Fast Biosequence Annotation via Reconfigurable Hardware

通过可重新配置硬件进行快速生物序列注释

• 批准号: 7480772
• 负责人: Jeremy D Buhler
• 金额: $ 51.06万
• 依托单位: BECS TECHNOLOGY, INC.
• 依托单位国家: 美国
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-09-30 至 2010-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7480772
• 关键词: Acceleration; Accounting; Address; Algorithms; Amino Acid Sequence; Architecture; Bioinformatics; Biological; Biological Models; Biological databases; Blast Cell; Blast Phase; Collection; Computer software; Computers; Conceptions; DNA; DNA Sequence Rearrangement; Data; Data Sources; Databases; Development; Devices; Disadvantaged; Etiology; Evolution; Face; Family; Gene Structure; Genome; Genomics; Goals; Growth; Hereditary Disease; Hour; Human; Investigation; Logic; Minor; Modeling; Modems; Molecular Biology; Numbers; Operative Surgical Procedures; Peptide Sequence Determination; Performance; Phase; Pliability; Process; Proteomics; Purpose; Rate; Reading; Running; Small Business Technology Transfer Research; Source Code; Speed; Staging; Stream; System; Technology; Testing; Time; Today; Validation; Variant; Work; base; commercialization; comparative; cost; day; design; fly; genome database; heuristics; improved; innovation; novel; pathogen; programs; prototype; software development; text searching; tool

DESCRIPTION (provided by applicant): Databases of biological sequences have proven valuable for understanding the organization of human and other genomes, for unraveling the etiology of genetic disorders, and for studying medically important pathogens. Unfortunately, these databases are growing at an exponential rate, posing a severe problem for bio-sequence annotation. Specialized hardware implementations of sequence comparison can dramatically accelerate BLAST and other algorithms used to annotate sequences. However, the utility of these hardware accelerators is limited by inflexible functionality, lack of a clear upgrade path to faster components, and limitations on the rate at which bio-sequence data can be streamed to the comparison logic. This proposal seeks to construct a novel hardware-based bio-sequence accelerator, the "smart disk" engine that addresses limitations of existing accelerators. The proposed engine combines the flexibility of reconfigurable FPGA logic, which can be reprogrammed at will and easily upgraded while running at hardware speeds, with an innovative architecture that ties the comparison logic closely to an array of hard disks, guaranteeing massive data bandwidth into the comparison hardware. The smart disk engine is designed to accelerate all stages of BLAST-like similarity search algorithms, not just the final Smith- Waterman stage. Phase I of this fast-track STTR application proposes to build the initial prototype of the smart disk engine, to implement comparison logic mirroring the stages of the widely used BLAST pipeline, to construct a transparent software front end to the engine, and finally to evaluate the performance of the prototype on large-scale tasks in bio-sequence annotation. Key innovations in this phase will be the integration of FPGA logic with the mass storage system, modeling the performance of the new architecture, and development of software control that can rapidly reprogram the FPGAs to construct comparison pipelines optimized for different types of comparison (BLASTN, BLASTP, etc). At the end of this phase, the combined hardware and software of the smart disk prototype should implement at least BLASTN- and BLASTP-like computations, run at least 30x faster than 2003-era commodity general-purpose processors, and successfully hide the complexity of the engine's hardware from the biological end user.

描述（由申请人提供）：生物序列数据库已被证明对于理解人类和其他基因组的组织、解开遗传疾病的病因以及研究医学上重要的病原体是有价值的。不幸的是，这些数据库正以指数级速度增长，给生物序列注释带来了严重的问题。序列比较的专用硬件实现可以显著加速BLAST和用于注释序列的其他算法。然而，这些硬件加速器的实用性受到功能不灵活、缺乏到更快组件的明确升级路径以及生物序列数据流传输到比较逻辑的速率限制的限制。该提案旨在构建一种新的基于硬件的生物序列加速器，即解决现有加速器局限性的“智能磁盘”引擎。所提出的引擎结合了可重构FPGA逻辑的灵活性，可以随意重新编程，并在以硬件速度运行时轻松升级，同时采用创新的架构，将比较逻辑与硬盘阵列紧密联系在一起，保证大量数据带宽进入比较硬件。智能磁盘引擎旨在加速类似BLAST的相似性搜索算法的所有阶段，而不仅仅是最后的史密斯-沃特曼阶段。这个快速通道STTR应用程序的第一阶段建议构建智能磁盘引擎的初始原型，实现反映广泛使用的BLAST管道阶段的比较逻辑，构建引擎的透明软件前端，最后评估原型在生物序列注释中的大规模任务上的性能。这一阶段的关键创新将是FPGA逻辑与大容量存储系统的集成，新架构的性能建模，以及软件控制的开发，这些软件控制可以快速重新编程FPGA，以构建针对不同类型比较（BLASTF，BLASTP等）优化的比较管道。在这一阶段结束时，智能磁盘原型的硬件和软件组合应该至少实现BLASTP-like和BLASTP计算，运行速度至少比2003年时代的商品通用处理器快30倍，并成功地向生物最终用户隐藏引擎硬件的复杂性。