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RattlesnakeJake: A Fast and Accurate Pre-alignment Filter Suitable for Computation-in-Memory

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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

Significant improvements in pre-alignment filter accuracy have shifted the execution bottleneck of short-read sequence alignment to the filtering step for many genomics datasets. Current pre-alignment filters move data from memory to the processing units, and when rejection is determined, this results in wasted energy and time. This paper presents RattlesnakeJake, a hardware/software co-designed accelerator that speeds up and reduces the energy consumption of pre-alignment filtering and hence sequence alignment. RattlesnakeJake achieves this by (1) proposing a lightweight and hardware-friendly filtering algorithm, (2) adopting the Computation-In-Memory paradigm to avoid unnecessary data movement, and (3) exploiting resistive memories (memristors) to perform the low-level operations required by the proposed algorithm. Our preliminary results for RattlesnakeJake show an accuracy at the state-of-the-art (SotA) level and a significant improvement in the execution time of sequence alignment, irrespective of the evaluated dataset. The improvement for filtering varies from dataset to dataset and goes up to \(\sim \)7\(\times \) and \(\sim \)80\(\times \), compared to SotA accelerators on GPU and CPU, respectively.

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Notes

  1. 1.

    We use the term filter and pre-alignment filter interchangeably hereafter.

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Author information

Authors and Affiliations

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

    Taha Shahroodi, Michael Miao, Mahdi Zahedi, Stephan Wong & Said Hamdioui

Authors
  1. Taha Shahroodi
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  2. Michael Miao
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  3. Mahdi Zahedi
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  4. Stephan Wong
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  5. Said Hamdioui
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Corresponding author

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., Miao, M., Zahedi, M., Wong, S., Hamdioui, S. (2023). RattlesnakeJake: A Fast and Accurate Pre-alignment Filter Suitable for Computation-in-Memory. 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_14

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  • DOI: https://doi.org/10.1007/978-3-031-46077-7_14

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