부산대학교 도서관

In this paper, we propose a fused-pipeline architecture that leverages the layer fusion technique to harness the strengths of both non-pipeline and full-pipeline architectures while mitigating their disadvantages. In particular, we observe that the performance of the fused-pipeline accelerators is significantly influenced by the layer fusion strategies and intra-layer mapping schemes. To optimize and rapidly employ the fused-pipeline architecture, we present an end-to-end automation framework, named PipeFuser. At the core of PipeFuser is a genetic algorithm (GA)-based co-design engine, which is used to acquire near-optimal hardware configurations in the vast design space. Experimental results demonstrate that our fused-pipeline architecture achieves 2.3 × to 3.3 × higher performance over the non-pipeline design and 1.9 × to 2.5 × speedup compared to the full-pipeline architecture, with greater deployment flexibility.