Merge pull request #4067 from dhiltgen/cudart

Add CUDA Driver API for GPU discovery

gpu/gpu.go

@@ -27,6 +27,7 @@ import (
 type handles struct {
 	deviceCount int
 	cudart      *C.cudart_handle_t
+	nvcuda      *C.nvcuda_handle_t
 }
 
 const (
@@ -63,6 +64,22 @@ var CudartWindowsGlobs = []string{
 	"c:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v*\\bin\\cudart64_*.dll",
 }
 
+var NvcudaLinuxGlobs = []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 NvcudaWindowsGlobs = []string{
+	"c:\\windows\\system*\\nvcuda.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")
@@ -75,6 +92,8 @@ func initGPUHandles() *handles {
 	gpuHandles := &handles{}
 	var cudartMgmtName string
 	var cudartMgmtPatterns []string
+	var nvcudaMgmtName string
+	var nvcudaMgmtPatterns []string
 
 	tmpDir, _ := PayloadsDir()
 	switch runtime.GOOS {
@@ -83,6 +102,9 @@ func initGPUHandles() *handles {
 		localAppData := os.Getenv("LOCALAPPDATA")
 		cudartMgmtPatterns = []string{filepath.Join(localAppData, "Programs", "Ollama", cudartMgmtName)}
 		cudartMgmtPatterns = append(cudartMgmtPatterns, CudartWindowsGlobs...)
+		// Aligned with driver, we can't carry as payloads
+		nvcudaMgmtName = "nvcuda.dll"
+		nvcudaMgmtPatterns = NvcudaWindowsGlobs
 	case "linux":
 		cudartMgmtName = "libcudart.so*"
 		if tmpDir != "" {
@@ -90,11 +112,25 @@ func initGPUHandles() *handles {
 			cudartMgmtPatterns = []string{filepath.Join(tmpDir, "cuda*", cudartMgmtName)}
 		}
 		cudartMgmtPatterns = append(cudartMgmtPatterns, CudartLinuxGlobs...)
+		// Aligned with driver, we can't carry as payloads
+		nvcudaMgmtName = "libcuda.so*"
+		nvcudaMgmtPatterns = NvcudaLinuxGlobs
 	default:
 		return gpuHandles
 	}
 
 	slog.Info("Detecting GPUs")
+	nvcudaLibPaths := FindGPULibs(nvcudaMgmtName, nvcudaMgmtPatterns)
+	if len(nvcudaLibPaths) > 0 {
+		deviceCount, nvcuda, libPath := LoadNVCUDAMgmt(nvcudaLibPaths)
+		if nvcuda != nil {
+			slog.Info("detected GPUs", "count", deviceCount, "library", libPath)
+			gpuHandles.nvcuda = nvcuda
+			gpuHandles.deviceCount = deviceCount
+			return gpuHandles
+		}
+	}
+
 	cudartLibPaths := FindGPULibs(cudartMgmtName, cudartMgmtPatterns)
 	if len(cudartLibPaths) > 0 {
 		deviceCount, cudart, libPath := LoadCUDARTMgmt(cudartLibPaths)
@@ -119,6 +155,9 @@ func GetGPUInfo() GpuInfoList {
 		if gpuHandles.cudart != nil {
 			C.cudart_release(*gpuHandles.cudart)
 		}
+		if gpuHandles.nvcuda != nil {
+			C.nvcuda_release(*gpuHandles.nvcuda)
+		}
 	}()
 
 	// All our GPU builds on x86 have AVX enabled, so fallback to CPU if we don't detect at least AVX
@@ -139,7 +178,11 @@ func GetGPUInfo() GpuInfoList {
 		gpuInfo := GpuInfo{
 			Library: "cuda",
 		}
+		if gpuHandles.cudart != nil {
 			C.cudart_check_vram(*gpuHandles.cudart, C.int(i), &memInfo)
+		} else {
+			C.nvcuda_check_vram(*gpuHandles.nvcuda, 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))
@@ -197,9 +240,10 @@ func GetCPUMem() (memInfo, error) {
 	return ret, nil
 }
 
-func FindGPULibs(baseLibName string, patterns []string) []string {
+func FindGPULibs(baseLibName string, defaultPatterns []string) []string {
 	// Multiple GPU libraries may exist, and some may not work, so keep trying until we exhaust them
 	var ldPaths []string
+	var patterns []string
 	gpuLibPaths := []string{}
 	slog.Debug("Searching for GPU library", "name", baseLibName)
 
@@ -219,6 +263,7 @@ func FindGPULibs(baseLibName string, patterns []string) []string {
 		}
 		patterns = append(patterns, filepath.Join(d, baseLibName+"*"))
 	}
+	patterns = append(patterns, defaultPatterns...)
 	slog.Debug("gpu library search", "globs", patterns)
 	for _, pattern := range patterns {
 		// Ignore glob discovery errors
@@ -268,6 +313,23 @@ func LoadCUDARTMgmt(cudartLibPaths []string) (int, *C.cudart_handle_t, string) {
 	return 0, nil, ""
 }
 
+func LoadNVCUDAMgmt(nvcudaLibPaths []string) (int, *C.nvcuda_handle_t, string) {
+	var resp C.nvcuda_init_resp_t
+	resp.ch.verbose = getVerboseState()
+	for _, libPath := range nvcudaLibPaths {
+		lib := C.CString(libPath)
+		defer C.free(unsafe.Pointer(lib))
+		C.nvcuda_init(lib, &resp)
+		if resp.err != nil {
+			slog.Debug("Unable to load nvcuda", "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 envconfig.Debug {
 		return C.uint16_t(1)

gpu/gpu_info.h

@@ -58,6 +58,7 @@ void cpu_check_ram(mem_info_t *resp);
 #endif
 
 #include "gpu_info_cudart.h"
+#include "gpu_info_nvcuda.h"
 
 #endif  // __GPU_INFO_H__
 #endif  // __APPLE__

gpu/gpu_info_cudart.h

@@ -6,9 +6,9 @@
 // Just enough typedef's to dlopen/dlsym for memory information
 typedef enum cudartReturn_enum {
   CUDART_SUCCESS = 0,
-  CUDA_ERROR_INVALID_VALUE = 1,
+  CUDART_ERROR_INVALID_VALUE = 1,
-  CUDA_ERROR_MEMORY_ALLOCATION = 2,
+  CUDART_ERROR_MEMORY_ALLOCATION = 2,
-  CUDA_ERROR_INSUFFICIENT_DRIVER = 35,
+  CUDART_ERROR_INSUFFICIENT_DRIVER = 35,
   // Other values omitted for now...
 } cudartReturn_t;
 

gpu/gpu_info_nvcuda.c

@@ -0,0 +1,203 @@
+#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;
+  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},
+      {"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);
+    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.cuInit)(0);
+  if (ret != CUDA_SUCCESS) {
+    LOG(resp->ch.verbose, "cuInit 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, "nvcuda init failure: %d", ret);
+    resp->err = strdup(buf);
+    return;
+  }
+
+  int version = 0;
+  nvcudaDriverVersion_t driverVersion;
+  driverVersion.major = 0;
+  driverVersion.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 {
+    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.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);
+    return;
+  }
+}
+
+const int buflen = 256;
+void nvcuda_check_vram(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("nvcuda handle isn't initialized");
+    return;
+  }
+
+  ret = (*h.cuDeviceGet)(&device, i);
+  if (ret != CUDA_SUCCESS) {
+    snprintf(buf, buflen, "nvcuda device failed to initialize");
+    resp->err = strdup(buf);
+    return;
+  }
+
+  resp->major = 0;
+  resp->minor = 0;
+  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]
+      );
+  }
+
+  // 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, "nvcuda failed to get primary device context %d", ret);
+    resp->err = strdup(buf);
+    return;
+  }
+
+  ret = (*h.cuMemGetInfo_v2)(&memInfo.free, &memInfo.total);
+  if (ret != CUDA_SUCCESS) {
+    snprintf(buf, buflen, "nvcuda 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, "nvcuda failed to release primary device context %d", ret);
+  }
+}
+
+void nvcuda_release(nvcuda_handle_t h) {
+  LOG(h.verbose, "releasing nvcuda library\n");
+  UNLOAD_LIBRARY(h.handle);
+  // TODO and other context release logic?
+  h.handle = NULL;
+}
+
+#endif  // __APPLE__

gpu/gpu_info_nvcuda.h

@@ -0,0 +1,71 @@
+#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_MEMORY_ALLOCATION = 2,
+  CUDA_ERROR_NOT_INITIALIZED = 3,
+  CUDA_ERROR_INSUFFICIENT_DRIVER = 35,
+  // 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;
+  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
+
+  // 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;
+} nvcuda_init_resp_t;
+
+void nvcuda_init(char *nvcuda_lib_path, nvcuda_init_resp_t *resp);
+void nvcuda_check_vram(nvcuda_handle_t ch, int device_id, mem_info_t *resp);
+void nvcuda_release(nvcuda_handle_t ch);
+
+#endif  // __GPU_INFO_NVCUDA_H__
+#endif  // __APPLE__