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bioRxiv · 10.1101/2023.09.29.560142

DASH-CAM: Dynamic Approximate SearcH Content Addressable Memory for genome classification

Jahshan, Z.·Yavits, L.·Garzon, E.·Merlin, I.
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Abstract

We propose a novel dynamic storage-based approximate search content addressable memory (DASH-CAM) for computational genomics applications, particularly for identification and classification of viral pathogens of epidemic significance. DASH-CAM provides 5.5x better density compared to state-of-the-art SRAM-based approximate search CAM. This allows using DASH-CAM as a portable classifier that can be applied to pathogen surveillance in low-quality field settings during pandemics, as well as to pathogen diagnostics at points of care. DASH-CAM approximate search capabilities allow a high level of flexibility when dealing with a variety of industrial sequencers with different error profiles. DASH-CAM achieves up to 30% and 20% higher F1 score when classifying DNA reads with 10% error rate, compared to state-of-the-art DNA classification tools MetaCache-GPU and Kraken2 respectively. Simulated at 1GHz, DASH-CAM provides 1, 178x and 1, 040x average speedup over MetaCache-GPU and Kraken2 respectively. CCS CONCEPTS*Hardware [->] Bio-embedded electronics.

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Jahshan, Z., Yavits, L., Garzon, E., Merlin, I.. 2023-10-02. DASH-CAM: Dynamic Approximate SearcH Content Addressable Memory for genome classification. https://doi.org/10.1101/2023.09.29.560142

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