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A Case for Genome Analysis Where Genomes Reside

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Embedded Computer Systems: Architectures, Modeling, and Simulation (SAMOS 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14385))

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Abstract

Genome analysis, such as studying human genomics, critically impacts various aspects of human life. These analyses involve diverse species and experience a surge in the data required to be dealt with. However, extant computer systems grapple with inherent limitations in processing genomic data, facing issues such as excessive data movement, suboptimal design for high parallelism, and optimization for high FLOPs, which are less suited for genomic analysis. In this paper, we argue that these challenges may well be addressed through the application of the Computation-In-Memory (CIM) paradigm, an approach well-aligned with the computational characteristics of genomic data. We advocate for an exploration of CIM ’s viability for kernels and functions within genome analysis pipelines. Such a CIM design processes genomes where it makes sense, potentially where genomes reside, which can be in different levels of memory units, e.g., storage, memory, and caches. Considering the inherent heterogeneity of contemporary genome analysis systems, the integration of a cost-effective CIM substrate could be conceivable. Nonetheless, we acknowledge that prior to this vision’s realization, critical groundwork in data mapping, execution flow, and operations of genomic kernels on such a system must first be established.

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Notes

  1. 1.

    Moore’s law states that the number of transistors on a chip will double approximately every two years. This exponential growth leads to an increase in computational power [25].

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Authors and Affiliations

  1. Technische Universiteit Delft (TU Delft), 2628 CD, Delft, The Netherlands

    Taha Shahroodi, Stephan Wong & Said Hamdioui

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  1. Taha Shahroodi
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  2. Stephan Wong
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  3. Said Hamdioui
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Correspondence to Taha Shahroodi .

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Editors and Affiliations

  1. Politecnico di Milano, Milan, Italy

    Cristina Silvano

  2. Politecnico di Milano, Milan, Italy

    Christian Pilato

  3. University of Rostock, Rostock, Germany

    Marc Reichenbach

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Shahroodi, T., Wong, S., Hamdioui, S. (2023). A Case for Genome Analysis Where Genomes Reside. In: Silvano, C., Pilato, C., Reichenbach, M. (eds) Embedded Computer Systems: Architectures, Modeling, and Simulation. SAMOS 2023. Lecture Notes in Computer Science, vol 14385. Springer, Cham. https://doi.org/10.1007/978-3-031-46077-7_30

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  • DOI: https://doi.org/10.1007/978-3-031-46077-7_30

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