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<p>Parallel and signal processing patterns for large-scale radio data applications have been captured with a new domain-specific language (DSL), OptiSDR. The intermediate representations (IR) of the code are optimized at the frontend with the Delite compiler targeted for heterogeneous computing architecture (HCA). The design flow begins at the abstract programming model and, at a later stage, addresses tuning of the domain applications to the target HCA comprising GPUs and MCPU, as well as scheduling and optimal memory access. For a variety of signal processing use cases, the framework has shown up to two orders of magnitude higher computational speed than MPI and C++ and comparable performance to architecture-specific CUDA. Additional gains are ease of use, scalable computing, and efficient runtime.</p>

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Automatic Heterogeneous Runtime Using Signal Processing Domain-Specific and Parallel Patterns

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年2月25日

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  • Yaseen Zaidi,
  • Simon Winberg

摘要

Parallel and signal processing patterns for large-scale radio data applications have been captured with a new domain-specific language (DSL), OptiSDR. The intermediate representations (IR) of the code are optimized at the frontend with the Delite compiler targeted for heterogeneous computing architecture (HCA). The design flow begins at the abstract programming model and, at a later stage, addresses tuning of the domain applications to the target HCA comprising GPUs and MCPU, as well as scheduling and optimal memory access. For a variety of signal processing use cases, the framework has shown up to two orders of magnitude higher computational speed than MPI and C++ and comparable performance to architecture-specific CUDA. Additional gains are ease of use, scalable computing, and efficient runtime.