PSI/J: A Portable Interface for Submitting, Monitoring, and Managing Jobs

07/15/2023
by   Mihael Hategan-Marandiuc, et al.
0

It is generally desirable for high-performance computing (HPC) applications to be portable between HPC systems, for example to make use of more performant hardware, make effective use of allocations, and to co-locate compute jobs with large datasets. Unfortunately, moving scientific applications between HPC systems is challenging for various reasons, most notably that HPC systems have different HPC schedulers. We introduce PSI/J, a job management abstraction API intended to simplify the construction of software components and applications that are portable over various HPC scheduler implementations. We argue that such a system is both necessary and that no viable alternative currently exists. We analyze similar notable APIs and attempt to determine the factors that influenced their evolution and adoption by the HPC community. We base the design of PSI/J on that analysis. We describe how PSI/J has been integrated in three workflow systems and one application, and also show via experiments that PSI/J imposes minimal overhead.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
09/25/2019

MPCDF HPC Performance Monitoring System: Enabling Insight via Job-Specific Analysis

This paper reports on the design and implementation of the HPC performan...
research
02/03/2018

JobPruner: A Machine Learning Assistant for Exploring Parameter Spaces in HPC Applications

High Performance Computing (HPC) applications are essential for scientis...
research
07/12/2018

Virtualizing the Stampede2 Supercomputer with Applications to HPC in the Cloud

Methods developed at the Texas Advanced Computing Center (TACC) are desc...
research
08/02/2023

PROV-IO+: A Cross-Platform Provenance Framework for Scientific Data on HPC Systems

Data provenance, or data lineage, describes the life cycle of data. In s...
research
12/11/2019

High Performance Computing for Geospatial Applications: A Retrospective View

Many types of geospatial analyses are computationally complex, involving...
research
01/20/2023

ARcode: HPC Application Recognition Through Image-encoded Monitoring Data

Knowing HPC applications of jobs and analyzing their performance behavio...
research
01/29/2018

A cost effective and reliable environment monitoring system for HPC applications

We present a slow control system to gather all relevant environment info...

Please sign up or login with your details

Forgot password? Click here to reset