The International Conference for High Performance Computing, Networking, Storage, and Analysis
The International Conference for High Performance Computing, Networking, Storage, and Analysis
Poster Type: Research Posters
Author: Logan Williams (North Carolina State University), Gavin Conant (North Carolina State University), Michela Becchi (North Carolina State University), Jan Ciesko (Sandia National Laboratories), Amy Powell (Sandia National Laboratories)
Supervisor: Gavin Conant (North Carolina State University)
Abstract: Inexpensive DNA sequencing [1] has opened new windows into biological complexity. These include metagenomics: the ability to catalog a microbial ecosystem by extracting and sequencing DNA directly from an environment. Analyzing metagenomic-scale datasets often requires exascale computing. Such computing platforms are heterogeneous, encompassing CPUs, GPUs, FPGAs or other co-processors. This heterogeneity presents complications for software design. The programming models can require code rewrites when hardware changes. Moreover, achieving adequate performance requires understanding the interaction between hardware and programming models. Computational biology codes suffer particularly from these problems because they are poorly studied [2] [3]. Here we describe a proxy application based on a metagenome assembler which allows both machine profiling and studying co-processor behavior for biology codes.
Best Poster Finalist (BP): no
Poster: PDF
Poster Summary: PDF