Sizeof(MEMORYSTATUSEX{}))
)
var CudartGlobs = []string{
"c:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v*\\bin\\cudart64_*.dll",
}
var NvmlGlobs = []string{
"c:\\Windows\\System32\\nvml.dll",
}
var NvcudaGlobs = []string{
"c:\\windows\\system*\\nvcuda.dll",
}
var OneapiGlobs = []string{
"c:\\Windows\\System32\\DriverStore\\FileRepository\\*\\ze_intel_gpu64.dll",
}
var (
CudartMgmtName = "cudart64_*.dll"
NvcudaMgmtName = "nvcuda.dll"
NvmlMgmtName = "nvml.dll"
OneapiMgmtName = "ze_intel_gpu64.dll"
)
func GetCPUMem() (memInfo, error) {
memStatus := MEMORYSTATUSEX{length: sizeofMemoryStatusEx}
r1, _, err := globalMemoryStatusExProc.Call(uintptr(unsafe.Pointer(&memStatus)))
if r1 == 0 {
return memInfo{}, fmt.Errorf("GlobalMemoryStatusEx failed: %w", err)
}
return memInfo{TotalMemory: memStatus.TotalPhys, FreeMemory: memStatus.AvailPhys, FreeSwap: memStatus.AvailPageFile}, nil
}
ollama/gpu/types.go deleted 100644 → 0
View file @ 28e95ed5
package gpu
import (
"fmt"
"log/slog"
"github.com/ollama/ollama/format"
)
type memInfo struct {
TotalMemory uint64 `json:"total_memory,omitempty"`
FreeMemory uint64 `json:"free_memory,omitempty"`
FreeSwap uint64 `json:"free_swap,omitempty"`
}
// Beginning of an `ollama info` command
type GpuInfo struct {
memInfo
Library string `json:"library,omitempty"`
// Optional variant to select (e.g. versions, cpu feature flags)
Variant CPUCapability `json:"variant"`
// MinimumMemory represents the minimum memory required to use the GPU
MinimumMemory uint64 `json:"-"`
// Any extra PATH/LD_LIBRARY_PATH dependencies required for the Library to operate properly
DependencyPath string `json:"lib_path,omitempty"`
// Extra environment variables specific to the GPU as list of [key,value]
EnvWorkarounds [][2]string `json:"envs,omitempty"`
// Set to true if we can NOT reliably discover FreeMemory. A value of true indicates
// the FreeMemory is best effort, and may over or under report actual memory usage
// False indicates FreeMemory can generally be trusted on this GPU
UnreliableFreeMemory bool
// GPU information
ID string `json:"gpu_id"` // string to use for selection of this specific GPU
Name string `json:"name"` // user friendly name if available
Compute string `json:"compute"` // Compute Capability or gfx
// Driver Information - TODO no need to put this on each GPU
DriverMajor int `json:"driver_major,omitempty"`
DriverMinor int `json:"driver_minor,omitempty"`
// TODO other performance capability info to help in scheduling decisions
}
type CPUInfo struct {
GpuInfo
}
type CudaGPUInfo struct {
GpuInfo
OSOverhead uint64 // Memory overhead between the driver library and management library
index int //nolint:unused,nolintlint
}
type CudaGPUInfoList []CudaGPUInfo
type RocmGPUInfo struct {
GpuInfo
usedFilepath string //nolint:unused,nolintlint
index int //nolint:unused,nolintlint
}
type RocmGPUInfoList []RocmGPUInfo
type OneapiGPUInfo struct {
GpuInfo
driverIndex int //nolint:unused,nolintlint
gpuIndex int //nolint:unused,nolintlint
}
type OneapiGPUInfoList []OneapiGPUInfo
type GpuInfoList []GpuInfo
// Split up the set of gpu info's by Library and variant
func (l GpuInfoList) ByLibrary() []GpuInfoList {
resp := []GpuInfoList{}
libs := []string{}
for _, info := range l {
found := false
requested := info.Library
if info.Variant != CPUCapabilityNone {
requested += "_" + info.Variant.String()
}
for i, lib := range libs {
if lib == requested {
resp[i] = append(resp[i], info)
found = true
break
}
}
if !found {
libs = append(libs, info.Library)
resp = append(resp, []GpuInfo{info})
}
}
return resp
}
// Report the GPU information into the log an Info level
func (l GpuInfoList) LogDetails() {
for _, g := range l {
slog.Info("inference compute",
"id", g.ID,
"library", g.Library,
"compute", g.Compute,
"driver", fmt.Sprintf("%d.%d", g.DriverMajor, g.DriverMinor),
"name", g.Name,
"total", format.HumanBytes2(g.TotalMemory),
"available", format.HumanBytes2(g.FreeMemory),
)
}
}
// Sort by Free Space
type ByFreeMemory []GpuInfo
func (a ByFreeMemory) Len() int { return len(a) }
func (a ByFreeMemory) Swap(i, j int) { a[i], a[j] = a[j], a[i] }
func (a ByFreeMemory) Less(i, j int) bool { return a[i].FreeMemory < a[j].FreeMemory }
type CPUCapability uint32
// Override at build time when building base GPU runners
var GPURunnerCPUCapability = CPUCapabilityAVX
const (
CPUCapabilityNone CPUCapability = iota
CPUCapabilityAVX
CPUCapabilityAVX2
// TODO AVX512
)
func (c CPUCapability) String() string {
switch c {
case CPUCapabilityAVX:
return "avx"
case CPUCapabilityAVX2:
return "avx2"
default:
return "no vector extensions"
}
}
ollama/integration/README.md deleted 100644 → 0
View file @ 28e95ed5
# Integration Tests
This directory contains integration tests to exercise Ollama end-to-end to verify behavior
By default, these tests are disabled so `go test ./...` will exercise only unit tests. To run integration tests you must pass the integration tag. `go test -tags=integration ./...`
The integration tests have 2 modes of operating.
1. By default, they will start the server on a random port, run the tests, and then shutdown the server.
2. If `OLLAMA_TEST_EXISTING` is set to a non-empty string, the tests will run against an existing running server, which can be remote
ollama/integration/basic_test.go deleted 100644 → 0
View file @ 28e95ed5
//go:build integration
package integration
import (
"context"
"log/slog"
"os"
"runtime"
"testing"
"time"
"github.com/ollama/ollama/api"
"github.com/stretchr/testify/require"
)
func TestOrcaMiniBlueSky(t *testing.T) {
ctx, cancel := context.WithTimeout(context.Background(), 2*time.Minute)
defer cancel()
// Set up the test data
req := api.GenerateRequest{
Model: "orca-mini",
Prompt: "why is the sky blue?",
Stream: &stream,
Options: map[string]interface{}{
"temperature": 0,
"seed": 123,
},
}
GenerateTestHelper(ctx, t, req, []string{"rayleigh", "scattering"})
}
func TestUnicodeModelDir(t *testing.T) {
// This is only useful for Windows with utf-16 characters, so skip this test for other platforms
if runtime.GOOS != "windows" {
t.Skip("Unicode test only applicable to windows")
}
// Only works for local testing
if os.Getenv("OLLAMA_TEST_EXISTING") != "" {
t.Skip("TestUnicodeModelDir only works for local testing, skipping")
}
modelDir, err := os.MkdirTemp("", "ollama_埃")
require.NoError(t, err)
defer os.RemoveAll(modelDir)
slog.Info("unicode", "OLLAMA_MODELS", modelDir)
t.Setenv("OLLAMA_MODELS", modelDir)
ctx, cancel := context.WithTimeout(context.Background(), 2*time.Minute)
defer cancel()
req := api.GenerateRequest{
Model: "orca-mini",
Prompt: "why is the sky blue?",
Stream: &stream,
Options: map[string]interface{}{
"temperature": 0,
"seed": 123,
},
}
GenerateTestHelper(ctx, t, req, []string{"rayleigh", "scattering"})
}
ollama/integration/concurrency_test.go deleted 100644 → 0
View file @ 28e95ed5
//go:build integration
package integration
import (
"context"
"log/slog"
"os"
"strconv"
"sync"
"testing"
"time"
"github.com/stretchr/testify/require"
"github.com/ollama/ollama/api"
"github.com/ollama/ollama/format"
)
func TestMultiModelConcurrency(t *testing.T) {
var (
req = [2]api.GenerateRequest{
{
Model: "orca-mini",
Prompt: "why is the ocean blue?",
Stream: &stream,
KeepAlive: &api.Duration{Duration: 10 * time.Second},
Options: map[string]interface{}{
"seed": 42,
"temperature": 0.0,
},
}, {
Model: "tinydolphin",
Prompt: "what is the origin of the us thanksgiving holiday?",
Stream: &stream,
KeepAlive: &api.Duration{Duration: 10 * time.Second},
Options: map[string]interface{}{
"seed": 42,
"temperature": 0.0,
},
},
}
resp = [2][]string{
{"sunlight"},
{"england", "english", "massachusetts", "pilgrims", "british"},
}
)
var wg sync.WaitGroup
wg.Add(len(req))
ctx, cancel := context.WithTimeout(context.Background(), time.Second*240)
defer cancel()
client, _, cleanup := InitServerConnection(ctx, t)
defer cleanup()
for i := 0; i < len(req); i++ {
require.NoError(t, PullIfMissing(ctx, client, req[i].Model))
}
for i := 0; i < len(req); i++ {
go func(i int) {
defer wg.Done()
DoGenerate(ctx, t, client, req[i], resp[i], 60*time.Second, 10*time.Second)
}(i)
}
wg.Wait()
}
func TestIntegrationConcurrentPredictOrcaMini(t *testing.T) {
req, resp := GenerateRequests()
reqLimit := len(req)
iterLimit := 5
if s := os.Getenv("OLLAMA_MAX_VRAM"); s != "" {
maxVram, err := strconv.ParseUint(s, 10, 64)
require.NoError(t, err)
// Don't hammer on small VRAM cards...
if maxVram < 4*format.GibiByte {
reqLimit = min(reqLimit, 2)
iterLimit = 2
}
}
ctx, cancel := context.WithTimeout(context.Background(), 9*time.Minute)
defer cancel()
client, _, cleanup := InitServerConnection(ctx, t)
defer cleanup()
// Get the server running (if applicable) warm the model up with a single initial request
DoGenerate(ctx, t, client, req[0], resp[0], 60*time.Second, 10*time.Second)
var wg sync.WaitGroup
wg.Add(reqLimit)
for i := 0; i < reqLimit; i++ {
go func(i int) {
defer wg.Done()
for j := 0; j < iterLimit; j++ {
slog.Info("Starting", "req", i, "iter", j)
// On slower GPUs it can take a while to process the concurrent requests
// so we allow a much longer initial timeout
DoGenerate(ctx, t, client, req[i], resp[i], 120*time.Second, 20*time.Second)
}
}(i)
}
wg.Wait()
}
// Stress the system if we know how much VRAM it has, and attempt to load more models than will fit
func TestMultiModelStress(t *testing.T) {
s := os.Getenv("OLLAMA_MAX_VRAM") // TODO - discover actual VRAM
if s == "" {
t.Skip("OLLAMA_MAX_VRAM not specified, can't pick the right models for the stress test")
}
maxVram, err := strconv.ParseUint(s, 10, 64)
if err != nil {
t.Fatal(err)
}
type model struct {
name string
size uint64 // Approximate amount of VRAM they typically use when fully loaded in VRAM
}
smallModels := []model{
{
name: "orca-mini",
size: 2992 * format.MebiByte,
},
{
name: "phi",
size: 2616 * format.MebiByte,
},
{
name: "gemma:2b",
size: 2364 * format.MebiByte,
},
{
name: "stable-code:3b",
size: 2608 * format.MebiByte,
},
{
name: "starcoder2:3b",
size: 2166 * format.MebiByte,
},
}
mediumModels := []model{
{
name: "llama2",
size: 5118 * format.MebiByte,
},
{
name: "mistral",
size: 4620 * format.MebiByte,
},
{
name: "orca-mini:7b",
size: 5118 * format.MebiByte,
},
{
name: "dolphin-mistral",
size: 4620 * format.MebiByte,
},
{
name: "gemma:7b",
size: 5000 * format.MebiByte,
},
{
name: "codellama:7b",
size: 5118 * format.MebiByte,
},
}
// These seem to be too slow to be useful...
// largeModels := []model{
// {
// name: "llama2:13b",
// size: 7400 * format.MebiByte,
// },
// {
// name: "codellama:13b",
// size: 7400 * format.MebiByte,
// },
// {
// name: "orca-mini:13b",
// size: 7400 * format.MebiByte,
// },
// {
// name: "gemma:7b",
// size: 5000 * format.MebiByte,
// },
// {
// name: "starcoder2:15b",
// size: 9100 * format.MebiByte,
// },
// }
var chosenModels []model
switch {
case maxVram < 10000*format.MebiByte:
slog.Info("selecting small models")
chosenModels = smallModels
// case maxVram < 30000*format.MebiByte:
default:
slog.Info("selecting medium models")
chosenModels = mediumModels
// default:
// slog.Info("selecting large models")
// chosenModels = largModels
}
req, resp := GenerateRequests()
for i := range req {
if i > len(chosenModels) {
break
}
req[i].Model = chosenModels[i].name
}
ctx, cancel := context.WithTimeout(context.Background(), 15*time.Minute) // TODO baseline -- 10m too short
defer cancel()
client, _, cleanup := InitServerConnection(ctx, t)
defer cleanup()
// Make sure all the models are pulled before we get started
for _, r := range req {
require.NoError(t, PullIfMissing(ctx, client, r.Model))
}
var wg sync.WaitGroup
consumed := uint64(256 * format.MebiByte) // Assume some baseline usage
for i := 0; i < len(req); i++ {
// Always get at least 2 models, but dont' overshoot VRAM too much or we'll take too long
if i > 1 && consumed > maxVram {
slog.Info("achieved target vram exhaustion", "count", i, "vram", format.HumanBytes2(maxVram), "models", format.HumanBytes2(consumed))
break
}
consumed += chosenModels[i].size
slog.Info("target vram", "count", i, "vram", format.HumanBytes2(maxVram), "models", format.HumanBytes2(consumed))
wg.Add(1)
go func(i int) {
defer wg.Done()
for j := 0; j < 3; j++ {
slog.Info("Starting", "req", i, "iter", j, "model", req[i].Model)
DoGenerate(ctx, t, client, req[i], resp[i], 120*time.Second, 5*time.Second)
}
}(i)
}
go func() {
for {
time.Sleep(2 * time.Second)
select {
case <-ctx.Done():
return
default:
models, err := client.ListRunning(ctx)
if err != nil {
slog.Warn("failed to list running models", "error", err)
continue
}
for _, m := range models.Models {
slog.Info("loaded model snapshot", "model", m)
}
}
}
}()
wg.Wait()
}
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