2025/07/02 by Yuan Dai, Xuchen Gao, Yunhui Qiu +7
Computer Science · #Parallel Computing and Optimization Techniques #Embedded Systems Design Techniques #Interconnection Networks and Systems
paper · doi:10.1109/tc.2025.3585345
Coarse-Grained Reconfigurable Architecture (CGRA) emerges as a competitive accelerator due to its high flexibility and energy efficiency. However, most CGRAs are effective for computation-intensive applications with regular loops but struggle with irregular loops containing control flows. These loops introduce fine-grained logic operations and are costly to execute by coarse-grained arithmetic units in CGRA. Efficiently handling such logic operations necessitates incorporating Boolean algebra optimization, which can improve logic density and reduce logic depth. Unfortunately, no previous research has incorporated it into the compilation flow to support irregular loops efficiently. <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">We propose <i>COFFA</i>, an open-source framework for heterogeneous architecture with a RISC-V CPU and a fused-grained reconfigurable accelerator, which integrates coarse-grained arithmetic and fine-grained logic units, along with flexible IO units and distributed interconnects. As a software/hardware co-design framework, <i>COFFA</i> has a powerful compiler that extracts and optimizes fine-grained logic operations from irregular loops, performs coarse-grained arithmetic and memory optimizations, and offloads the loops to the accelerator. <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Across various challenging benchmarks with irregular loops, <i>COFFA</i> achieves significant performance and energy efficiency improvements over an in-order, an out-of-order RISC-V CPUs, and a recent FPGA, respectively. Moreover, compared with the state-of-the-art CGRA <i>UE-CGRA</i> and <i>Hycube</i>, <i>COFFA</i> can achieve 2.5× and 3.5× performance gains, respectively.