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T. Zhang, E. Tang, F. Siddique, K. Skadron and Franz Franchetti (Proc. High Performance Extreme Computing (HPEC), 2024)
Towards an End-to-End Processing-in-DRAM Acceleration of Spectral Library Search
Comment: Extended abstract with poster
Preprint (871 KB)
Bibtex

This work explores accelerating spectral library searches, a key mass spectrometry (MS) workload, using processing-in-memory (PIM) architectures through an end-toend, co-designed approach. We apply signal processing and approximate computing techniques for pre-filtering MS data and implement a sum of absolute differences (SAD) algorithm optimized for PIM to compare spectral similarity. Our methodology is evaluated using a DRAM-based PIM simulator and compared against traditional CPU implementations. While initial results with small datasets favor CPUs, our analysis indicates potential benefits for PIM with larger, more realistic proteomics datasets. This work represents an initial step towards investigating PIM acceleration for MS applications.

Keywords:
Processing-in-memory, Application-specific accelleration, Bioinformatics, Mass spectrometry, Spectral library search, Near-data processing