Hybrid-PGAS Memory Hierarchy for Next Generation HPC Systems

Abstract

Demands on computational performance, power efficiency, data transfer, resource capacity, and resilience for next generation high performance computing (HPC) systems present a new host of challenges. There is a growing disparity between computational performance vs. network and storage device throughput and among the energy costs of computational, memory, and communication operations. Chapel is a powerful, high-level, parallel, PGAS language designed to streamline development by addressing code complexities and uses a shared memory model for handling large, distributed memory systems. I extended the capabilities of Chapel by providing support of persistent memory with intrinsic and programmatic features for HPC systems. In my approach I explored the efficacy of persistent memory in a hybrid-PGAS environment through latency hiding analysis via cache monitoring, identification and mitigation of performance bottlenecks via data-centric analysis, and hardware profiling to assess performance cost vs. benefits and energy footprint. To manage persistency and ensure resiliency I developed a transaction system with ACID properties that supports hybrid-PGAS virtual addressing and distributed checkpoint and recovery system.