Nvidia Cuda Benchmark

Thank you so much.

Nvidia cuda benchmark. With cuda developers are able to dramatically speed up computing applications by harnessing the power of gpus. 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. 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. Nvidia gpus with nearly 8 000 cuda cores spotted in benchmark database updated and they obliterate the rtx 2080 ti in benchmarks of course by isaiah mayersen on march 4 2020 2 06 81 comments.

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. To make sure the results accurately reflect the average performance of each gpu the chart only includes gpus with at least five unique results in the geekbench browser. The data on this chart is calculated from geekbench 5 results users have uploaded to the geekbench browser. Hi i recently got some new titan x gpus and i hope to do some performance benchmark tests on these gpus.

In gpu accelerated applications the sequential part of the workload runs on the cpu which is optimized for single threaded performance. 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. Cuda is a parallel computing platform and programming model developed by nvidia for general computing on graphical processing units gpus.

Here are a couple cuda benchmarks that ran gracefully under wsl2 albeit the performance leaves a lot to be desired. Welcome to the geekbench cuda benchmark chart.