Using a domain specific language for SDR to facilitate radar signal processing in heterogeneous computing architectures

Abstract

This paper presents the use of a Domain-Specific Language (DSL) for Software Defined Radio (SDR) in a Radar digital signal processing (DSP) using heterogeneous computing architectures (HCAs). These HCAs are a combinations of mul-ticore CPU, GPUs, and FPGAs. This DSL, which we named OptiSDR, uses a dataflow-like model of computations named parallel stream processing and a compiler guided optimization technique to provide optimized parallel executable patterns for a hybrid MCPU-GPU architecture. In this paper, we demonstrate the capabilities of OptiSDR in a Radar DSP case study, and show how OptiSDR achieves up to 50 times (50X) speed-up as compared to the hand-crafted Matlab and Octave scripts for the NetRAD pulse compression algorithm. We also show that, while hand-crafted CUDA-Qt implementation of the same pulse compression algorithm presents up to 2X speed-up against Op-tiSDR, this was minimized using platform-specific optimizations by efficiently utilizing available computing resources such as number of GPUs, memory, and number of cores of a MCPU.