Paper
:
An Early Evaluation of Intel’s Optane DC Persistent Memory Module and Its Impact on High-Performance Scientific Applications
Event Type
Paper
Registration Categories
TP
Tags
Best Practices
Energy
Exascale
Machine Learning
Memory
Modelling
Networks
Performance
Power
Reliability
Reproducibility
TimeThursday, 21 November 20192pm - 2:30pm
Location405-406-407
DescriptionMemory and I/O performance bottlenecks in supercomputing simulations are two key challenges that must be addressed on the road to Exascale. The new byte-addressable persistent non-volatile memory technology from Intel, DCPMM, promises to be an exciting opportunity to break with the status quo, with unprecedented levels of capacity at near-DRAM speeds. Here, we explore the potential of DCPMM in the context of two high-performance scientific applications in terms of outright performance, efficiency and usability for both its Memory and App Direct modes. In Memory mode, we show equivalent performance and better efficiency for a CASTEP simulation that is limited by memory capacity on conventional DRAM-only systems without any changes to the application. For IFS, we demonstrate that a distributed object-store over NVRAM reduces the data contention created in weather forecasting data producer-consumer workflows. In addition, we also present the achievable memory bandwidth performance using STREAM.
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