Why Does SYCL Have Different Implementations, and What Version to Use for GPGPU Computing(With Slower CPU Mode for Testing/No Gpu Machines)?

This page summarizes the projects mentioned and recommended in the original post on /r/gpgpu
Sycl Opencl gpu-computing Intel Llvm

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  • AdaptiveCpp

    Implementation of SYCL and C++ standard parallelism for CPUs and GPUs from all vendors: The independent, community-driven compiler for C++-based heterogeneous programming models. Lets applications adapt themselves to all the hardware in the system - even at runtime!

    • See https://github.com/illuhad/hipSYCL - hardware support is clearly described ;) * Any CPU * AMD GPUs * NVIDIA GPUs * Intel GPUs (highly experimental)

  • llvm

    Intel staging area for llvm.org contribution. Home for Intel LLVM-based projects. (by intel)

    • Intel LLVM SYCL oneAPI DPC++ - an open source implementation of SYCL that is being contributed to the LLVM project

  • WorkOS

    The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

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  • triSYCL

    Generic system-wide modern C++ for heterogeneous platforms with SYCL from Khronos Group

    • triSYCL - an open-source implementation led by Xilinx

  • featuresupport

    • See also https://github.com/hipSYCL/featuresupport

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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