Mapping and Execution of Nested Loops on Processor Arrays: CGRAs vs. TCPAs

TL;DR

This paper compares CGRA and TCPA processor arrays in terms of their methods for mapping nested loops, analyzing their advantages and trade-offs for energy-efficient SoC acceleration.

Contribution

It provides a comprehensive analysis of operation-centric and iteration-centric mapping approaches on CGRAs and TCPAs, highlighting their respective benefits and limitations.

Findings

Operation-centric mapping favors fine-grained parallelism.

Iteration-centric mapping benefits from coarse-grained execution.

Trade-offs include energy efficiency and flexibility.

Abstract

Increasing demands for computing power also propel the need for energy-efficient SoC accelerator architectures. One class of such accelerators are so-called processor arrays, which typically integrate a two-dimensional mesh of interconnected processing elements~(PEs). Such arrays are specifically designed to accelerate the execution of multidimensional nested loops by exploiting the intrinsic parallelism of loops. Moreover, for mapping a given loop nest application, two opposed mapping methods have emerged: Operation-centric and iteration-centric. Both differ in the granularity of the mapping. The operation-centric approach maps individual operations to the PEs of the array, while the iteration-centric approach maps entire tiles of iterations to each PE. The operation-centric approach is applied predominantly for processor arrays often referred to as Coarse-Grained Reconfigurable Arrays~(CGRAs), while processor arrays supporting an iteration-centric approach are referred to as Tightly-Coupled Processor Arrays~(TCPAs) in the following. This work provides a comprehensive comparison of both approaches and related architectures by evaluating their respective benefits and trade-offs. ...