GenASM: A High-Performance, Low-Power Approximate String Matching Acceleration Framework for Genome Sequence Analysis

Damla Senol Cali, Gurpreet S. Kalsi, Zulal Bingol, Can Firtina, Lavanya Subramanian, Jeremie S. Kim, Rachata Ausavarungnirun, Mohammed Alser, Juan Gomez-Luna, Amirali Boroumand, Anant Nori, Allison Scibisz, Sreenivas Subramoney, Can Alkan, Saugata Ghose, Onur Mutlu

October 2020

Paper Source Code Talk Video (18 minutes) Talk Slides (PDF) Talk Slides (PPTX) Live Talk and Q/A Video (15 minutes) Short Talk Video (6 minutes) Short Talk Slides (PDF) Short Talk Slides (PPTX) Lightning Talk Video (90 seconds) Lightning Talk Slides (PDF) Lightning Talk Slides (PPTX) Lecture Video (37 minutes) Lecture Slides (PDF) Lecture Talk Slides (PPTX)

Type

Conference paper

Publication

In Proceedings of the 53rd International Symposium on Microarchitecture (MICRO)

Staff Software Engineer, Hardware Acceleration, Bionano Genomics

My research interests include HW/SW co-design for bioinformatics applications and genomic data analysis.