Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Cuda version #9

Closed
trinayan opened this issue May 6, 2017 · 6 comments
Closed

Cuda version #9

trinayan opened this issue May 6, 2017 · 6 comments

Comments

@trinayan
Copy link

trinayan commented May 6, 2017

Hi,

Which cuda version is required to run these benchmarks? Also since there is cuda-U version I believe it is possible to run those on the jetson boards?

Best,
Trinayan

@el1goluj
Copy link
Member

el1goluj commented May 7, 2017

Hi Trinayan,

CUDA-D runs on every NVIDIA GPU (c.c.>=2.0) and CUDA version (tested on CUDA 7.5). For CUDA-U, you will need NVIDIA Pascal and CUDA 8.0.

Best regards,
Juan

@trinayan
Copy link
Author

Thanks for that. Just wondering about the performance metrics which is shown at the end. Is the kernel time the sum of executions on both devices or only on the gpu? I think it is both device from the code but just wanted to confirm.

@el1goluj
Copy link
Member

The kernel time measurements in our ISPASS paper include CPU and GPU execution. Keep in mind that the execution on both devices is concurrent.
If you have more specific questions, please let us know.

@trinayan
Copy link
Author

Thanks a lot. I wanted to know about the default partitioning options in each benchmark. Did you like try different options and made the ones which gave the best performance as default or was it based on other decision? Thank you

@lchang20
Copy link

The default partitioning option (-a, and default as 0.2) for data partitioning benchmarks are NOT the ones giving the best performance. It is arbitrarily preset to a reasonable value for one internal device. The benchmarks are written to evaluate multiple devices, so different data sets, languages, or devices might have different best partitions. To find the best, you can either sample different values, or enable dynamic partitioning (by giving "-a" a value not between 0.0 and 1.0).

@trinayan
Copy link
Author

Ok thank you very much

@trinayan trinayan closed this as completed Jun 5, 2017
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

3 participants