2024/09/20 by Sumukh Pinge, Weihong Xu, Pinge, Sumukh +9 · 3 citations
Computer Science · Engineering · #CCD and CMOS Imaging Sensors #Distributed #FOS: Computer and information sciences #Hardware Architecture (cs.AR) #Neural Networks and Applications #Parallel #and Cluster Computing (cs.DC)
paper · pdf · doi:10.48550/arxiv.2409.13361
openalex publication_date 2024/09/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Mass spectrometry (MS) is essential for protein analysis but faces significant challenges with large datasets and complex post-translational modifications, resulting in difficulties in spectral identification. Open Modification Search (OMS) improves the analysis of these modifications. We present RapidOMS, a solution leveraging the Samsung SmartSSD, which integrates SSD and FPGA in a near-storage configuration to minimize data movement and enhance the efficiency of large-scale database searching. RapidOMS employs hyperdimensional computing (HDC), a brain-inspired, high-dimensional data processing approach, exploiting the parallel processing and low-latency capabilities of FPGAs, making it well-suited for MS. Utilizing the parallelism and efficiency of bitwise operations in HDC, RapidOMS delivers up to a 60x speedup over the state-of-the-art (SOTA) CPU tool ANN-Solo and is 2.72x faster than the GPU tool HyperOMS. Furthermore, RapidOMS achieves an 11x improvement in energy efficiency compared to conventional systems, providing scalable, energy-efficient solutions for large-scale proteomics applications and advancing the efficient processing of proteomic data.