//go:build linux || windows package gpu /* #cgo linux LDFLAGS: -lrt -lpthread -ldl -lstdc++ -lm #cgo windows LDFLAGS: -lpthread #include "gpu_info.h" */ import "C" import ( "fmt" "log/slog" "os" "path/filepath" "runtime" "strings" "sync" "unsafe" "github.com/ollama/ollama/format" ) type handles struct { deviceCount int cudart *C.cudart_handle_t } const ( cudaMinimumMemory = 457 * format.MebiByte rocmMinimumMemory = 457 * format.MebiByte ) var gpuMutex sync.Mutex // With our current CUDA compile flags, older than 5.0 will not work properly var CudaComputeMin = [2]C.int{5, 0} var RocmComputeMin = 9 // TODO find a better way to detect iGPU instead of minimum memory const IGPUMemLimit = 1 * format.GibiByte // 512G is what they typically report, so anything less than 1G must be iGPU var CudartLinuxGlobs = []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 CudartWindowsGlobs = []string{ "c:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v*\\bin\\cudart64_*.dll", } // Jetson devices have JETSON_JETPACK="x.y.z" factory set to the Jetpack version installed. // Included to drive logic for reducing Ollama-allocated overhead on L4T/Jetson devices. var CudaTegra string = os.Getenv("JETSON_JETPACK") // Note: gpuMutex must already be held func initGPUHandles() *handles { // TODO - if the ollama build is CPU only, don't do these checks as they're irrelevant and confusing gpuHandles := &handles{} var cudartMgmtName string var cudartMgmtPatterns []string tmpDir, _ := PayloadsDir() switch runtime.GOOS { case "windows": cudartMgmtName = "cudart64_*.dll" localAppData := os.Getenv("LOCALAPPDATA") cudartMgmtPatterns = []string{filepath.Join(localAppData, "Programs", "Ollama", cudartMgmtName)} cudartMgmtPatterns = append(cudartMgmtPatterns, CudartWindowsGlobs...) case "linux": cudartMgmtName = "libcudart.so*" if tmpDir != "" { // TODO - add "payloads" for subprocess cudartMgmtPatterns = []string{filepath.Join(tmpDir, "cuda*", cudartMgmtName)} } cudartMgmtPatterns = append(cudartMgmtPatterns, CudartLinuxGlobs...) default: return gpuHandles } slog.Info("Detecting GPUs") cudartLibPaths := FindGPULibs(cudartMgmtName, cudartMgmtPatterns) if len(cudartLibPaths) > 0 { deviceCount, cudart, libPath := LoadCUDARTMgmt(cudartLibPaths) if cudart != nil { slog.Info("detected GPUs", "library", libPath, "count", deviceCount) gpuHandles.cudart = cudart gpuHandles.deviceCount = deviceCount return gpuHandles } } return gpuHandles } func GetGPUInfo() GpuInfoList { // TODO - consider exploring lspci (and equivalent on windows) to check for // GPUs so we can report warnings if we see Nvidia/AMD but fail to load the libraries gpuMutex.Lock() defer gpuMutex.Unlock() gpuHandles := initGPUHandles() defer func() { if gpuHandles.cudart != nil { C.cudart_release(*gpuHandles.cudart) } }() // All our GPU builds on x86 have AVX enabled, so fallback to CPU if we don't detect at least AVX cpuVariant := GetCPUVariant() if cpuVariant == "" && runtime.GOARCH == "amd64" { slog.Warn("CPU does not have AVX or AVX2, disabling GPU support.") } var memInfo C.mem_info_t resp := []GpuInfo{} // NVIDIA first for i := 0; i < gpuHandles.deviceCount; i++ { // TODO once we support CPU compilation variants of GPU libraries refine this... if cpuVariant == "" && runtime.GOARCH == "amd64" { continue } gpuInfo := GpuInfo{ Library: "cuda", } C.cudart_check_vram(*gpuHandles.cudart, C.int(i), &memInfo) if memInfo.err != nil { slog.Info("error looking up nvidia GPU memory", "error", C.GoString(memInfo.err)) C.free(unsafe.Pointer(memInfo.err)) continue } if memInfo.major < CudaComputeMin[0] || (memInfo.major == CudaComputeMin[0] && memInfo.minor < CudaComputeMin[1]) { slog.Info(fmt.Sprintf("[%d] CUDA GPU is too old. Compute Capability detected: %d.%d", i, memInfo.major, memInfo.minor)) continue } gpuInfo.TotalMemory = uint64(memInfo.total) gpuInfo.FreeMemory = uint64(memInfo.free) gpuInfo.ID = C.GoString(&memInfo.gpu_id[0]) gpuInfo.Major = int(memInfo.major) gpuInfo.Minor = int(memInfo.minor) gpuInfo.MinimumMemory = cudaMinimumMemory // TODO potentially sort on our own algorithm instead of what the underlying GPU library does... resp = append(resp, gpuInfo) } // Then AMD resp = append(resp, AMDGetGPUInfo()...) if len(resp) == 0 { C.cpu_check_ram(&memInfo) if memInfo.err != nil { slog.Info("error looking up CPU memory", "error", C.GoString(memInfo.err)) C.free(unsafe.Pointer(memInfo.err)) return resp } gpuInfo := GpuInfo{ Library: "cpu", Variant: cpuVariant, } gpuInfo.TotalMemory = uint64(memInfo.total) gpuInfo.FreeMemory = uint64(memInfo.free) gpuInfo.ID = C.GoString(&memInfo.gpu_id[0]) resp = append(resp, gpuInfo) } return resp } func GetCPUMem() (memInfo, error) { var ret memInfo var info C.mem_info_t C.cpu_check_ram(&info) if info.err != nil { defer C.free(unsafe.Pointer(info.err)) return ret, fmt.Errorf(C.GoString(info.err)) } ret.FreeMemory = uint64(info.free) ret.TotalMemory = uint64(info.total) return ret, nil } func FindGPULibs(baseLibName string, patterns []string) []string { // Multiple GPU libraries may exist, and some may not work, so keep trying until we exhaust them var ldPaths []string gpuLibPaths := []string{} slog.Debug("Searching for GPU library", "name", baseLibName) switch runtime.GOOS { case "windows": ldPaths = strings.Split(os.Getenv("PATH"), ";") case "linux": ldPaths = strings.Split(os.Getenv("LD_LIBRARY_PATH"), ":") default: return gpuLibPaths } // Start with whatever we find in the PATH/LD_LIBRARY_PATH for _, ldPath := range ldPaths { d, err := filepath.Abs(ldPath) if err != nil { continue } patterns = append(patterns, filepath.Join(d, baseLibName+"*")) } slog.Debug("gpu library search", "globs", patterns) for _, pattern := range patterns { // Ignore glob discovery errors matches, _ := filepath.Glob(pattern) for _, match := range matches { // Resolve any links so we don't try the same lib multiple times // and weed out any dups across globs libPath := match tmp := match var err error for ; err == nil; tmp, err = os.Readlink(libPath) { if !filepath.IsAbs(tmp) { tmp = filepath.Join(filepath.Dir(libPath), tmp) } libPath = tmp } new := true for _, cmp := range gpuLibPaths { if cmp == libPath { new = false break } } if new { gpuLibPaths = append(gpuLibPaths, libPath) } } } slog.Debug("discovered GPU libraries", "paths", gpuLibPaths) return gpuLibPaths } func LoadCUDARTMgmt(cudartLibPaths []string) (int, *C.cudart_handle_t, string) { var resp C.cudart_init_resp_t resp.ch.verbose = getVerboseState() for _, libPath := range cudartLibPaths { lib := C.CString(libPath) defer C.free(unsafe.Pointer(lib)) C.cudart_init(lib, &resp) if resp.err != nil { slog.Debug("Unable to load cudart", "library", libPath, "error", C.GoString(resp.err)) C.free(unsafe.Pointer(resp.err)) } else { return int(resp.num_devices), &resp.ch, libPath } } return 0, nil, "" } func getVerboseState() C.uint16_t { if debug := os.Getenv("OLLAMA_DEBUG"); debug != "" { return C.uint16_t(1) } return C.uint16_t(0) } // Given the list of GPUs this instantiation is targeted for, // figure out the visible devices environment variable // // If different libraries are detected, the first one is what we use func (l GpuInfoList) GetVisibleDevicesEnv() (string, string) { if len(l) == 0 { return "", "" } switch l[0].Library { case "cuda": return cudaGetVisibleDevicesEnv(l) case "rocm": return rocmGetVisibleDevicesEnv(l) default: slog.Debug("no filter required for library " + l[0].Library) return "", "" } }