Design and Application Space Exploration of a Domain-Specific Accelerator System

Abstract

Domain-specific accelerators are a reaction adapting to device scaling and the dark silicon era. This paper describes a radar signal processing oriented configurable accelerator and the application space exploration of the system. The system is built around accelerator engines and general-purpose processors (GPPs) that make it suitable for intensive computing kernel acceleration and complex control tasks. It is geared toward high-performance radar digital signal processing; we characterize the applications and find that each of them contains a series of serializable kernels. Taking advantage of this discovery, we design an algorithm pool that shares the same computation resource and memory resource, and each algorithm is size reconfigurable. On the other hand, shared on-chip addressable scratchpad memory eliminates unnecessary explicit data copy between accelerators. Performance of the system is evaluated from measurements performed both on an FPGA SoC test chip and on a prototype chip fabricated by CMOS 40 nm technology. The experimental results show that for different algorithms, the proposed system achieves 1.9× to 10.1× performance gain compared with a state-of-the-art TI DSP chip. In order to characterize the application of the system, a complex real-life task is adopted, and the results show that it can obtain high throughput and desirable precision.