Accelerating Scientific Workflows on HPC Platforms with In Situ Processing

Do, Tu Mai Anh; Pottier, Loic; Yildiz, Orcun; Vahi, Karan; Krawczuk, Patrycja; Peterka, Thomas; Deelman, Ewa

doi:10.1109/CCGrid54584.2022.00009

Accelerating Scientific Workflows on HPC Platforms with In Situ Processing

Conference · Fri Dec 31 23:00:00 EST 2021

DOI:https://doi.org/10.1109/CCGrid54584.2022.00009· OSTI ID:1888792

Do, Tu Mai Anh; Pottier, Loic; Yildiz, Orcun; Vahi, Karan; Krawczuk, Patrycja; Peterka, Thomas; Deelman, Ewa

Scientific workflows drive most modern large-scale science breakthroughs by allowing scientists to define their computations as a set of jobs executed in a given order based on their data dependencies. Workflow management systems (WMSs) have become key to automating scientific workflows-executing computational jobs and orchestrating data transfers between those jobs running on complex high-performance computing (HPC) platforms. Traditionally, WMSs use files to communicate between jobs: a job writes out files that are read by other jobs. However, HPC machines face a growing gap between their storage and compute capabilities. To address that concern, the scientific community has adopted a new approach called in situ, which bypasses costly parallel filesystem I/O operations with faster in-memory or in-network communications. When using in situ approaches, communication and computations can be interleaved. In this work, we leverage the Decaf in situ dataflow framework to accelerate task-based scientific workflows managed by the Pegasus WMS, by replacing file communications with faster MPI messaging. We propose a new execution engine that uses Decaf to manage communications within a sub-workflow (i.e., set of jobs) to optimize inter-job communications. We consider two workflows in this study: (i) a synthetic workflow that benchmarks and compares file- and MPI-based communication; and (ii) a realistic bioinformatics workflow that computes mu-tational overlaps in the human genome. Experiments show that in situ communication can improve the bioinformatics workflow execution time by 22% to 30% compared with file communication. Our results motivate further opportunities and challenges for bridging traditional WMSs with in situ frameworks.

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Research Organization:: Argonne National Laboratory (ANL)

Sponsoring Organization:: USDOE Office of Science - Office of Advanced Scientific Computing Research (ASCR); National Science Foundation (NSF)

DOE Contract Number:: AC02-06CH11357

OSTI ID:: 1888792

Country of Publication:: United States

Language:: English

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