It may seem natural to expect that the performance of your CPU-to-GPU port will range below that of a dedicated HPC code. After all, you are limited by the constraints of the software architecture, the established API, and the need to account for sophisticated extra features expected by the user base. Not only that, the simplistic programming model of C++ standard parallelism allows for less…
]]>The difficulty of porting an application to GPUs varies from one case to another. In the best-case scenario, you can accelerate critical code sections by calling into an existing GPU-optimized library. This is, for example, when the building blocks of your simulation software consist of BLAS linear algebra functions, which can be accelerated using cuBLAS. This is the second post in the…
]]>