Name
Abstract | ||
|---|---|---|
We improve on GenASM, a recent algorithm for genomic sequence alignment, by significantly reducing its memory footprint and bandwidth requirement. Our algorithmic improvements reduce the memory footprint by 24 × and the number of memory accesses by 12 ×. We efficiently parallelize the algorithm for GPUs, achieving a 4.1 × speedup over a CPU implementation of the same algorithm, a 62× speedup over minimap2's CPU-based KSW2 and a 7.2 × speedup over the CPU-based Edlib for long reads. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/IPDPSW55747.2022.00038 | 2022 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) |
Keywords | DocType | ISSN |
read mapping,sequence alignment,GPU,memory | Conference | 2164-7062 |
ISBN | Citations | PageRank |
978-1-6654-9748-0 | 1 | 0.34 |
References | Authors | |
8 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Joël Lindegger | 1 | 1 | 0.68 |
| Damla Senol Cali | 2 | 34 | 3.32 |
| Mohammed Alser | 3 | 17 | 3.19 |
| Juan Gómez-Luna | 4 | 22 | 3.88 |
| Onur Mutlu | 5 | 1 | 0.34 |