Simulation / Modeling / Design

Webinar: GPU-Accelerated Analysis of DNA Sequencing Data

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  • Parabricks accelerates secondary analysis of DNA sequencing data, reducing whole-genome analysis from days to one hour using GPU-accelerated workflows.
  • The GPU-accelerated workflow completes alignment, pre-processing, and variant calling at trailblazing speeds compared to up to 30 hours on 32 vCPU servers.
  • Industry-standard algorithms including BWA-Mem, GATK4, Smith-Waterman, PairHMM, and deep learning technologies such as DeepVariant are accelerated on GPUs.

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Personalizing treatments based on patients’ genetic variation will revolutionize how medicine cures diseases; but time to analysis has become a major bottleneck.
Join Mehrzad Samadi, CEO of Parabricks on Thursday, March 1, 2018, from 11am-12pm PST as he discusses the use of GPU-acceleration to speed the analysis of DNA sequencing data.
Parabricks has accelerated secondary analysis of sequencing data to analyze a 30x whole genome from days to ONE hour. Using GPUs, Parabrick’s accelerated workflow with superior visualizations can finish alignment, pre-processing and variant calling—a process that can easily take up to 30 hours on 32 vCPU servers—at trailblazing speeds. Gain an in-depth understanding of how GPUs can be used for accelerating industry standard algorithms used in BWA-Mem, GATK4 such as Smith-Waterman, PairHMM and deep learning technologies used in variant calling.
By attending this webinar, attendees will:

  • Develop an understanding of the compute intensive nature of genomic analysis;
  • Learn about accelerating dynamic programming on GPUs, including deep learning on genomic data using DeepVariant; and
  • Explore options for large computing power for genomic analysis, including the DGX-1, as well as GPUs on-premise and on the cloud.

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