# Issues running CUDA on GPU cluster

**URL:** <https://forums.developer.nvidia.com/t/issues-running-cuda-on-gpu-cluster/47951>\
**Category:** CUDA Programming and Performance\
**Created:** [February 17, 2017, 4:26pm UTC](https://forums.developer.nvidia.com/t/issues-running-cuda-on-gpu-cluster/47951 "2017-02-17T16:26:18Z")\
**Posts on this page:** 4\
**Page:** 1

<div class="post-metadata">

**Author:** ![u-sandu](https://sea2.discourse-cdn.com/nvidia/user_avatar/forums.developer.nvidia.com/u-sandu/32/22947_2.png) [@u-sandu](https://forums.developer.nvidia.com/u/u-sandu)\
**Post date:** [February 17, 2017, 4:26pm UTC](https://forums.developer.nvidia.com/t/issues-running-cuda-on-gpu-cluster/47951/1 "2017-02-17T16:26:18Z")

</div>

I am very new to CUDA.

I have tried to execute the following program (from Udacity, lesson 1):

```auto
#include <iostream>

__global__ void cube(float * d_out, float * d_in) {
	int idx = threadIdx.x;
	float f = d_in[idx];
	d_out[idx] = f*f*f;
}

int main(int argc, char *argv[]) {
	const int ARRAY_SIZE = 64;
	const int ARRAY_BYTES = ARRAY_SIZE * sizeof(float);

	// generate the input array on the host
	float h_in[ARRAY_SIZE];
	for (int i = 0; i < ARRAY_SIZE; i++) {
		h_in[i] = float(i);
	}
	float h_out[ARRAY_SIZE];

	// declare GPU memory pointers
	float * d_in;
	float * d_out;

	// allocate GPU memory
	cudaMalloc((void**)&d_in, ARRAY_BYTES);
	cudaMalloc((void**)&d_out, ARRAY_BYTES);

	// transfer the array to the GPU
	cudaMemcpy(d_in, h_in, ARRAY_BYTES, cudaMemcpyHostToDevice);

	// launch the kernel
	cube <<<1, ARRAY_SIZE>>>(d_out, d_in);

	// copy back the result array to the CPU
	cudaMemcpy(h_out, d_out, ARRAY_BYTES, cudaMemcpyDeviceToHost);

	// print out the resulting array
	for (int i = 0; i < ARRAY_SIZE; i++) {
		std::cout << h_out[i];
		std::cout << (((i%4)!=3)?"\t":"\n");		
	}

	cudaFree(d_in);
	cudaFree(d_out);

	return 0;
}

```

I don’t have CUDA installed on my machine, but I have tried run it on my uni’s GPU clusters.

It runs OK on this cluster:

Model  
HP SL390 G7  
Processors  
Two INTEL X5650 @ 2.66 GHz, 6 cores, 48GB  
Two NVDIA Tesla M2090 @ 650 MHz, 512 cores, 6GB

However, I couldn’t manage to run on another one. More precisely, it runs, but gives me only zeros (or numbers such as 8.68805e-44).

I have tried to identify the reason. But I couldn’t find it.  
Any suggestion will be highly valued.

To help you assess what am I dealing with, I’ll be running the commands on the desired cluster node from this link:  
[http://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#axzz4YxAZvHxk](http://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#axzz4YxAZvHxk)

$ lspci | grep -i nvidia  
02:00.0 3D controller: NVIDIA Corporation GK110GL [Tesla K20m] (rev a1)  
84:00.0 3D controller: NVIDIA Corporation GK110GL [Tesla K20m] (rev a1)

$ uname -m && cat /etc/\*release  
x86\_64  
CentOS release 6.8 (Final)  
LSB\_VERSION=base-4.0-amd64:base-4.0-ia32:base-4.0-noarch:core-4.0-amd64:core-4.0-ia32:core-4.0-noarch:graphics-4.0-amd64:graphics-4.0-ia32:graphics-4.0-noarch:printing-4.0-amd64:printing-4.0-ia32:printing-4.0-noarch  
CentOS release 6.8 (Final)  
CentOS release 6.8 (Final)

$ gcc --version  
gcc (GCC) 4.4.7 20120313 (Red Hat 4.4.7-17)  
Copyright (C) 2010 Free Software Foundation, Inc.  
This is free software; see the source for copying conditions. There is NO  
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

$ uname -r  
2.6.32-642.13.1.el6.x86\_64

---

<div class="post-metadata">

**Author:** ![Robert\_Crovella](https://sea2.discourse-cdn.com/nvidia/user_avatar/forums.developer.nvidia.com/robert_crovella/32/14043_2.png) [@Robert\_Crovella](https://forums.developer.nvidia.com/u/Robert_Crovella)\
**Post date:** [February 17, 2017, 4:59pm UTC](https://forums.developer.nvidia.com/t/issues-running-cuda-on-gpu-cluster/47951/2 "2017-02-17T16:59:10Z")

</div>

Add proper cuda error checking to your code, and run your code with cuda-memcheck

Don’t know what those are? Google each.

---

<div class="post-metadata">

**Author:** ![u-sandu](https://sea2.discourse-cdn.com/nvidia/user_avatar/forums.developer.nvidia.com/u-sandu/32/22947_2.png) [@u-sandu](https://forums.developer.nvidia.com/u/u-sandu)\
**Post date:** [February 18, 2017, 7:39am UTC](https://forums.developer.nvidia.com/t/issues-running-cuda-on-gpu-cluster/47951/3 "2017-02-18T07:39:08Z")

</div>

Here is the result:

Ran cube: no CUDA-capable device is detected  
Sync: no CUDA-capable device is detected

Doesn’t make much sense to me. As I have showed above, running:  
$ lspci | grep -i nvidia  
gives:  
02:00.0 3D controller: NVIDIA Corporation GK110GL [Tesla K20m] (rev a1)  
84:00.0 3D controller: NVIDIA Corporation GK110GL [Tesla K20m] (rev a1)

---

<div class="post-metadata">

**Author:** ![Robert\_Crovella](https://sea2.discourse-cdn.com/nvidia/user_avatar/forums.developer.nvidia.com/robert_crovella/32/14043_2.png) [@Robert\_Crovella](https://forums.developer.nvidia.com/u/Robert_Crovella)\
**Post date:** [February 18, 2017, 2:50pm UTC](https://forums.developer.nvidia.com/t/issues-running-cuda-on-gpu-cluster/47951/4 "2017-02-18T14:50:20Z")

</div>

The CUDA install on that machine is broken.

Refer to the linux install guide:

[url][Installation Guide Linux :: CUDA Toolkit Documentation](http://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#abstract%5B/url%5D)

read it in its entirety. Perform all necessary steps, including validation, before trying to run your own codes.