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Even now, Thrust as a dependency is one of the main reason why we have a #CUDA backend, a #HIP / #ROCm backend and a pure #CPU backend in #GPUSPH, but not a #SYCL or #OneAPI backend (which would allow us to extend hardware support to #Intel GPUs). <doi.org/10.1002/cpe.8313>

This is also one of the reason why we implemented our own #BLAS routines when we introduced the semi-implicit integrator. A side-effect of this choice is that it allowed us to develop the improved #BiCGSTAB that I've had the opportunity to mention before <doi.org/10.1016/j.jcp.2022.111>. Sometimes I do wonder if it would be appropriate to “excorporate” it into its own library for general use, since it's something that would benefit others. OTOH, this one was developed specifically for GPUSPH and it's tightly integrated with the rest of it (including its support for multi-GPU), and refactoring to turn it into a library like cuBLAS is

a. too much effort
b. probably not worth it.

Again, following @eniko's original thread, it's really not that hard to roll your own, and probably less time consuming than trying to wrangle your way through an API that may or may not fit your needs.

6/

I'm getting the material ready for my upcoming #GPGPU course that starts on March. Even though I most probably won't get to it,I also checked my trivial #SYCL programs. Apparently the 2025.0 version of the #Intel #OneAPI #DPCPP runtime doesn't like any #OpenCL platform except Intel's own (I have two other platforms that support #SPIRV, so why aren't they showing up? From the documentation I can find online this should be sufficient, but apparently it's not …)

Just how deep is #Nvidia's #CUDA moat really?
Not as impenetrable as you might think, but still more than Intel or AMD would like
It's not enough just to build a competitive part: you also have to have #software that can harness all those #FLOPS — something Nvidia has spent the better part of two decades building with its CUDA runtime, while competing frameworks for low-level #GPU #programming are far less mature like AMD's #ROCm or Intel's #OneAPI.
theregister.com/2024/12/17/nvi #developers

The Register · Just how deep is Nvidia's CUDA moat really?By Tobias Mann

Howdy all - registrations are still open for the first oneAPI DevSummit hosted by the UXL Foundation! Learn about GPGPU programming, oneAPI and how companies are coalescing around #oneapi / #sycl
linuxfoundation.regfox.com/one

Registration will closeat 5pm today. The DevSummit will start at 8pm PT or 8:30am IST. See you there!

linuxfoundation.regfox.comoneAPI DevSummit hosted by UXL FoundationGet registered online for oneAPI DevSummit hosted by UXL Foundation here.

James Reinders et al. have released the second edition of their SYCL book "Data Parallel C++", available for free in PDF and EPUB: link.springer.com/book/10.1007

"SYCL is a royalty-free open standard developed by the Khronos Group that allows developers to program heterogeneous architectures [such as CPUs, GPUs, and FPGAs] in standard C++."

SpringerLinkData Parallel C++This open access book teaches data-parallel programming using C++ with SYCL and walks through everything needed to program accelerated systems.
#SYCL#Cpp#HPC