  As the High Performance Computing world moves towards the Exa-Scale era, huge
amounts of data should be analyzed, manipulated and stored. In the traditional
storage/memory hierarchy, each compute node retains its data objects in its
local volatile DRAM. Whenever the DRAM's capacity becomes insufficient for
storing this data, the computation should either be distributed between several
compute nodes, or some portion of these data objects must be stored in a
non-volatile block device such as a hard disk drive or an SSD storage device.
Optane DataCenter Persistent Memory Module (DCPMM), a new technology introduced
by Intel, provides non-volatile memory that can be plugged into standard memory
bus slots and therefore be accessed much faster than standard storage devices.
In this work, we present and analyze the results of a comprehensive performance
assessment of several ways in which DCPMM can 1) replace standard storage
devices, and 2) replace or augment DRAM for improving the performance of HPC
scientific computations. To achieve this goal, we have configured an HPC system
such that DCPMM can service I/O operations of scientific applications, replace
standard storage devices and file systems (specifically for diagnostics and
checkpoint-restarting), and serve for expanding applications' main memory. We
focus on keeping the scientific codes with as few changes as possible, while
allowing them to access the NVM transparently as if they access persistent
storage. Our results show that DCPMM allows scientific applications to fully
utilize nodes' locality by providing them with sufficiently-large main memory.
Moreover, it can be used for providing a high-performance replacement for
persistent storage. Thus, the usage of DCPMM has the potential of replacing
standard HDD and SSD storage devices in HPC architectures and enabling a more
efficient platform for modern supercomputing applications.
