Disaggregating Non-Volatile Memory for Throughput-Oriented Genomics Workloads

TL;DR

This paper explores how disaggregating non-volatile memory can improve throughput for genomics workloads like SMUFIN within flexible, software-defined infrastructure environments, addressing future HPC challenges.

Contribution

It investigates the benefits of disaggregating NVM for genomics applications in SDI environments, proposing new hardware management strategies.

Findings

Enhanced throughput for genomics workloads with NVM disaggregation

Improved resource flexibility and utilization in SDI environments

Potential for better scalability in bioinformatics pipelines

Abstract

Massive exploitation of next-generation sequencing technologies requires dealing with both: huge amounts of data and complex bioinformatics pipelines. Computing architectures have evolved to deal with these problems, enabling approaches that were unfeasible years ago: accelerators and Non-Volatile Memories (NVM) are becoming widely used to enhance the most demanding workloads. However, bioinformatics workloads are usually part of bigger pipelines with different and dynamic needs in terms of resources. The introduction of Software Defined Infrastructures (SDI) for data centers provides roots to dramatically increase the efficiency in the management of infrastructures. SDI enables new ways to structure hardware resources through disaggregation, and provides new hardware composability and sharing mechanisms to deploy workloads in more flexible ways. In this paper we study a state-of-the-art genomics application, SMUFIN, aiming to address the challenges of future HPC facilities.