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Dynamically load NVML

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romner-set 2023-06-01 03:41:56 +02:00
parent 547f17dda3
commit b2df0696fd
2 changed files with 81 additions and 29 deletions
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9
Makefile
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@ -120,15 +120,6 @@ ifeq ($(PLATFORM_LC),linux)
THREADS := $(shell getconf _NPROCESSORS_ONLN 2>/dev/null || echo 1)
SU_GROUP := root
ifneq ($(NO_GPU),true)
ifeq ($(shell find /usr/local/cuda/include/ -type f -name nvml.h >/dev/null 2>&1; echo $$?),0)
GPUCXXFLAGS := -I/usr/local/cuda/include
GPULDFLAGS := -L/usr/local/cuda/lib -lnvidia-ml
override ADDFLAGS += -DGPU_NVIDIA
else ifeq ($(shell find /opt/cuda/include/ -type f -name nvml.h >/dev/null 2>&1; echo $$?),0)
GPUCXXFLAGS := -I/opt/cuda/include
GPULDFLAGS := -L/opt/cuda/lib -lnvidia-ml
override ADDFLAGS += -DGPU_NVIDIA
endif
ifeq ($(shell find /opt/rocm/include/rocm_smi/ -type f -name rocm_smi.h >/dev/null 2>&1; echo $$?),0)
GPUCXXFLAGS += -I/opt/rocm/include
GPULDFLAGS += -L/opt/rocm/lib -lrocm_smi64

101
src/linux/btop_collect.cpp
View file

@ -28,9 +28,7 @@ tab-size = 4
#include <ifaddrs.h>
#include <net/if.h>
#include <arpa/inet.h> // for inet_ntop()
#if defined(GPU_NVIDIA)
#include <nvml.h>
#endif
#include <dlfcn.h>
#if defined(GPU_AMD)
#include <rocm_smi/rocm_smi.h>
#endif
@ -108,13 +106,51 @@ namespace Gpu {
//? NVIDIA data collection
namespace Nvml {
// NVML defines, structs & typedefs
#define NVML_DEVICE_NAME_BUFFER_SIZE 64
#define NVML_SUCCESS 0
#define NVML_TEMPERATURE_THRESHOLD_SHUTDOWN 0
#define NVML_CLOCK_GRAPHICS 0
#define NVML_CLOCK_MEM 2
#define NVML_TEMPERATURE_GPU 0
#define NVML_PCIE_UTIL_TX_BYTES 0
#define NVML_PCIE_UTIL_RX_BYTES 1
typedef void* nvmlDevice_t; // we won't be accessing any of the underlying struct's properties, so this is fine
typedef int nvmlReturn_t, // enums are basically ints
nvmlTemperatureThresholds_t,
nvmlClockType_t,
nvmlPstates_t,
nvmlTemperatureSensors_t,
nvmlPcieUtilCounter_t;
struct nvmlUtilization_t {unsigned int gpu, memory;};
struct nvmlMemory_t {unsigned long long total, free, used;};
//? Function pointers
const char* (*nvmlErrorString)(nvmlReturn_t);
nvmlReturn_t (*nvmlInit)();
nvmlReturn_t (*nvmlShutdown)();
nvmlReturn_t (*nvmlDeviceGetCount)(unsigned int*);
nvmlReturn_t (*nvmlDeviceGetHandleByIndex)(unsigned int, nvmlDevice_t*);
nvmlReturn_t (*nvmlDeviceGetName)(nvmlDevice_t, char*, unsigned int);
nvmlReturn_t (*nvmlDeviceGetPowerManagementLimit)(nvmlDevice_t, unsigned int*);
nvmlReturn_t (*nvmlDeviceGetTemperatureThreshold)(nvmlDevice_t, nvmlTemperatureThresholds_t, unsigned int*);
nvmlReturn_t (*nvmlDeviceGetUtilizationRates)(nvmlDevice_t, nvmlUtilization_t*);
nvmlReturn_t (*nvmlDeviceGetClockInfo)(nvmlDevice_t, nvmlClockType_t, unsigned int*);
nvmlReturn_t (*nvmlDeviceGetPowerUsage)(nvmlDevice_t, unsigned int*);
nvmlReturn_t (*nvmlDeviceGetPowerState)(nvmlDevice_t, nvmlPstates_t*);
nvmlReturn_t (*nvmlDeviceGetTemperature)(nvmlDevice_t, nvmlTemperatureSensors_t, unsigned int*);
nvmlReturn_t (*nvmlDeviceGetMemoryInfo)(nvmlDevice_t, nvmlMemory_t*);
nvmlReturn_t (*nvmlDeviceGetPcieThroughput)(nvmlDevice_t, nvmlPcieUtilCounter_t, unsigned int*);
//? Actual data
void* nvml_dl_handle;
bool initialized = false;
bool init();
bool shutdown();
template <bool is_init> bool collect(gpu_info* gpus_slice);
#if defined(GPU_NVIDIA)
vector<nvmlDevice_t> devices;
#endif
unsigned int device_count = 0;
}
@ -876,9 +912,45 @@ namespace Gpu {
//? NVIDIA
namespace Nvml {
bool init() {
#if defined(GPU_NVIDIA)
if (initialized) return false;
//? Dynamic loading & linking
nvml_dl_handle = dlopen("libnvidia-ml.so", RTLD_LAZY);
if (!nvml_dl_handle) {
Logger::info(std::string("Failed to load libnvidia-ml.so, NVIDIA GPUs will not be detected: ") + dlerror());
return false;
}
auto load_nvml_sym = [&](const char sym_name[]) {
auto sym = dlsym(nvml_dl_handle, sym_name);
auto err = dlerror();
if (err != NULL) {
Logger::error(string("NVML: Couldn't find function ") + sym_name + ": " + err);
return (void*)nullptr;
} else return sym;
};
#define LOAD_SYM(NAME) if ((NAME = (decltype(NAME))load_nvml_sym(#NAME)) == nullptr) return false
LOAD_SYM(nvmlErrorString);
LOAD_SYM(nvmlInit);
LOAD_SYM(nvmlShutdown);
LOAD_SYM(nvmlDeviceGetCount);
LOAD_SYM(nvmlDeviceGetHandleByIndex);
LOAD_SYM(nvmlDeviceGetName);
LOAD_SYM(nvmlDeviceGetPowerManagementLimit);
LOAD_SYM(nvmlDeviceGetTemperatureThreshold);
LOAD_SYM(nvmlDeviceGetUtilizationRates);
LOAD_SYM(nvmlDeviceGetClockInfo);
LOAD_SYM(nvmlDeviceGetPowerUsage);
LOAD_SYM(nvmlDeviceGetPowerState);
LOAD_SYM(nvmlDeviceGetTemperature);
LOAD_SYM(nvmlDeviceGetMemoryInfo);
LOAD_SYM(nvmlDeviceGetPcieThroughput);
#undef LOAD_SYM
//? Function calls
nvmlReturn_t result = nvmlInit();
if (result != NVML_SUCCESS) {
Logger::warning(std::string("Failed to initialize NVML, NVIDIA GPUs will not be detected: ") + nvmlErrorString(result));
@ -904,28 +976,21 @@ namespace Gpu {
return true;
} else {initialized = true; shutdown(); return false;}
#else
return false;
#endif
}
bool shutdown() {
#if defined(GPU_NVIDIA)
if (!initialized) return false;
nvmlReturn_t result = nvmlShutdown();
if (NVML_SUCCESS == result)
if (NVML_SUCCESS == result) {
initialized = false;
else Logger::warning(std::string("Failed to shutdown NVML: ") + nvmlErrorString(result));
dlclose(nvml_dl_handle);
} else Logger::warning(std::string("Failed to shutdown NVML: ") + nvmlErrorString(result));
return !initialized;
#else
return false;
#endif
}
template <bool is_init> // collect<1> is called in Nvml::init(), and populates gpus.supported_functions
bool collect(gpu_info* gpus_slice) { // raw pointer to vector data, size == device_count
#if defined(GPU_NVIDIA)
if (!initialized) return false;
nvmlReturn_t result;
@ -1090,10 +1155,6 @@ namespace Gpu {
}
return true;
#else
(void)gpus_slice;
return false;
#endif
}
}