Opportunities for Partitioning Non-volatile Memory DIMMs Between Co-scheduled Jobs on HPC Nodes

Abstract

The emergence of non-volatile memory DIMMs such as Intel Optane DCPMM blurs the gap between usual volatile memory and persistent storage by enabling byte-accessible persistent memory with reasonable performance. This new hardware supports many possible use cases for high-performance applications, from high performance storage to very-high-capacity volatile memory (terabytes). However the numerous ways to configure the memory subsystem raises the question of how to configure nodes to satisfy applications' needs (memory, storage, fault tolerance, etc.). We focus on the issue of partitioning HPC nodes with NVDIMMs in the context of coscheduling multiple jobs. We show that the basic NVDIMM configuration modes would require node reboots and expensive hardware configuration. Moreover it does not allow the co-scheduling of all kinds of jobs, and it does not always allow locality to be taken into account during resource allocation. Then we show that using 1-Level-Memory and the Device DAX mode by default is a good compromise. It may be easily used and partitioned for storage and memory-bound applications with locality awareness.

Preliminary Experience with OpenMP Memory Management Implementation

“…With minor modifications, this graphic shows the ability to perform data allocation in large capacity memory devices like NVDIMM technology. As explained in [14], the NVDIMM memory can be configured in two modes. Our results are similar for both selected memory spaces.…”