{"title":"基因组变异调用的FPGA加速器","authors":"Tiancheng Xu, Scott Rixner, Alan L. Cox","doi":"https://dl.acm.org/doi/10.1145/3595297","DOIUrl":null,"url":null,"abstract":"<p>In genome analysis, it is often important to identify variants from a reference genome. However, identifying variants that occur with low frequency can be challenging, as it is computationally intensive to do so accurately. LoFreq is a widely used program that is adept at identifying low frequency variants. This paper presents a design framework for an FPGA-based accelerator for LoFreq. In particular, this accelerator is targeted at virus analysis, which is particularly challenging, compared to human genome analysis, as the characteristics of the data to be analyzed are fundamentally different. Across the design space, this accelerator can achieve up to 120 × speedups on the core computation of LoFreq and speedups of up to 51.7 × across the entire program.</p>","PeriodicalId":49248,"journal":{"name":"ACM Transactions on Reconfigurable Technology and Systems","volume":"37 1","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2023-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An FPGA Accelerator for Genome Variant Calling\",\"authors\":\"Tiancheng Xu, Scott Rixner, Alan L. Cox\",\"doi\":\"https://dl.acm.org/doi/10.1145/3595297\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>In genome analysis, it is often important to identify variants from a reference genome. However, identifying variants that occur with low frequency can be challenging, as it is computationally intensive to do so accurately. LoFreq is a widely used program that is adept at identifying low frequency variants. This paper presents a design framework for an FPGA-based accelerator for LoFreq. In particular, this accelerator is targeted at virus analysis, which is particularly challenging, compared to human genome analysis, as the characteristics of the data to be analyzed are fundamentally different. Across the design space, this accelerator can achieve up to 120 × speedups on the core computation of LoFreq and speedups of up to 51.7 × across the entire program.</p>\",\"PeriodicalId\":49248,\"journal\":{\"name\":\"ACM Transactions on Reconfigurable Technology and Systems\",\"volume\":\"37 1\",\"pages\":\"\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2023-05-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM Transactions on Reconfigurable Technology and Systems\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/https://dl.acm.org/doi/10.1145/3595297\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Transactions on Reconfigurable Technology and Systems","FirstCategoryId":"94","ListUrlMain":"https://doi.org/https://dl.acm.org/doi/10.1145/3595297","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
In genome analysis, it is often important to identify variants from a reference genome. However, identifying variants that occur with low frequency can be challenging, as it is computationally intensive to do so accurately. LoFreq is a widely used program that is adept at identifying low frequency variants. This paper presents a design framework for an FPGA-based accelerator for LoFreq. In particular, this accelerator is targeted at virus analysis, which is particularly challenging, compared to human genome analysis, as the characteristics of the data to be analyzed are fundamentally different. Across the design space, this accelerator can achieve up to 120 × speedups on the core computation of LoFreq and speedups of up to 51.7 × across the entire program.
期刊介绍：
TRETS is the top journal focusing on research in, on, and with reconfigurable systems and on their underlying technology. The scope, rationale, and coverage by other journals are often limited to particular aspects of reconfigurable technology or reconfigurable systems. TRETS is a journal that covers reconfigurability in its own right.
Topics that would be appropriate for TRETS would include all levels of reconfigurable system abstractions and all aspects of reconfigurable technology including platforms, programming environments and application successes that support these systems for computing or other applications.
-The board and systems architectures of a reconfigurable platform.
-Programming environments of reconfigurable systems, especially those designed for use with reconfigurable systems that will lead to increased programmer productivity.
-Languages and compilers for reconfigurable systems.
-Logic synthesis and related tools, as they relate to reconfigurable systems.
-Applications on which success can be demonstrated.
The underlying technology from which reconfigurable systems are developed. (Currently this technology is that of FPGAs, but research on the nature and use of follow-on technologies is appropriate for TRETS.)
In considering whether a paper is suitable for TRETS, the foremost question should be whether reconfigurability has been essential to success. Topics such as architecture, programming languages, compilers, and environments, logic synthesis, and high performance applications are all suitable if the context is appropriate. For example, an architecture for an embedded application that happens to use FPGAs is not necessarily suitable for TRETS, but an architecture using FPGAs for which the reconfigurability of the FPGAs is an inherent part of the specifications (perhaps due to a need for re-use on multiple applications) would be appropriate for TRETS.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
