Franscobec/gpufetch
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Patch cuda.cpp with cloudy's fix

Browse Source
This commit is contained in:
Franscobec
2026-01-10 19:29:45 -05:00
parent 5f619dc95a
commit 0f416b2da9
1 changed files with 33 additions and 39 deletions
Download Patch File Download Diff File Expand all files Collapse all files

72
src/cuda/cuda.cpp
View File

@@ -1,3 +1,6 @@
// patched cuda.cpp for cuda13 by cloudy
#include <cuda_runtime.h>
#include <cstring>
#include <cstdlib>
@@ -14,25 +17,20 @@ bool print_gpu_cuda(struct gpu_info* gpu) {
char* cc = get_str_cc(gpu->arch);
printf("%s (Compute Capability %s)\n", gpu->name, cc);
free(cc);
return true;
}
struct cache* get_cache_info(cudaDeviceProp prop) {
struct cache* cach = (struct cache*) emalloc(sizeof(struct cache));
cach->L2 = (struct cach*) emalloc(sizeof(struct cach));
cach->L2->size = prop.l2CacheSize;
cach->L2->num_caches = 1;
cach->L2->exists = true;
return cach;
}
int get_tensor_cores(struct uarch* arch, int sm, int major) {
if(major == 7) {
// TU116 does not have tensor cores!
// https://www.anandtech.com/show/13973/nvidia-gtx-1660-ti-review-feat-evga-xc-gaming/2
if (is_chip_TU116(arch))
return 0;
return sm * 8;
@@ -43,57 +41,57 @@ int get_tensor_cores(struct uarch* arch, int sm, int major) {
struct topology_c* get_topology_info(struct uarch* arch, cudaDeviceProp prop) {
struct topology_c* topo = (struct topology_c*) emalloc(sizeof(struct topology_c));
topo->streaming_mp = prop.multiProcessorCount;
topo->cores_per_mp = _ConvertSMVer2Cores(prop.major, prop.minor);
topo->cuda_cores = topo->streaming_mp * topo->cores_per_mp;
topo->tensor_cores = get_tensor_cores(arch, topo->streaming_mp, prop.major);
return topo;
}
int32_t guess_clock_multipilier(struct gpu_info* gpu, struct memory* mem) {
// Guess clock multiplier
int32_t clk_mul = 1;
int32_t clk8 = abs((mem->freq/8) - gpu->freq);
int32_t clk4 = abs((mem->freq/4) - gpu->freq);
int32_t clk2 = abs((mem->freq/2) - gpu->freq);
int32_t clk1 = abs((mem->freq/1) - gpu->freq);
int32_t min = mem->freq;
if(clkm_possible_for_uarch(8, gpu->arch) && min > clk8) { clk_mul = 8; min = clk8; }
if(clkm_possible_for_uarch(4, gpu->arch) && min > clk4) { clk_mul = 4; min = clk4; }
if(clkm_possible_for_uarch(2, gpu->arch) && min > clk2) { clk_mul = 2; min = clk2; }
if(clkm_possible_for_uarch(1, gpu->arch) && min > clk1) { clk_mul = 1; min = clk1; }
return clk_mul;
}
struct memory* get_memory_info(struct gpu_info* gpu, cudaDeviceProp prop) {
struct memory* mem = (struct memory*) emalloc(sizeof(struct memory));
int val = 0;
mem->size_bytes = (unsigned long long) prop.totalGlobalMem;
mem->freq = prop.memoryClockRate * 0.001f;
if (cudaDeviceGetAttribute(&val, cudaDevAttrMemoryClockRate, gpu->idx) == cudaSuccess) {
if (val > 1000000)
mem->freq = (float)val / 1000000.0f;
else
mem->freq = (float)val * 0.001f;
} else {
mem->freq = 0.0f;
}
mem->bus_width = prop.memoryBusWidth;
mem->clk_mul = guess_clock_multipilier(gpu, mem);
mem->type = guess_memtype_from_cmul_and_uarch(mem->clk_mul, gpu->arch);
// Fix frequency returned from CUDA to show real frequency
mem->freq = mem->freq / mem->clk_mul;
if (mem->clk_mul > 0)
mem->freq = mem->freq / mem->clk_mul;
return mem;
}
// Compute peak performance when using CUDA cores
int64_t get_peak_performance_cuda(struct gpu_info* gpu) {
return gpu->freq * 1000000 * gpu->topo_c->cuda_cores * 2;
}
// Compute peak performance when using tensor cores
int64_t get_peak_performance_tcu(cudaDeviceProp prop, struct gpu_info* gpu) {
// Volta / Turing tensor cores performs 4x4x4 FP16 matrix multiplication
// Ampere tensor cores performs 8x4x8 FP16 matrix multiplicacion
if(prop.major == 7) return gpu->freq * 1000000 * 4 * 4 * 4 * 2 * gpu->topo_c->tensor_cores;
else if(prop.major == 8) return gpu->freq * 1000000 * 8 * 4 * 8 * 2 * gpu->topo_c->tensor_cores;
else return 0;
@@ -115,8 +113,7 @@ struct gpu_info* get_gpu_info_cuda(struct pci_dev *devices, int gpu_idx) {
}
int num_gpus = -1;
cudaError_t err = cudaSuccess;
err = cudaGetDeviceCount(&num_gpus);
cudaError_t err = cudaGetDeviceCount(&num_gpus);
if(gpu_idx == 0) {
printf("\r%*c\r", (int) strlen(CUDA_DRIVER_START_WARNING), ' ');
@@ -134,7 +131,6 @@ struct gpu_info* get_gpu_info_cuda(struct pci_dev *devices, int gpu_idx) {
}
if(gpu->idx+1 > num_gpus) {
// Master is trying to query an invalid GPU
return NULL;
}
@@ -144,15 +140,25 @@ struct gpu_info* get_gpu_info_cuda(struct pci_dev *devices, int gpu_idx) {
return NULL;
}
gpu->freq = deviceProp.clockRate * 1e-3f;
int core_clk = 0;
if (cudaDeviceGetAttribute(&core_clk, cudaDevAttrClockRate, gpu->idx) == cudaSuccess) {
if (core_clk > 1000000)
gpu->freq = core_clk / 1000000.0f;
else
gpu->freq = core_clk * 0.001f;
} else {
gpu->freq = 0.0f;
}
gpu->vendor = GPU_VENDOR_NVIDIA;
gpu->name = (char *) emalloc(sizeof(char) * (strlen(deviceProp.name) + 1));
gpu->name = (char *) emalloc(strlen(deviceProp.name) + 1);
strcpy(gpu->name, deviceProp.name);
if((gpu->pci = get_pci_from_pciutils(devices, PCI_VENDOR_ID_NVIDIA, gpu_idx)) == NULL) {
printErr("Unable to find a valid device for vendor id 0x%.4X using pciutils", PCI_VENDOR_ID_NVIDIA);
return NULL;
}
gpu->arch = get_uarch_from_cuda(gpu);
gpu->cach = get_cache_info(deviceProp);
gpu->mem = get_memory_info(gpu, deviceProp);
@@ -163,19 +169,7 @@ struct gpu_info* get_gpu_info_cuda(struct pci_dev *devices, int gpu_idx) {
return gpu;
}
char* get_str_sm(struct gpu_info* gpu) {
return get_str_generic(gpu->topo_c->streaming_mp);
}
char* get_str_cores_sm(struct gpu_info* gpu) {
return get_str_generic(gpu->topo_c->cores_per_mp);
}
char* get_str_cuda_cores(struct gpu_info* gpu) {
return get_str_generic(gpu->topo_c->cuda_cores);
}
char* get_str_tensor_cores(struct gpu_info* gpu) {
return get_str_generic(gpu->topo_c->tensor_cores);
}
char* get_str_sm(struct gpu_info* gpu) { return get_str_generic(gpu->topo_c->streaming_mp); }
char* get_str_cores_sm(struct gpu_info* gpu) { return get_str_generic(gpu->topo_c->cores_per_mp); }
char* get_str_cuda_cores(struct gpu_info* gpu) { return get_str_generic(gpu->topo_c->cuda_cores); }
char* get_str_tensor_cores(struct gpu_info* gpu) { return get_str_generic(gpu->topo_c->tensor_cores); }