Nvidia Cuda Kernel

The windows insider sdk supports running existing ml tools libraries and popular frameworks that use nvidia cuda for gpu hardware acceleration inside a wsl 2 instance.

Nvidia cuda kernel. Profiler this is the guide to the profiler. Overview and live demo of the latest debugging features available in nvidia nsight visual studio edition. It can be as simple as converting a loop into a cuda kernel using cuda c. The nvidia nsight compute is the next generation interactive kernel profiler for cuda applications.

It provides detailed performance metrics and api debugging via a user interface and command line tool. Since most algorithms start off as serial algorithms it s often trivial to port programs to the cuda architecture. The gpu takes this kernel and executes it in parallel by launching thousands of instances across many processors in the gpu. Gpu technology conference 2013.

This post is a super simple introduction to cuda the popular parallel computing platform and programming model from nvidia. Cuda compute unified device architecture is a parallel computing platform and application programming interface api model created by nvidia. We can use the profiler to measure the time taken to be 2 9μs where we are running on an nvidia tesla v100 gpu using cuda 10 1 and we have. It allows software developers and software engineers to use a cuda enabled graphics processing unit gpu for general purpose processing an approach termed gpgpu general purpose computing on graphics processing units.

Debugging cuda kernel code with nvidia nsight visual studio edition author. A kernel is defined using the global declaration specifier and the number of cuda threads that execute that kernel for a given kernel call is specified using a new. Cuda binary utilities the application notes for cuobjdump nvdisasm and nvprune. Cuda c extends c by allowing the programmer to define c functions called kernels that when called are executed n times in parallel by n different cuda threads as opposed to only once like regular c functions.

I wrote a previous easy introduction to cuda in 2013 that has been very popular over the years. 2 minutes to read.