SYCL for CUDA Developers

SYCL, like CUDA, offers developers the ability to write "single-source" C++ code that can be deployed and executed on parallel hardware architectures.

The guide in this section has been created to help CUDA developers understand the similarities and differences between CUDA and SYCL, and how they can transition their code to SYCL. The document assumes that you already know C++ and are proficient in CUDA, but we aim to offer a high level explanation of CUDA concepts and offer links to relevant documentation whenever possible.

The guide consists of various sections that will help you:

These resources are based on the OpenCL 1.2 and SYCL 1.2.1 specifications. CUDA 9 is used as the reference CUDA version.

If you are looking for a general SYCL introduction, we also have a SYCL Guide that takes you through all the fundamentals.

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    ComputeCpp enables developers to integrate parallel computing into applications using SYCL and accelerate code on a wide range of OpenCL devices such as GPUs.

    ComputeSuite for R-Car enables developers to accelerate their applications on a wide range of Renesas R-Car based hardware such as the H3 and V3M, using widely supported open standards such as Khronos SYCL and OpenCL.

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