Jens Domke, Emil Vatai, Balazs Gerofi, Yuetsu Kodama, Mohamed Wahib, Artur Podobas, Sparsh Mittal, Miquel Pericàs, Lingqi Zhang, Peng Chen, Aleksandr Drozd, Satoshi Matsuoka
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At the Locus of Performance: Quantifying the Effects of Copious 3D-Stacked Cache on HPC Workloads
Over the last three decades, innovations in the memory subsystem were primarily targeted at overcoming the data movement bottleneck. In this paper, we focus on a specific market trend in memory technology: 3D-stacked memory and caches. We investigate the impact of extending the on-chip memory capabilities in future HPC-focused processors, particularly by 3D-stacked SRAM. First, we propose a method oblivious to the memory subsystem to gauge the upper-bound in performance improvements when data movement costs are eliminated. Then, using the gem5 simulator, we model two variants of a hypothetical LARge Cache processor (LARC), fabricated in 1.5 nm and enriched with high-capacity 3D-stacked cache. With a volume of experiments involving a broad set of proxy-applications and benchmarks, we aim to reveal how HPC CPU performance will evolve, and conclude an average boost of 9.56x for cache-sensitive HPC applications, on a per-chip basis. Additionally, we exhaustively document our methodological exploration to motivate HPC centers to drive their own technological agenda through enhanced co-design.
期刊介绍:
ACM Transactions on Architecture and Code Optimization (TACO) focuses on hardware, software, and system research spanning the fields of computer architecture and code optimization. Articles that appear in TACO will either present new techniques and concepts or report on experiences and experiments with actual systems. Insights useful to architects, hardware or software developers, designers, builders, and users will be emphasized.