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llama.cpp
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cuda : display total and free VRAM capacity during device initialization (#20185)

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Michael Huang 2026-03-08 21:45:43 -07:00 committed by GitHub
parent ae87863dc1
commit 5f4cdac385
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GPG Key ID: B5690EEEBB952194
1 changed files with 23 additions and 7 deletions
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30
ggml/src/ggml-cuda/ggml-cuda.cu
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@ -205,7 +205,14 @@ static ggml_cuda_device_info ggml_cuda_init() {
GGML_ASSERT(info.device_count <= GGML_CUDA_MAX_DEVICES);
int64_t total_vram = 0;
GGML_LOG_INFO("%s: found %d " GGML_CUDA_NAME " devices:\n", __func__, info.device_count);
for (int id = 0; id < info.device_count; ++id) {
cudaDeviceProp prop;
CUDA_CHECK(cudaGetDeviceProperties(&prop, id));
total_vram += prop.totalGlobalMem;
}
GGML_LOG_INFO("%s: found %d " GGML_CUDA_NAME " devices (Total VRAM: %zu MiB):\n",
__func__, info.device_count, (size_t)(total_vram / (1024 * 1024)));
total_vram = 0;
std::vector<std::pair<int, std::string>> turing_devices_without_mma;
for (int id = 0; id < info.device_count; ++id) {
@ -243,6 +250,12 @@ static ggml_cuda_device_info ggml_cuda_init() {
#else
info.devices[id].supports_cooperative_launch = false;
#endif // !(GGML_USE_MUSA)
// cudaMemGetInfo returns info for the current device
size_t free_mem;
CUDA_CHECK(cudaSetDevice(id));
CUDA_CHECK(cudaMemGetInfo(&free_mem, NULL));
#if defined(GGML_USE_HIP)
info.devices[id].smpbo = prop.sharedMemPerBlock;
@ -257,22 +270,25 @@ static ggml_cuda_device_info ggml_cuda_init() {
info.devices[id].cc += prop.minor * 0x10;
}
}
GGML_LOG_INFO(" Device %d: %s, %s (0x%x), VMM: %s, Wave Size: %d\n",
GGML_LOG_INFO(" Device %d: %s, %s (0x%x), VMM: %s, Wave Size: %d, VRAM: %zu MiB (%zu MiB free)\n",
id, prop.name, prop.gcnArchName, info.devices[id].cc & 0xffff,
device_vmm ? "yes" : "no", prop.warpSize);
device_vmm ? "yes" : "no", prop.warpSize,
(size_t)(prop.totalGlobalMem / (1024 * 1024)), free_mem / (1024 * 1024));
#elif defined(GGML_USE_MUSA)
// FIXME: Ensure compatibility with varying warp sizes across different MUSA archs.
info.devices[id].warp_size = 32;
info.devices[id].smpbo = prop.sharedMemPerBlockOptin;
info.devices[id].cc = GGML_CUDA_CC_OFFSET_MTHREADS + prop.major * 0x100;
info.devices[id].cc += prop.minor * 0x10;
GGML_LOG_INFO(" Device %d: %s, compute capability %d.%d, VMM: %s\n",
id, prop.name, prop.major, prop.minor, device_vmm ? "yes" : "no");
GGML_LOG_INFO(" Device %d: %s, compute capability %d.%d, VMM: %s, VRAM: %zu MiB (%zu MiB free)\n",
id, prop.name, prop.major, prop.minor, device_vmm ? "yes" : "no",
(size_t)(prop.totalGlobalMem / (1024 * 1024)), free_mem / (1024 * 1024));
#else
info.devices[id].smpbo = prop.sharedMemPerBlockOptin;
info.devices[id].cc = 100*prop.major + 10*prop.minor;
GGML_LOG_INFO(" Device %d: %s, compute capability %d.%d, VMM: %s\n",
id, prop.name, prop.major, prop.minor, device_vmm ? "yes" : "no");
GGML_LOG_INFO(" Device %d: %s, compute capability %d.%d, VMM: %s, VRAM: %zu MiB (%zu MiB free)\n",
id, prop.name, prop.major, prop.minor, device_vmm ? "yes" : "no",
(size_t)(prop.totalGlobalMem / (1024 * 1024)), free_mem / (1024 * 1024));
std::string device_name(prop.name);
if (device_name == "NVIDIA GeForce MX450") {
turing_devices_without_mma.push_back({ id, device_name });