8 citations · 10 across the 4 of their papers we have counts for
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cs.AR2022
RUBICON: A Framework for Designing Efficient Deep Learning-Based Genomic Basecallers
Gagandeep Singh, Mohammed Alser, Kristof Denolf +5
Nanopore sequencing generates noisy electrical signals that need to be converted into a standard string of DNA nucleotide bases using a computational step called basecalling. The a…
cs.AR2022★ 1 cited
Machine Learning Training on a Real Processing-in-Memory System
Juan Gómez-Luna, Yuxin Guo, Sylvan Brocard +5
Training machine learning algorithms is a computationally intensive process, which is frequently memory-bound due to repeatedly accessing large training datasets. As a result, proc…