MPI Streams for HPC Applications

TL;DR

This paper introduces MPIStream, an extension to MPI, enabling efficient data streaming within and across applications on HPC platforms, supporting both traditional HPC and data analytics workloads.

Contribution

MPIStream extends MPI to support data streams, facilitating efficient data flow for diverse HPC applications and data analytics, with demonstrated use cases and performance analysis.

Findings

MPIStream enables intra- and inter-application data streaming.

Supports traditional HPC and data analytics applications.

Shows promising parallel performance in use cases.

Abstract

Data streams are a sequence of data flowing between source and destination processes. Streaming is widely used for signal, image and video processing for its efficiency in pipelining and effectiveness in reducing demand for memory. The goal of this work is to extend the use of data streams to support both conventional scientific applications and emerging data analytic applications running on HPC platforms. We introduce an extension called MPIStream to the de-facto programming standard on HPC, MPI. MPIStream supports data streams either within a single application or among multiple applications. We present three use cases using MPI streams in HPC applications together with their parallel performance. We show the convenience of using MPI streams to support the needs from both traditional HPC and emerging data analytics applications running on supercomputers.