On Design Space Exploration of Cache System in Multi-Chiplet Systems

While multi-chiplet based many-core systems have emerged as a viable solution for heterogeneous integration and addressing manufacturing and technological challenges in the post-Moore’s Law era, their design and optimization remain highly complex and challenging. Among the various subsystems, the cache hierarchy has significant implications for overall system performance, yet its vast design space presents substantial optimization challenges. This complexity arises from factors such as the large number of chiplets in the system, the number of cores per chiplet, memory hierarchy variations, cache size variability, caching strategies, and inter-chiplet interconnection networks. Existing design space exploration methods, such as NN-Baton and IntLP, fail to optimize cache subsystem performance or thoroughly explore the design space. To address these limitations, we propose a novel design space exploration method for cache subsystem optimization. Our approach models cache miss rates and network latency as functions of cache hierarchy and inter-/intra-chiplet interconnection network parameters. We then define an optimization problem to minimize the concurrent average memory access time (C-AMAT) under cost and power consumption constraints. This problem is addressed using a bilevel optimization algorithm, which iteratively solves two independent subproblems: (1) cache subsystem optimization, and (2) inter-chiplet interconnection network optimization. Experimental results show that our method reduces the application execution time by 39.7% and 39.2%, on average, compared to architectures similar to AMD Zen 4 and Intel Sapphire Rapids, respectively, and by $\mathbf{2 5 . 9 1 \%}$ over IntLP. These results underscore the potential of the proposed method for optimizing cache subsystems in future multi-chiplet based many-core systems.