| Autor: |
Diab, Safaa, Nassereldine, Amir, Alser, Mohammed, Gómez-Luna, Juan, Mutlu, Onur, Hajj, Izzat El |
| Rok vydání: |
2022 |
| Předmět: |
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| Druh dokumentu: |
Working Paper |
| Popis: |
Sequence alignment is a memory bound computation whose performance in modern systems is limited by the memory bandwidth bottleneck. Processing-in-memory architectures alleviate this bottleneck by providing the memory with computing competencies. We propose Alignment-in-Memory (AIM), a framework for high-throughput sequence alignment using processing-in-memory, and evaluate it on UPMEM, the first publicly-available general-purpose programmable processing-in-memory system. Our evaluation shows that a real processing-in-memory system can substantially outperform server-grade multi-threaded CPU systems running at full-scale when performing sequence alignment for a variety of algorithms, read lengths, and edit distance thresholds. We hope that our findings inspire more work on creating and accelerating bioinformatics algorithms for such real processing-in-memory systems. Our code is available at https://github.com/safaad/aim. |
| Databáze: |
arXiv |
| Externí odkaz: |
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