Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
125 tokens/sec
GPT-4o
47 tokens/sec
Gemini 2.5 Pro Pro
43 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
47 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

FPGA Acceleration of Sequence Alignment: A Survey (2002.02394v2)

Published 5 Feb 2020 in q-bio.QM, cs.AR, and q-bio.GN

Abstract: Genomics is changing our understanding of humans, evolution, diseases, and medicines to name but a few. As sequencing technology is developed collecting DNA sequences takes less time thereby generating more genetic data every day. Today the rate of generating genetic data is outpacing the rate of computation power growth. Current sequencing machines can sequence 50 humans genome per day; however, aligning the read sequences against a reference genome and assembling the genome will take 1300 CPU hours. The main step in constructing the genome is aligning the reads against a reference genome. Numerous accelerators have been proposed to accelerate the DNA alignment process. Providing massive parallelism, FPGA-based accelerators have shown great performance in accelerating DNA alignment algorithms. Additionally, FPGA-based accelerators provide better energy efficiency than general-purpose processors. In this survey, we introduce three main DNA alignment algorithms and FPGA-based implementation of these algorithms to accelerate the DNA alignment. We also, compare these three alignment categories and show how accelerators are developing during the time.

Citations (12)

Summary

We haven't generated a summary for this paper yet.