Presentation
Performance of Inline Compression with Software Caching for Reducing the Memory Footprint in pySDC
DescriptionThe volume of data required for high performance computing (HPC) jobs is growing faster than the memory storage available to store the required data, leading to performance bottlenecks. Hence the need for inline data compression, which reduces the amount of allocated memory needed by storing all data in its compressed format and decompressing/recompressing single variables as needed. We apply inline compression to HPC application pySDC, a framework that solves collocation problems iteratively using parallel-in-time methods. We introduce a new version of pySDC that has a compression manager to add inline compression functionality, along with a software cache that stores the decompressed state of the most frequently used variables. We use lossy compressor ZFP and test our model with varying software cache sizes. Results show that having no cache has the best compression ratio, but having a cache of size 16 improves the timing while also slightly improving the memory footprint.
Event Type
ACM Student Research Competition: Graduate Poster
ACM Student Research Competition: Undergraduate Poster
Doctoral Showcase
Posters
TimeTuesday, 19 November 202412pm - 5pm EST
LocationB302-B305
TP
XO/EX