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implement nvml for linux (#12517)

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* implement nvml for linux

* Improve scheduler logging when VRAM doesn't recover
This commit is contained in:
Daniel Hiltgen 2025-10-10 15:15:56 -07:00 committed by GitHub
parent 629db9dc43
commit aab2190420
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GPG Key ID: B5690EEEBB952194
3 changed files with 125 additions and 42 deletions
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73
llama/patches/0026-GPU-discovery-enhancements.patch
View File

@ -13,13 +13,13 @@ management libraries for more accurate VRAM usage reporting if available.
ggml/src/ggml-impl.h | 8 +
ggml/src/ggml-metal/ggml-metal.cpp | 3 +-
ggml/src/mem_hip.cpp | 449 +++++++++++++++++++++++++++++
ggml/src/mem_nvml.cpp | 172 +++++++++++
8 files changed, 718 insertions(+), 1 deletion(-)
ggml/src/mem_nvml.cpp | 209 ++++++++++++++
8 files changed, 755 insertions(+), 1 deletion(-)
create mode 100644 ggml/src/mem_hip.cpp
create mode 100644 ggml/src/mem_nvml.cpp
diff --git a/ggml/include/ggml-backend.h b/ggml/include/ggml-backend.h
index 0a2dae26..a6bf3378 100644
index 0a2dae26a..a6bf33785 100644
--- a/ggml/include/ggml-backend.h
+++ b/ggml/include/ggml-backend.h
@@ -169,6 +169,15 @@ extern "C" {
@ -39,7 +39,7 @@ index 0a2dae26..a6bf3378 100644
GGML_API const char * ggml_backend_dev_name(ggml_backend_dev_t device);
diff --git a/ggml/src/CMakeLists.txt b/ggml/src/CMakeLists.txt
index 33b3a15f..86191ef2 100644
index 33b3a15f0..86191ef2c 100644
--- a/ggml/src/CMakeLists.txt
+++ b/ggml/src/CMakeLists.txt
@@ -206,6 +206,8 @@ add_library(ggml-base
@ -52,7 +52,7 @@ index 33b3a15f..86191ef2 100644
target_include_directories(ggml-base PRIVATE .)
diff --git a/ggml/src/ggml-cuda/ggml-cuda.cu b/ggml/src/ggml-cuda/ggml-cuda.cu
index 531d6e27..3fa3a057 100644
index 531d6e272..3fa3a0575 100644
--- a/ggml/src/ggml-cuda/ggml-cuda.cu
+++ b/ggml/src/ggml-cuda/ggml-cuda.cu
@@ -261,6 +261,16 @@ static ggml_cuda_device_info ggml_cuda_init() {
@ -184,7 +184,7 @@ index 531d6e27..3fa3a057 100644
/* .iface = */ ggml_backend_cuda_device_interface,
/* .reg = */ &reg,
diff --git a/ggml/src/ggml-cuda/vendors/hip.h b/ggml/src/ggml-cuda/vendors/hip.h
index 06f9e7c1..eb8f66cb 100644
index 06f9e7c1e..eb8f66cb0 100644
--- a/ggml/src/ggml-cuda/vendors/hip.h
+++ b/ggml/src/ggml-cuda/vendors/hip.h
@@ -5,6 +5,9 @@
@ -206,7 +206,7 @@ index 06f9e7c1..eb8f66cb 100644
#define cudaErrorPeerAccessAlreadyEnabled hipErrorPeerAccessAlreadyEnabled
#define cudaErrorPeerAccessNotEnabled hipErrorPeerAccessNotEnabled
diff --git a/ggml/src/ggml-impl.h b/ggml/src/ggml-impl.h
index 86a1ebf6..9fc9fbfc 100644
index 86a1ebf62..9fc9fbfcf 100644
--- a/ggml/src/ggml-impl.h
+++ b/ggml/src/ggml-impl.h
@@ -635,6 +635,14 @@ static inline bool ggml_can_fuse(const struct ggml_cgraph * cgraph, int node_idx
@ -225,7 +225,7 @@ index 86a1ebf6..9fc9fbfc 100644
}
#endif
diff --git a/ggml/src/ggml-metal/ggml-metal.cpp b/ggml/src/ggml-metal/ggml-metal.cpp
index 08ab4fc9..17999a61 100644
index 08ab4fc91..17999a616 100644
--- a/ggml/src/ggml-metal/ggml-metal.cpp
+++ b/ggml/src/ggml-metal/ggml-metal.cpp
@@ -535,6 +535,7 @@ static enum ggml_backend_dev_type ggml_backend_metal_device_get_type(ggml_backen
@ -247,7 +247,7 @@ index 08ab4fc9..17999a61 100644
/* .host_buffer = */ false,
diff --git a/ggml/src/mem_hip.cpp b/ggml/src/mem_hip.cpp
new file mode 100644
index 00000000..8ef19b8c
index 000000000..8ef19b8cf
--- /dev/null
+++ b/ggml/src/mem_hip.cpp
@@ -0,0 +1,449 @@
@ -703,10 +703,10 @@ index 00000000..8ef19b8c
\ No newline at end of file
diff --git a/ggml/src/mem_nvml.cpp b/ggml/src/mem_nvml.cpp
new file mode 100644
index 00000000..aa05e9dc
index 000000000..c9073cef0
--- /dev/null
+++ b/ggml/src/mem_nvml.cpp
@@ -0,0 +1,172 @@
@@ -0,0 +1,209 @@
+// NVIDIA Management Library (NVML)
+//
+// https://developer.nvidia.com/management-library-nvml
@ -721,6 +721,7 @@ index 00000000..aa05e9dc
+#include "ggml-impl.h"
+#include <filesystem>
+#include <mutex>
+#include <array>
+
+#ifdef _WIN32
+# define WIN32_LEAN_AND_MEAN
@ -787,6 +788,7 @@ index 00000000..aa05e9dc
+ nvmlReturn_t (*nvmlShutdown)(void);
+ nvmlReturn_t (*nvmlDeviceGetHandleByUUID)(const char *, nvmlDevice_t *);
+ nvmlReturn_t (*nvmlDeviceGetMemoryInfo)(nvmlDevice_t, nvmlMemory_t *);
+ const char * (*nvmlErrorString)(nvmlReturn_t result);
+} nvml { NULL, NULL, NULL, NULL, NULL };
+static std::mutex ggml_nvml_lock;
+
@ -824,7 +826,8 @@ index 00000000..aa05e9dc
+ nvml.nvmlShutdown = (nvmlReturn_enum (*)()) GetProcAddress((HMODULE)(nvml.handle), "nvmlShutdown");
+ nvml.nvmlDeviceGetHandleByUUID = (nvmlReturn_t (*)(const char *, nvmlDevice_t *)) GetProcAddress((HMODULE)(nvml.handle), "nvmlDeviceGetHandleByUUID");
+ nvml.nvmlDeviceGetMemoryInfo = (nvmlReturn_t (*)(nvmlDevice_t, nvmlMemory_t *)) GetProcAddress((HMODULE)(nvml.handle), "nvmlDeviceGetMemoryInfo");
+ if (nvml.nvmlInit_v2 == NULL || nvml.nvmlShutdown == NULL || nvml.nvmlDeviceGetHandleByUUID == NULL || nvml.nvmlDeviceGetMemoryInfo == NULL) {
+ nvml.nvmlErrorString = (const char * (*)(nvmlReturn_enum)) GetProcAddress((HMODULE)(nvml.handle), "nvmlErrorString");
+ if (nvml.nvmlInit_v2 == NULL || nvml.nvmlShutdown == NULL || nvml.nvmlDeviceGetHandleByUUID == NULL || nvml.nvmlDeviceGetMemoryInfo == NULL || nvml.nvmlErrorString == NULL) {
+ GGML_LOG_INFO("%s unable to locate required symbols in NVML.dll", __func__);
+ FreeLibrary((HMODULE)(nvml.handle));
+ nvml.handle = NULL;
@ -833,11 +836,45 @@ index 00000000..aa05e9dc
+
+ SetErrorMode(old_mode);
+
+ nvmlReturn_t status = nvml.nvmlInit_v2();
+ if (status != NVML_SUCCESS) {
+ GGML_LOG_INFO("%s unable to initialize NVML: %s\n", __func__, nvml.nvmlErrorString(status));
+ FreeLibrary((HMODULE)(nvml.handle));
+ nvml.handle = NULL;
+ return status;
+ }
+#else
+ // Not currently wired up on Linux
+ return NVML_ERROR_NOT_SUPPORTED;
+ constexpr std::array<const char*, 2> libPaths = {
+ "/usr/lib/wsl/lib/libnvidia-ml.so.1", // Favor WSL2 path if present
+ "libnvidia-ml.so.1" // On a non-WSL2 system, it should be in the path
+ };
+ for (const char* path : libPaths) {
+ nvml.handle = dlopen(path, RTLD_LAZY);
+ if (nvml.handle) break;
+ }
+ if (nvml.handle == NULL) {
+ GGML_LOG_INFO("%s unable to load libnvidia-ml: %s\n", __func__, dlerror());
+ return NVML_ERROR_NOT_FOUND;
+ }
+ nvml.nvmlInit_v2 = (nvmlReturn_enum (*)()) dlsym(nvml.handle, "nvmlInit_v2");
+ nvml.nvmlShutdown = (nvmlReturn_enum (*)()) dlsym(nvml.handle, "nvmlShutdown");
+ nvml.nvmlDeviceGetHandleByUUID = (nvmlReturn_t (*)(const char *, nvmlDevice_t *)) dlsym(nvml.handle, "nvmlDeviceGetHandleByUUID");
+ nvml.nvmlDeviceGetMemoryInfo = (nvmlReturn_t (*)(nvmlDevice_t, nvmlMemory_t *)) dlsym(nvml.handle, "nvmlDeviceGetMemoryInfo");
+ nvml.nvmlErrorString = (const char * (*)(nvmlReturn_enum)) dlsym(nvml.handle, "nvmlErrorString");
+ if (nvml.nvmlInit_v2 == NULL || nvml.nvmlShutdown == NULL || nvml.nvmlDeviceGetHandleByUUID == NULL || nvml.nvmlDeviceGetMemoryInfo == NULL) {
+ GGML_LOG_INFO("%s unable to locate required symbols in libnvidia-ml.so", __func__);
+ dlclose(nvml.handle);
+ nvml.handle = NULL;
+ return NVML_ERROR_NOT_FOUND;
+ }
+ nvmlReturn_t status = nvml.nvmlInit_v2();
+ if (status != NVML_SUCCESS) {
+ GGML_LOG_INFO("%s unable to initialize NVML: %s\n", __func__, nvml.nvmlErrorString(status));
+ dlclose(nvml.handle);
+ nvml.handle = NULL;
+ return status;
+ }
+#endif
+ int status = nvml.nvmlInit_v2();
+ return NVML_SUCCESS;
+}
+
@ -849,14 +886,14 @@ index 00000000..aa05e9dc
+ }
+ nvmlReturn_enum status = nvml.nvmlShutdown();
+ if (status != NVML_SUCCESS) {
+ GGML_LOG_INFO("%s failed to shutdown NVML: %d\n", __func__, status);
+ GGML_LOG_INFO("%s failed to shutdown NVML: %s\n", __func__, nvml.nvmlErrorString(status));
+ }
+#ifdef _WIN32
+ FreeLibrary((HMODULE)(nvml.handle));
+ nvml.handle = NULL;
+#else
+ // Not currently wired up on Linux
+ dlclose(nvml.handle);
+#endif
+ nvml.handle = NULL;
+}
+
+int ggml_nvml_get_device_memory(const char *uuid, size_t *free, size_t *total) {

51
ml/backend/ggml/ggml/src/mem_nvml.cpp vendored
View File

@ -12,6 +12,7 @@
#include "ggml-impl.h"
#include <filesystem>
#include <mutex>
#include <array>
#ifdef _WIN32
# define WIN32_LEAN_AND_MEAN
@ -78,6 +79,7 @@ struct {
nvmlReturn_t (*nvmlShutdown)(void);
nvmlReturn_t (*nvmlDeviceGetHandleByUUID)(const char *, nvmlDevice_t *);
nvmlReturn_t (*nvmlDeviceGetMemoryInfo)(nvmlDevice_t, nvmlMemory_t *);
const char * (*nvmlErrorString)(nvmlReturn_t result);
} nvml { NULL, NULL, NULL, NULL, NULL };
static std::mutex ggml_nvml_lock;
@ -115,7 +117,8 @@ int ggml_nvml_init() {
nvml.nvmlShutdown = (nvmlReturn_enum (*)()) GetProcAddress((HMODULE)(nvml.handle), "nvmlShutdown");
nvml.nvmlDeviceGetHandleByUUID = (nvmlReturn_t (*)(const char *, nvmlDevice_t *)) GetProcAddress((HMODULE)(nvml.handle), "nvmlDeviceGetHandleByUUID");
nvml.nvmlDeviceGetMemoryInfo = (nvmlReturn_t (*)(nvmlDevice_t, nvmlMemory_t *)) GetProcAddress((HMODULE)(nvml.handle), "nvmlDeviceGetMemoryInfo");
if (nvml.nvmlInit_v2 == NULL || nvml.nvmlShutdown == NULL || nvml.nvmlDeviceGetHandleByUUID == NULL || nvml.nvmlDeviceGetMemoryInfo == NULL) {
nvml.nvmlErrorString = (const char * (*)(nvmlReturn_enum)) GetProcAddress((HMODULE)(nvml.handle), "nvmlErrorString");
if (nvml.nvmlInit_v2 == NULL || nvml.nvmlShutdown == NULL || nvml.nvmlDeviceGetHandleByUUID == NULL || nvml.nvmlDeviceGetMemoryInfo == NULL || nvml.nvmlErrorString == NULL) {
GGML_LOG_INFO("%s unable to locate required symbols in NVML.dll", __func__);
FreeLibrary((HMODULE)(nvml.handle));
nvml.handle = NULL;
@ -124,11 +127,45 @@ int ggml_nvml_init() {
SetErrorMode(old_mode);
nvmlReturn_t status = nvml.nvmlInit_v2();
if (status != NVML_SUCCESS) {
GGML_LOG_INFO("%s unable to initialize NVML: %s\n", __func__, nvml.nvmlErrorString(status));
FreeLibrary((HMODULE)(nvml.handle));
nvml.handle = NULL;
return status;
}
#else
// Not currently wired up on Linux
return NVML_ERROR_NOT_SUPPORTED;
constexpr std::array<const char*, 2> libPaths = {
"/usr/lib/wsl/lib/libnvidia-ml.so.1", // Favor WSL2 path if present
"libnvidia-ml.so.1" // On a non-WSL2 system, it should be in the path
};
for (const char* path : libPaths) {
nvml.handle = dlopen(path, RTLD_LAZY);
if (nvml.handle) break;
}
if (nvml.handle == NULL) {
GGML_LOG_INFO("%s unable to load libnvidia-ml: %s\n", __func__, dlerror());
return NVML_ERROR_NOT_FOUND;
}
nvml.nvmlInit_v2 = (nvmlReturn_enum (*)()) dlsym(nvml.handle, "nvmlInit_v2");
nvml.nvmlShutdown = (nvmlReturn_enum (*)()) dlsym(nvml.handle, "nvmlShutdown");
nvml.nvmlDeviceGetHandleByUUID = (nvmlReturn_t (*)(const char *, nvmlDevice_t *)) dlsym(nvml.handle, "nvmlDeviceGetHandleByUUID");
nvml.nvmlDeviceGetMemoryInfo = (nvmlReturn_t (*)(nvmlDevice_t, nvmlMemory_t *)) dlsym(nvml.handle, "nvmlDeviceGetMemoryInfo");
nvml.nvmlErrorString = (const char * (*)(nvmlReturn_enum)) dlsym(nvml.handle, "nvmlErrorString");
if (nvml.nvmlInit_v2 == NULL || nvml.nvmlShutdown == NULL || nvml.nvmlDeviceGetHandleByUUID == NULL || nvml.nvmlDeviceGetMemoryInfo == NULL) {
GGML_LOG_INFO("%s unable to locate required symbols in libnvidia-ml.so", __func__);
dlclose(nvml.handle);
nvml.handle = NULL;
return NVML_ERROR_NOT_FOUND;
}
nvmlReturn_t status = nvml.nvmlInit_v2();
if (status != NVML_SUCCESS) {
GGML_LOG_INFO("%s unable to initialize NVML: %s\n", __func__, nvml.nvmlErrorString(status));
dlclose(nvml.handle);
nvml.handle = NULL;
return status;
}
#endif
int status = nvml.nvmlInit_v2();
return NVML_SUCCESS;
}
@ -140,14 +177,14 @@ void ggml_nvml_release() {
}
nvmlReturn_enum status = nvml.nvmlShutdown();
if (status != NVML_SUCCESS) {
GGML_LOG_INFO("%s failed to shutdown NVML: %d\n", __func__, status);
GGML_LOG_INFO("%s failed to shutdown NVML: %s\n", __func__, nvml.nvmlErrorString(status));
}
#ifdef _WIN32
FreeLibrary((HMODULE)(nvml.handle));
nvml.handle = NULL;
#else
// Not currently wired up on Linux
dlclose(nvml.handle);
#endif
nvml.handle = NULL;
}
int ggml_nvml_get_device_memory(const char *uuid, size_t *free, size_t *total) {

43
server/sched.go
View File

@ -21,6 +21,7 @@ import (
"github.com/ollama/ollama/format"
"github.com/ollama/ollama/fs/ggml"
"github.com/ollama/ollama/llm"
"github.com/ollama/ollama/logutil"
"github.com/ollama/ollama/ml"
"github.com/ollama/ollama/types/model"
)
@ -645,27 +646,35 @@ func (s *Scheduler) waitForVRAMRecovery(runner *runnerRef, runners []discover.Fi
totalMemoryBefore += gpu.TotalMemory
freeMemoryBefore += gpu.FreeMemory
}
totalMemoryNow := totalMemoryBefore
freeMemoryNow := freeMemoryBefore
go func() {
expiresAt := start.Add(5 * time.Second) // typical convergence is 0.5-1.5s
// typical convergence is 0.5-1.5s - If it takes more than 5 seconds to discover and converge, let the scheduler estimate VRAM usage
ctx, cancel := context.WithTimeout(context.Background(), 5*time.Second)
defer cancel()
ticker := time.NewTicker(250 * time.Millisecond)
defer ticker.Stop()
for {
<-ticker.C
if time.Now().After(expiresAt) {
slog.Warn("gpu VRAM usage didn't recover within timeout", "seconds", time.Since(start).Seconds(), "runner", runner)
finished <- struct{}{}
}
// Query GPUs, look for free to go back up
gpusNow := s.getGpuFn(context.Background(), runners)
var totalMemoryNow, freeMemoryNow uint64
for _, gpu := range gpusNow {
totalMemoryNow += gpu.TotalMemory
freeMemoryNow += gpu.FreeMemory
}
// If we're within ~80% of the estimated memory usage recovered, bail out
if float32(freeMemoryNow-freeMemoryBefore) > float32(runner.vramSize)*0.8 {
slog.Debug(fmt.Sprintf("gpu VRAM free memory converged after %0.2f seconds", time.Since(start).Seconds()), "runner", runner)
select {
case <-ticker.C:
// Query GPUs, look for free to go back up
gpusNow := s.getGpuFn(ctx, runners)
totalMemoryNow = 0
freeMemoryNow = 0
for _, gpu := range gpusNow {
totalMemoryNow += gpu.TotalMemory
freeMemoryNow += gpu.FreeMemory
}
logutil.Trace("gpu VRAM convergence", "percent", int(max(float32(freeMemoryNow-freeMemoryBefore), 0.0)/float32(runner.vramSize)*100))
// If we're within ~75% of the estimated memory usage recovered, bail out
if float32(freeMemoryNow-freeMemoryBefore) > float32(runner.vramSize)*0.75 {
slog.Debug(fmt.Sprintf("gpu VRAM free memory converged after %0.2f seconds", time.Since(start).Seconds()), "free_before", format.HumanBytes2(freeMemoryBefore), "free_now", format.HumanBytes2(freeMemoryNow), "runner", runner)
finished <- struct{}{}
return
}
case <-ctx.Done():
slog.Debug("gpu VRAM usage didn't recover within timeout", "seconds", time.Since(start).Seconds(), "free_before", format.HumanBytes2(freeMemoryBefore), "free_now", format.HumanBytes2(freeMemoryNow), "runner", runner)
finished <- struct{}{}
return
}