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Hot-starting software containers for STAR aligner.

Pai Zhang1, Ling-Hong Hung1, Wes Lloyd1

  • 1School of Engineering and Technology, Campus Box 358426, 1900 Commerce Street, University of Washington, Tacoma, Washington 98402-3100, USA.

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Summary
This summary is machine-generated.

Hot-starting software containers by saving their execution state significantly speeds up bioinformatics workflows. This method avoids costly re-initialization, making cloud-based analysis more efficient.

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Area of Science:

  • Computational Biology
  • Bioinformatics
  • Cloud Computing

Background:

  • Software containers are standard for reproducible biomedical workflows on the cloud.
  • Time-consuming initialization in some applications leads to unnecessary costs for repeated executions.

Purpose of the Study:

  • To demonstrate that hot-starting containers can accelerate bioinformatics workflows by bypassing repetitive initialization.
  • To evaluate the effectiveness of checkpointing and restoring container states for performance improvement.

Main Methods:

  • Utilized Checkpoint and Restore in Userspace (CRIU) to save and restore container states.
  • Created a hot-start container for the STAR aligner for RNA sequencing data alignment.
  • Compared performance with and without hot-starting on cloud platforms (AWS, Azure) and local VMs.

Main Results:

  • Hot-starting Docker containers from saved snapshots significantly speeds up STAR aligner execution.
  • Performance improvements were observed across various cloud and local virtual machine platforms.
  • The method effectively avoids repetitive initialization steps, reducing execution time.

Conclusions:

  • Hot-starting Docker containers offers substantial speedups for bioinformatics applications with lengthy initialization.
  • The checkpointing and restoring technique using CRIU is a viable method for enhancing workflow efficiency.
  • This approach has potential applications in other bioinformatics tools requiring checkpointing after initialization.