ccminer/nvml.h

/*
 * A trivial little dlopen()-based wrapper library for the
 * NVIDIA NVML library, to allow runtime discovery of NVML on an
 * arbitrary system.  This is all very hackish and simple-minded, but
 * it serves my immediate needs in the short term until NVIDIA provides
 * a static NVML wrapper library themselves, hopefully in
 * CUDA 6.5 or maybe sometime shortly after.
 *
 * This trivial code is made available under the "new" 3-clause BSD license,
 * and/or any of the GPL licenses you prefer.
 * Feel free to use the code and modify as you see fit.
 *
 * John E. Stone - john.stone@gmail.com
 *
 */

/*
 * Ugly hacks to avoid dependencies on the real nvml.h until it starts
 * getting included with the CUDA toolkit or a GDK that's got a known
 * install location, etc.
 */
typedef enum wrap_nvmlReturn_enum {
	WRAPNVML_SUCCESS = 0
} wrap_nvmlReturn_t;

typedef void * wrap_nvmlDevice_t;

/* our own version of the PCI info struct */
typedef struct {
	char bus_id_str[16];             /* string form of bus info */
	unsigned int domain;
	unsigned int bus;
	unsigned int device;
	unsigned int pci_device_id;      /* combined device and vendor id */
	unsigned int pci_subsystem_id;
	unsigned int res0;               /* NVML internal use only */
	unsigned int res1;
	unsigned int res2;
	unsigned int res3;
} wrap_nvmlPciInfo_t;

typedef enum nvmlClockType_t {
NVML_CLOCK_GRAPHICS = 0,
NVML_CLOCK_SM = 1,
NVML_CLOCK_MEM = 2
} wrap_nvmlClockType_t;

/*
 * Handle to hold the function pointers for the entry points we need,
 * and the shared library itself.
 */
typedef struct {
	void *nvml_dll;
	int nvml_gpucount;
	int cuda_gpucount;
	unsigned int *nvml_pci_domain_id;
	unsigned int *nvml_pci_bus_id;
	unsigned int *nvml_pci_device_id;
	unsigned int *nvml_pci_subsys_id;
	int *nvml_cuda_device_id;          /* map NVML dev to CUDA dev */
	int *cuda_nvml_device_id;          /* map CUDA dev to NVML dev */
	wrap_nvmlDevice_t *devs;
	wrap_nvmlReturn_t (*nvmlInit)(void);
	wrap_nvmlReturn_t (*nvmlDeviceGetCount)(int *);
	wrap_nvmlReturn_t (*nvmlDeviceGetHandleByIndex)(int, wrap_nvmlDevice_t *);
	wrap_nvmlReturn_t (*nvmlDeviceGetClockInfo)(wrap_nvmlDevice_t, wrap_nvmlClockType_t, unsigned int *);
	wrap_nvmlReturn_t (*nvmlDeviceGetApplicationsClock)(wrap_nvmlDevice_t, wrap_nvmlClockType_t, unsigned int *);
	wrap_nvmlReturn_t (*nvmlDeviceGetPciInfo)(wrap_nvmlDevice_t, wrap_nvmlPciInfo_t *);
	wrap_nvmlReturn_t (*nvmlDeviceGetName)(wrap_nvmlDevice_t, char *, int);
	wrap_nvmlReturn_t (*nvmlDeviceGetTemperature)(wrap_nvmlDevice_t, int, unsigned int *);
	wrap_nvmlReturn_t (*nvmlDeviceGetFanSpeed)(wrap_nvmlDevice_t, unsigned int *);
	wrap_nvmlReturn_t (*nvmlDeviceGetPerformanceState)(wrap_nvmlDevice_t, int *); /* enum */
	wrap_nvmlReturn_t (*nvmlDeviceGetPowerUsage)(wrap_nvmlDevice_t, unsigned int *);
	char* (*nvmlErrorString)(wrap_nvmlReturn_t);
	wrap_nvmlReturn_t (*nvmlShutdown)(void);
} wrap_nvml_handle;


wrap_nvml_handle * wrap_nvml_create();
int wrap_nvml_destroy(wrap_nvml_handle *nvmlh);

/*
 * Query the number of GPUs seen by NVML
 */
int wrap_nvml_get_gpucount(wrap_nvml_handle *nvmlh, int *gpucount);

/*
 * Query the number of GPUs seen by CUDA
 */
int wrap_cuda_get_gpucount(wrap_nvml_handle *nvmlh, int *gpucount);


/*
 * query the name of the GPU model from the CUDA device ID
 *
 */
int wrap_nvml_get_gpu_name(wrap_nvml_handle *nvmlh,
                           int gpuindex,
                           char *namebuf,
                           int bufsize);

/*
 * Query the current GPU temperature (Celsius), from the CUDA device ID
 */
int wrap_nvml_get_tempC(wrap_nvml_handle *nvmlh,
                        int gpuindex, unsigned int *tempC);

/*
 * Query the current GPU fan speed (percent) from the CUDA device ID
 */
int wrap_nvml_get_fanpcnt(wrap_nvml_handle *nvmlh,
                          int gpuindex, unsigned int *fanpcnt);

/*
 * Query the current GPU power usage in millwatts from the CUDA device ID
 *
 * This feature is only available on recent GPU generations and may be
 * limited in some cases only to Tesla series GPUs.
 * If the query is run on an unsupported GPU, this routine will return -1.
 */
int wrap_nvml_get_power_usage(wrap_nvml_handle *nvmlh,
                              int gpuindex,
                              unsigned int *milliwatts);

/* nvapi functions */
#ifdef WIN32
int wrap_nvapi_init();
#endif

/* api functions */

#include "miner.h"

#ifdef USE_WRAPNVML

int gpu_fanpercent(struct cgpu_info *gpu);
float gpu_temp(struct cgpu_info *gpu);
unsigned int gpu_power(struct cgpu_info *gpu);
unsigned int gpu_usage(struct cgpu_info *gpu);
int gpu_pstate(struct cgpu_info *gpu);
int gpu_busid(struct cgpu_info *gpu);

int gpu_nvids(struct cgpu_info *gpu);
int gpu_info(struct cgpu_info *gpu);

#endif

// cuda api based
int gpu_clocks(struct cgpu_info *gpu);