Nvidia Benchmark Cuda

For microsoft platforms nvidia s cuda driver supports directx.

Nvidia benchmark cuda. With cuda developers are able to dramatically speed up computing applications by harnessing the power of gpus. Here are a couple cuda benchmarks that ran gracefully under wsl2 albeit the performance leaves a lot to be desired. I chose a weak scaling benchmark with a communication reducing 2d domain decomposition to avoid constructing an artificial benchmark just to show off cuda aware mpi. Nvidia management library nvml apis are not supported.

In gpu accelerated applications the sequential part of the workload runs on the cpu which is optimized for single threaded performance. Hi i recently got some new titan x gpus and i hope to do some performance benchmark tests on these gpus. Thank you so much. For the same reason i chose a domain size of 4k by 4k because this problem size demonstrates strong performance in the single gpu version.

Although the cuda cores in a gpu are similar in performance to the cores in the cpu there is a huge difference in the power each core possesses. Cuda is a parallel computing platform and programming model developed by nvidia for general computing on graphical processing units gpus. Few cuda samples for windows demonstrates cuda directx12 interoperability for building such samples one needs to install windows 10 sdk or higher with vs 2015 or vs 2017. Switching to the latest fast ring windows 10 insider preview builds paired with the latest nvidia windows driver and then installing cuda within wsl2 can yield working gpu based cuda compute support.

Julia on the cpu is known for its good performance approaching that of statically compiled languages like c. The same holds for programming nvidia gpus with kernels written using cuda jl where we have shown the performance to approach and even sometimes exceed that of cuda c on a selection 1 of applications from the rodinia. The primary set of functionality in the library focuses on image processing and is widely applicable for developers in these areas. Note that nvidia container toolkit does not yet support docker desktop wsl 2 backend.

I m wondering what are the standard benchmark tests that people usually do and where can i find the testing programs and the expected performance numbers. Similarly an nvidia gpu with more cuda cores has more parallel processors and can perform more complex tasks and shows better performance than a gpu with fewer cuda cores. Nvidia npp is a library of functions for performing cuda accelerated 2d image and signal processing. Performance has not yet been tuned on the preview driver.

Released july 3 2010 originally released for.