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Will solid-state drives accelerate your bioinformatics? In-depth profiling, performance analysis and beyond.

Sungmin Lee, Hyeyoung Min, Sungroh Yoon

Briefings in Bioinformatics

|September 3, 2015

Summary

This summary is machine-generated.

Solid-state drives (SSDs) significantly accelerate bioinformatics programs by overcoming parallelization limits. This study profiles 23 key programs, offering insights for optimizing algorithms and pipelines with SSDs for faster biomedical big data analysis.

Keywords:

benchmarking bioinformatics pipeline high-performance bioinformatics high-performance computing and storage large-scale analysis

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Area of Science:

Bioinformatics
Computational Biology
Data Science

Background:

Bioinformatics generates vast datasets, necessitating efficient big data handling.
Parallel computing partially addresses this, but many programs remain time-intensive.
New storage technologies like solid-state drives (SSDs) offer potential acceleration.

Purpose of the Study:

To review and analyze the performance of bioinformatics programs using SSDs.
To explore how SSDs can complement parallel processing for acceleration.
To provide guidance on optimizing bioinformatics algorithms and pipelines for SSDs.

Main Methods:

In-depth profiling and performance analysis of 23 key bioinformatics programs.
Utilized multiple types of storage devices, including SSDs and traditional hard disk drives.
Examined programs across diverse areas: alignment, assembly, mapping, expression analysis, variant calling, and metagenomics.

Main Results:

SSDs provide dramatic speedups for many bioinformatics tasks, often exceeding parallelization benefits alone.
Profiling revealed specific performance bottlenecks and opportunities for SSD optimization in various programs.
Demonstrated significant acceleration for pipelines like Genome Analysis Toolkit variant calling and RNA sequencing transcriptome analysis.

Conclusions:

SSDs are a crucial technology for accelerating time-consuming bioinformatics programs and handling biomedical big data.
Combining parallel processing with SSDs offers enhanced performance improvements.
This review provides essential insights for designing future bioinformatics algorithms and pipelines to leverage modern storage devices.