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  • JonCohen
    Junior Member
    • Apr 2012
    • 1

    Hello from NVIDIA

    Hi,

    I'm the manager of the CUDA Libraries and Algorithms group at NVIDIA - that includes all of the libraries that come with CUDA like cuBLAS, cuSPARSE, etc. We also have new initiatives that I would call more "applied research" to develop functionality built on top of CUDA in emerging high-tech areas.

    One of our new focus areas is in bioinformatics. We've been doing some work prototyping short-read aligners in CUDA, similar to BarraCUDA or CUSHAW. We have CUDA-accelerated versions of the BWA and Bowtie2 algorithms, and we are seeing some really nice speedups on our preliminary benchmarking. It's probably not worth saying too much more since none of this has been peer-reviewed yet.

    Based on these success, we are committed to investing more seriously in building bioinformatics expertise at NVIDIA, and making CUDA a platform that is friendly to bioinformatics researchers. Hence, my interest in learning more about bioinformatics.

    I'm happy to answer any questions about CUDA - I see that it comes up from time to time. I don't want to be here as any type of salesman - I will try to be as candid as possible about the strengths and weaknesses of our technology.

    Regards,
    Jon
  • adaptivegenome
    Super Moderator
    • Nov 2009
    • 436

    #2
    Welcome to SEQanswers!

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    • SEQadmin2
      Nine Things a Sample Prep Scientist Thinks About Before Sequencing
      by SEQadmin2


      I’m not a sequencing expert. I’m a purification scientist who uses NGS to evaluate workflows my group develops. With this perspective, we think about the sample first and the NGS workflow second. The sequencer is an exceptionally honest reporter, but it can only report on what you give it, so whether you get clean, interpretable data from an NGS workflow is largely determined before you begin.

      Here are nine questions we think about, in roughly the order they matter, before...
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    • SEQadmin2
      From Collection to Sequencing: Why Sample Preparation and Preservation Define Sequencing Data
      by SEQadmin2


      Data variability is still an issue in sequencing technologies despite the advances in reproducibility and accuracy of these platforms. But the problem does not originate in the sequencing itself, but in the previous steps, before the sample reaches the sequencer.


      The first step is collection, followed by preservation and sample preparation for analysis. Most scientists overlook those steps, but not being careful might just be skewing the experiment’s results.
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      06-02-2026, 10:05 AM

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