Cannot dynamic link nvidia-ml and use gonvml at the same time #8
Description
example failed to query device count:
package main
// #cgo LDFLAGS: -ldl -lnvidia-ml
// #cgo CFLAGS: -I /usr/local/cuda-8.0/include
/*
#include <stdio.h>
#include "nvml.h"
void testNvml()
{
nvmlReturn_t result;
unsigned int device_count, i;
// First initialize NVML library
result = nvmlInit();
if (NVML_SUCCESS != result)
{
printf("Failed to initialize NVML: %s\n", nvmlErrorString(result));
return;
}
result = nvmlDeviceGetCount(&device_count);
if (NVML_SUCCESS != result)
{
printf("Failed to query device count: %s\n", nvmlErrorString(result));
return;
}
printf("Found %d device%s\n\n", device_count, device_count != 1 ? "s" : "");
}
*/
import "C"
import (
"fmt"
"github.com/mindprince/gonvml"
)
func testGoNvml() (value []string) {
err := gonvml.Initialize()
if err != nil {
return
}
defer func() { _ = gonvml.Shutdown() }()
n, err := gonvml.DeviceCount()
if err != nil {
panic(err)
}
fmt.Println("testGoNvml gpu num:", n)
return
}
func main() {
C.testNvml()
testGoNvml()
C.testNvml()
}output:
Failed to query device count: nvmlErrorString Function Not Found
testGoNvml gpu num: 8
Found 8 devices
example ok
package main
// #cgo LDFLAGS: -ldl -lnvidia-ml
// #cgo CFLAGS: -I /usr/local/cuda-8.0/include
/*
#include <stdio.h>
#include "nvml.h"
void testNvml()
{
nvmlReturn_t result;
unsigned int device_count, i;
// First initialize NVML library
result = nvmlInit();
if (NVML_SUCCESS != result)
{
printf("Failed to initialize NVML: %s\n", nvmlErrorString(result));
return;
}
result = nvmlDeviceGetCount(&device_count);
if (NVML_SUCCESS != result)
{
printf("Failed to query device count: %s\n", nvmlErrorString(result));
return;
}
printf("Found %d device%s\n\n", device_count, device_count != 1 ? "s" : "");
}
*/
import "C"
func main() {
C.testNvml()
}output:
Found 8 devices
This is a simple example, actually a possible situation:
a complex golang program import package a and b
package a import gonvml
package b call libnvidia-xxx use cgo
libnvidia-xxx dynamic link libnvidia-ml