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MetaFast: Enabling Fast Metagenomic Classification via Seed Counting and Edit Distance Approximation., , , , , , , and . CoRR, (2023)Going From Molecules to Genomic Variations to Scientific Discovery: Intelligent Algorithms and Architectures for Intelligent Genome Analysis., , , , , , , and . CoRR, (2022)ApHMM: Accelerating Profile Hidden Markov Models for Fast and Energy-efficient Genome Analysis., , , , , , , , , and 3 other author(s). ACM Trans. Archit. Code Optim., 21 (1): 19:1-19:29 (March 2024)TargetCall: Eliminating the Wasted Computation in Basecalling via Pre-Basecalling Filtering., , , , , , , , and . CoRR, (2022)Morpheus: Extending the Last Level Cache Capacity in GPU Systems Using Idle GPU Core Resources., , , , , , , , and . MICRO, page 228-244. IEEE, (2022)RawHash: enabling fast and accurate real-time analysis of raw nanopore signals for large genomes., , , , , , and . Bioinform., 39 (Supplement-1): 297-307 (2023)Scrooge: a fast and memory-frugal genomic sequence aligner for CPUs, GPUs, and ASICs., , , , , and . Bioinform., (May 2023)Swordfish: A Framework for Evaluating Deep Neural Network-based Basecalling using Computation-In-Memory with Non-Ideal Memristors., , , , , , , , and . MICRO, page 1437-1452. ACM, (2023)RowPress: Amplifying Read Disturbance in Modern DRAM Chips., , , , , , , , and . ISCA, page 28:1-28:18. ACM, (2023)Scrooge: A Fast and Memory-Frugal Genomic Sequence Aligner for CPUs, GPUs, and ASICs., , , , , and . CoRR, (2022)