Wavelet Compression for High Performance Computing

Date and time: 
Tuesday, November 28, 2017 - 15:30
Location: 
220 Deschutes
Author(s):
Samuel Li
University of Oregon
Host/Committee: 
  • Hank Childs (Chair)
  • Allen Malony
  • Boyana Norris
  • Emilie Hooft Toomey, Geological Sciences

As HPC systems move towards exascale, the discrepancy between computational power and I/O transfer rate is only growing larger. Lossy in situ compression is a promising solution to address this gap, since it alleviates I/O constraints while still enabling traditional post hoc analysis. This thesis explores the viability of such a solution with respect to a specific kind of compressor — wavelets. We especially examine three aspects of concern regarding the viability of wavelets: 1) information loss after compression, 2) its capability to fit within in situ constraints, and 3) the compressor’s capability to adapt to HPC architectural changes. Findings from this thesis inform in situ use of wavelet compressors on HPC systems.