A domain-specific language to facilitate software defined radio parallel executable patterns deployment on heterogeneous architectures
A domain-specific language to facilitate software defined radio parallel executable patterns deployment on heterogeneous architectures
复制标题
一种特定于领域的语言，有助于在异构架构上部署软件定义的无线电并行可执行模式
DOI：
10.1109/pccc.2014.7017083
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
M. Inggs
中科院分区：
文献类型：
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作者：
L. Mohapi;S. Winberg;M. Inggs
在本文中，我们提出了一个特定领域的语言，被称为OptiSDR，匹配高层次的数字信号处理（DSP）例程的软件定义无线电（SDR）的通用并行可执行模式针对异构计算架构（HCA）。这些HCA包括混合GPU-CPU和DSP-FPGA架构的组合，其使用不同的编程范例（诸如C/C++、CUDA、OpenCL和/或VHDL）来编程。OptiSDR提供了一个直观的单一高级源代码和接近规范级别的方法，用于优化和促进HCA。OptiSDR使用一个优化的嵌入式领域特定语言（DSL）编译器框架Delite。我们的重点是在SDR HCA上部署的典型DSP算法的并行编程和优化的编程语言的表现力。我们证明了OptiSDR的能力，以最接近原始并行编程的SDR系统的方式来表达并行DSP低级别实现复杂性问题的解决方案。本文将通过关注三种适用于DSP例程的通用并行可执行模式来实现这些功能，例如互相关、基于Hilbert变换的FIR滤波器中的卷积和用于频谱分析的快速傅立叶变换。本文最后使用DSP算法进行性能分析，测试自动生成的代码与手工制作的解决方案。
In this paper, we present a domain-specific language, referred to as OptiSDR, that matches high level digital signal processing (DSP) routines for software defined radio (SDR) to their generic parallel executable patterns targeted to heterogeneous computing architectures (HCAs). These HCAs includes a combination of hybrid GPU-CPU and DSP-FPGA architectures that are programmed using different programming paradigms such as C/C++, CUDA, OpenCL, and/or VHDL. OptiSDR presents an intuitive single high-level source code and near specification-level approach for optimization and facilitation of HCAs. OptiSDR uses an optimized embedded domain-specific language (DSL) compiler framework called Delite. Our focus is on the programming language expressiveness for parallel programming and optimization of typical DSP algorithms for deployment on SDR HCAs. We demonstrate the capability of OptiSDR to express the solution to the issues of parallel DSP low-level implementation complexities in the closest way to the original parallel programming of SDR systems. This paper will achieve these by focusing on three generic parallel executable patterns suitable for DSP routines such as cross-correlation, convolution in FIR filter based Hilbert transformers, and fast Fourier transforms for spectral analysis. This paper concludes with a performance analysis using DSP algorithms that tests automatically generated code against hand-crafted solutions.