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arXiv · 2511.03437

HERP: Hardware for Energy Efficient and Realtime DB Search and Cluster Expansion in Proteomics

Md Mizanur Rahaman Nayan·Zheyu Li·Flavio Ponzina·Sumukh Pinge·Tajana Rosing·Azad J. Naeemi
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Abstract

Database search and clustering are fundamental components of many data analytics problems, such as mass spectrometry-driven proteomics. Traditional full clustering and search algorithms suffer from high resource usage and long latencies. We introduce HERP, a lightweight incremental clustering method and a highly parallelizable database (DB) search platform that utilizes 3T2MTJ SOT-MRAM based CAM in 7nm technology for in-memory acceleration. A single hardware initialization using pre-clustered proteomics data allows for continuous DB searching and local re-clustering, providing a more practical and efficient alternative to clustering from scratch. Heuristics derived from the initial pre-clustered data guide the incremental process, accelerating clustering by 20x at a cost of 0.3% increase in clustering error where DB search results overlap by 96% with SOTA algorithms validating search quality. For a 131GB human genome proteomics dataset HERP setup requires 1.19mJ for 2M spectra while 1000 query search consumes only 1.1uJ at SOTA accuracy. Bucket-wise parallelization and query scheduling provides additional 100x speedup.

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Md Mizanur Rahaman Nayan, Zheyu Li, Flavio Ponzina, Sumukh Pinge, Tajana Rosing, Azad J. Naeemi. 2025-11-05. HERP: Hardware for Energy Efficient and Realtime DB Search and Cluster Expansion in Proteomics. https://arxiv.org/abs/2511.03437

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