A Review on Hardware Implementations of Signal Processing Algorithms

Abstract

AbstractSignal processing algorithms are becoming more and more important nowadays due to their utility in almost all fields such as control, communications, instrumentation, automobiles, medical, military applications, etc. In recent times, signal processing algorithms are simulated generally using MATLAB. But for practical use, these simulations need to be implemented in hardware. Their implementation as a stand-alone system requires dedicated hardware as an application-specific integrated circuit (ASIC), field-programmable gate array (FPGA), and others. Therefore, in this paper, a review of various hardware implementations of signal processing algorithms is presented. Different means for these hardware implementations are presented and compared discussing their relative merits and demerits. The emerging trend based on the graphics processing unit (GPU), which takes care of complex floating-point operations involved in signal processing algorithms effectively, is presented in detail along with the associated hardware and software features. ASICs and System-on-Chip (SoCs) are the first choices for hardware implementation as they provide. This review will help the researchers to get a comprehensive review of this domain and help them to jump start in exploring the design of GPU-based stand-alone systems.KeywordsSignal processing algorithmsOpen source languagesASICSoCHardware platformsGPUCentral processing unit (CPU)GPU accelerators