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A novel computational architecture for large-scale genomics

Nature Biotechnology volume 38, pages 1239–1241 (2020)Cite this article

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To the Editor — Biomedical and biological research is increasingly shifting toward the collection and analysis of ever-larger datasets. For example, genomics for precision medicine is moving from bulk sequencing toward single-cell studies that substantially increase the amount of data collected1,2; large-scale human research, clinical trials and population studies are also generating ever larger datasets1,3,4,5; and biological and biomedical fields such as microscopy, medical imaging or wearable devices are also increasingly generating gigabytes to terabytes of data.

At the same time as the datasets are increasing in size, our ability to develop more powerful processors for data analysis is becoming limited by our ability to further miniaturize silicon transistors6; as a result, alternative computational approaches are needed. Here we introduce memory-driven computing (MDC) as a novel and alternative in silico architecture that overcomes many of the limitations posed by current approaches.

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Fig. 1: Principles and implementation of an MDC architecture.
Fig. 2: Scaling MDC to federated computing.

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Author information

Author notes

  1. These authors jointly supervised this work: Thomas Ulas and Joachim L. Schultze.

Authors and Affiliations

  1. German Center for Neurodegenerative Diseases (DZNE), PRECISE Platform for Single Cell Genomics and Epigenomics at DZNE and the University of Bonn, Bonn, Germany

    Matthias Becker, Thomas Ulas & Joachim L. Schultze

  2. Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany

    Matthias Becker, Thomas Ulas & Joachim L. Schultze

  3. Hewlett Packard Enterprise, Ratingen, Germany

    Hartmut Schultze

  4. Hewlett Packard Labs, Palo Alto, CA, USA

    Kirk Bresniker & Sharad Singhal

Authors
  1. Matthias Becker
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  2. Hartmut Schultze
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  3. Kirk Bresniker
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  4. Sharad Singhal
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  5. Thomas Ulas
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  6. Joachim L. Schultze
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Corresponding author

Correspondence to Joachim L. Schultze.

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Competing interests

H.S., K.B. and S.S are employees of Hewlett Packard Enterprise.

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Editorial note: This article has been peer reviewed.

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Becker, M., Schultze, H., Bresniker, K. et al. A novel computational architecture for large-scale genomics. Nat Biotechnol 38, 1239–1241 (2020). https://doi.org/10.1038/s41587-020-0699-5

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  • DOI: https://doi.org/10.1038/s41587-020-0699-5

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