Mozart: Taming Taxes and Composing Accelerators with Shared-Memory
Vignesh Suresh, Bakshree Mishra, Ying Jing, Zeran Zhu, Naiyin Jin, Charles Block, Paolo Mantovani, Davide Giri, Joseph Zuckerman, Luca P. Carloni, Sarita V. Adve · 2024
Resource-constrained system-on-chips (SoCs) are increasingly heterogeneous with specialized accelerators for various tasks. Acceleration taxes due to control and data movement, however, diminish end-to-end speedups from hardware acceleration. Meanwhile, emerging workloads are increasingly task-diverse with several, potentially shared, fine-grained acceleration candidates. This motivates a paradigm of parallel and disaggregated acceleration. Compared to a monolithic accelerator, disaggregation provides higher flexibility, reuse, and utilization, but at the cost of higher control and data acceleration taxes.