I recently migrated a lot of my CUDA code to SYCL using Intel's compatibility tool [1]. I'm trying to get my applications to work irregardless of hardware, so i

I recently migrated a lot of my CUDA code to SYCL using Intel's compatibility tool [1]. I'm trying to get my applications to work irregardless of hardware, so it simply needed to be done despite the pain. It actually wasn't as hard as I was expecting. Don't get me wrong, it will definitely depend on the size of your code base as to how effective of a tool it is. However, I managed to port over most of mine in the course of the month, and it's showing dividends now I'm making back performance gains using FPGA hardware acceleration. I'm now vendor neutral, and can run my code on team Red, Blue, or Green. I'd argue that heterogeneous computing is a good enough reason to make the switch. [1]https://www.intel.com/content/www/us/en/develop/documentation/oneapi-programming-guide/top/software-development-process/migrating-code-to-dpcpp/migrating-from-cuda-to-dpcpp.html https://www.intel.com/content/www/us/en/develop/documentatio... [2]https://www.khronos.org/sycl/ https://www.khronos.org/sycl/