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SYCLomatic: SYCL Adoption for Everyone - Moving from CUDA to SYCL Gets Progressively Easier: Advanced Migration Considerations

Published:08 April 2024Publication History

ABSTRACT

Since widening its scope and becoming its independent working group 5 years ago, SYCL has evolved into the alternative to CUDA by championing an open-source and standards-based approach to accelerator offload, including GPUs. SYCL became the cornerstone of the oneAPI industry initiative, which combines it with a range of library and API specifications to create a multiarchitecture, multi-vendor programming model with the components needed by a developer relying on an ecosystem of ready-to-use device interfaces for common optimized and specialized routines. In September last year, this industry initiative became the starting point of the Unified Acceleration Foundation (UXL), governed by the Linux Foundation and hosted by the Linux Foundation's Joint Development Foundation (JDF). Its steering members include Arm, Fujitsu, Google Cloud, Imagination Technologies, Intel, Qualcomm Technologies Inc., Samsung, and VMware. SYCL and the drive to wide SYCL 2020 adoption and compliance are still at the heart of this effort. To help enable ecosystem-wide usage across workloads and accelerator hardware, it must be possible to conveniently migrate the CUDA-based legacy codebase of popular applications to SYCL. SYCLomatic was developed to provide a tool to ingest a project targeting C++ with CUDA-based GPU offload and translate it into ready-to-build C++ with SYCL code. This poster and accompanying paper go into advanced considerations for successful, and performant migrated code.

References

  1. Intel. 2023. SYCLomatic. https://github.com/oneapi-src/SYCLomaticGoogle ScholarGoogle Scholar
  2. Intel. 2023. Velocity Bench. https://github.com/oneapi-src/Velocity-BenchGoogle ScholarGoogle Scholar

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  • Published in

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    IWOCL '24: Proceedings of the 12th International Workshop on OpenCL and SYCL
    April 2024
    124 pages
    ISBN:9798400717901
    DOI:10.1145/3648115

    Copyright © 2024 Owner/Author

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 8 April 2024

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