GPUBench

Compare GPUs using standard numerical benchmarks in MATLAB.

Description

GPUBENCH times different MATLAB GPU tasks and estimates the peak performance of your GPU in floating-point operations per second (FLOP/s). It produces a detailed HTML report showing how your GPU's performance compares to pre-stored performance results from a range of other GPUs.

Note that this tool is designed for comparing GPU hardware. It does not compare GPU performance across different MATLAB releases.

Requires MATLAB R2011b or above and a GPU with CUDA Compute Capability 1.3 or higher.

• Required Products: Parallel Computing Toolbox; MATLAB
• MATLAB release: MATLAB 7.13 (2011b)
• Other requirements: GPU with CUDA Compute Capability 1.3 or higher.

[Thomas Anthony]

Good benchmark for GPU's

[Tristan Martel]

I've attempted to run benchmark. I have 3 teslas and a quadro in my machine. I noticed that only my fourth GPU was being used at all. The benchmark failed at 19% with the following error:
An unexpected error occurred during CUDA execution. The CUDA error was: CUDA_ERROR_ECC_UNCORRECTABLE.

Error in C:\Program
Files\MATLAB\R2011b\toolbox\distcomp\gpu\+parallel\+internal\+gpu\currentDeviceFreeMem.p>currentDeviceFreeMem
(line 7)

Error in parallel.gpu.CUDADevice/get.FreeMemory (line 107)
                fm = parallel.internal.gpu.currentDeviceFreeMem();

Error in gpuBench>getTestSizes (line 371)
    freeMem = gpu.FreeMemory;

Error in gpuBench>runMTimes (line 163)
sizes = getTestSizes( type, safetyFactor, device );

Error in gpuBench (line 76)
    gpuData = runMTimes( gpuData, reps, 'double', 'GPU', progressTitle, numTasks );

Thanks for your help on this.

[Ben Tordoff]

Hi Tristan,

GPUBench only benchmarks one GPU at a time. Since it just uses the current device, you can use "gpuDevice(n)" to select the nth GPU before calling it. However, NVIDIA's drivers normally default to the most powerful card first, so if you're only getting results for your slowest card that indicates a wider problem. Can you try doing:

>> gpuDeviceCount()

to make sure all four devices are found? You can then try

>> for ii=1:gpuDeviceCount(), gpuDevice(ii), end

to print out the details of all the cards found. You need to make sure all of them have the "DeviceSupported" flag set to 1.

I've never seen the particular error you report, and looking on NVIDIA's forums they say it is most likely caused by a hardware problem and once you hit it you have to reboot to fully flush memory:

http://forums.nvidia.com/index.php?showtopic=204333

That doesn't sound good, I'm afraid!
Let me know how you get on.

Ben

[David Allen]

Hi Ben,

Thanks for the code.

I am getting this error though. I know it is to do with the time-out settings, but don't know what to do from here. My Quadro 1000M does not appear to be speeding up my ffts etc.

Warning: An unexpected error occurred during CUDA execution. The CUDA error was:
CUDA_ERROR_LAUNCH_TIMEOUT.
> In gpuBench at 75
Warning: An unexpected error occurred during CUDA execution. The CUDA error was:
CUDA_ERROR_LAUNCH_TIMEOUT.
> In gpuBench at 75
Warning: An unexpected error occurred during CUDA execution. The CUDA error was:
CUDA_ERROR_LAUNCH_TIMEOUT.
> In gpuBench at 75
An unexpected error occurred during CUDA execution. The CUDA error was:
CUDA_ERROR_LAUNCH_TIMEOUT.

Error in C:\Program
Files\MATLAB\R2011b\toolbox\distcomp\gpu\+parallel\+internal\+gpu\currentDeviceFreeMem.p>currentDeviceFreeMem
(line 7)

Error in parallel.gpu.CUDADevice/get.FreeMemory (line 107)
                fm = parallel.internal.gpu.currentDeviceFreeMem();

Error in gpuBench>getTestSizes (line 371)
    freeMem = gpu.FreeMemory;

Error in gpuBench>runMTimes (line 163)
sizes = getTestSizes( type, safetyFactor, device );

Error in gpuBench (line 76)
    gpuData = runMTimes( gpuData, reps, 'double', 'GPU', progressTitle, numTasks );

Thanks,
Dave

[Narfi]

If you run into CUDA_ERROR_LAUNCH_TIMEOUT, have a look at

http://www.mathworks.com/gputimeout

It explains how to change your system settings to avoid this.