Gold, Silver and Bronze

Kernels of course! :)

Most of the readers of this blog should be familiar with a "Gold" kernel in which your data is processed on the CPU (usually) and the output is carefully checked. This kernel and its associated outputs form the basis of the regression testing of subsequent implementations on the GPU including algorithmic optimizations.

Personally I like most of my gold kernels to be naive implementations of an algorithm. This causes them to be  easily verifiable and usually easy to debug if there is a problem.

If you currently don't implement a Gold kernel before writing your CUDA implementations and/or adapting you algorithm I strongly suggest you do.

The purpose of this post is to suggest two other debugging techniques I use when needed and where possible. I call them my Silver and Bronze kernels.

A Silver kernel is implemented on the GPU without any optimizations or algorithmic enhancements. The grid / block structure is as simple as possible making sure we don't vary from the Gold kernels implementation too much - only unwinding the loops into grid/blocks is allowed where possible. This type of kernel I use when I am writing something that depends on numerical precision. Once written and verified within acceptable numerical limits against the Gold kernel it becomes the new baseline kernel before later optimizations. This allows exact matching of later kernel outputs rather than using an "acceptable deviation" approach.