Accelerating Biomolecular Simulations on Reconfigurable Computing Hardware

加速可重构计算硬件上的生物分子模拟

• 批准号: 7532368
• 负责人: Pratul K Agarwal
• 金额: $ 23.07万
• 依托单位: UT-BATTELLE, LLC-OAK RIDGE NATIONAL LAB
• 依托单位国家: 美国
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-08-15 至 2010-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7532368
• 关键词: Acceleration; Algorithms; Area; Binding; Biochemical; Biochemical Reaction; Biological; Biology; Catalysis; Cell physiology; Code; Communities; Compatible; Complex; Computer Hardware; Computer software; Computers; Computing Methodologies; DNA; Data; Development; Devices; Docking; Enzymes; Excision; Future; Goals; Health; Heating; Hour; Investigation; Laws; Ligands; Mainstreaming; Medical; Membrane; Memory; Microprocessor; Modification; Movement; Numbers; Performance; Pharmaceutical Preparations; Process; Production; Protein Engineering; Proteins; Public Health; Purpose; Range; Research; Research Personnel; Solutions; Speed; Structure; System; Technology; Time; Transistors; Vendor; Work; computing resources; cost; data structure; design; drug discovery; engineering design; experience; interest; molecular dynamics; molecular recognition; multi-scale modeling; next generation; protein folding; simulation; small molecule; supercomputer

DESCRIPTION (provided by applicant): Accelerating biomolecular simulations will have a direct impact on investigations in many areas of health related research. Simulations of biomolecules are widely used for fundamental understanding of their structure, folding, dynamics and function. The underlying calculations in these simulations are computationally intensive and have benefited considerably from more than an order of magnitude increase in computer processor speeds in last decade alone. There is widespread interest in alternate hardware and software solutions that can speed-up these simulations, as physical challenges in the computing technology are currently placing the limits on future speed increase of processors. Here we propose the development of biomolecular simulations software for adaptive computing that includes Reconfigurable Computing (RC) hardware and General Purpose Graphical Processing Units (GPGPUs) devices. The RC hardware, including Field Programmable Gate Arrays (FPGAs), and GPGPUs provide a tremendous amount of raw computing power even at the desktop level at a fraction of power requirements and cost of multi-processors parallel systems. PMEMD and LAMMPS, widely used biomolecular simulation engines, will be ported and optimized for popular RC/GPGPU devices. Moreover a molecular dynamics (MD) kernel specially designed to efficiently exploit the computational power of current and future RC/GPGPU devices will be developed. The proposed work will benefit the wide community of biochemists, biophysicists and computational chemists. The availability of these codes optimized on adaptive computing hardware will allow the non-expert user to benefit without worrying about the porting and optimizing details. Moreover, the availability of performance profiling utilities and the optimized MD kernel will enable other groups of application code developers to extend our implementation to exploit future FPGA and GPGPU devices enabled platforms. PUBLIC HEALTH RELEVANCE: The development of proposed optimized biomolecular simulations software will have direct impact on health and medical related research in many different areas including biochemical/biophysical characterization of cellular processes, drug-discovery and protein engineering. Biomolecular simulation software is used to investigate biological complexes and activities including protein folding, enzyme catalysis, conformational changes associated with bimolecular function, molecular recognition of proteins, DNA, and biological membrane complexes as well as docking/binding of small compounds to biomolecules.

描述（由申请人提供）：加速生物分子模拟将对健康相关研究的许多领域的调查产生直接影响。生物分子模拟广泛用于对其结构、折叠、动力学和功能的基本理解。这些模拟中的基础计算属于计算密集型，并且仅在过去十年中就从计算机处理器速度超过一个数量级的增长中受益匪浅。人们对能够加速这些模拟的替代硬件和软件解决方案产生了广泛的兴趣，因为计算技术中的物理挑战目前限制了处理器未来速度的提高。在这里，我们建议开发用于自适应计算的生物分子模拟软件，其中包括可重构计算（RC）硬件和通用图形处理单元（GPGPU）设备。包括现场可编程门阵列 (FPGA) 和 GPGPU 在内的 RC 硬件即使在桌面级别也能提供巨大的原始计算能力，而功耗要求和成本仅为多处理器并行系统的一小部分。广泛使用的生物分子模拟引擎PMEMD和LAMMPS将针对流行的RC/GPGPU设备进行移植和优化。此外，还将开发专门设计用于有效利用当前和未来 RC/GPGPU 设备的计算能力的分子动力学 (MD) 内核。拟议的工作将使生物化学家、生物物理学家和计算化学家的广泛社区受益。这些在自适应计算硬件上优化的代码的可用性将使非专家用户受益，而无需担心移植和优化细节。此外，性能分析实用程序和优化的 MD 内核的可用性将使其他应用程序代码开发人员组能够扩展我们的实现，以利用未来支持 FPGA 和 GPGPU 设备的平台。公共健康相关性：所提出的优化生物分子模拟软件的开发将对许多不同领域的健康和医学相关研究产生直接影响，包括细胞过程的生化/生物物理表征、药物发现和蛋白质工程。生物分子模拟软件用于研究生物复合物和活性，包括蛋白质折叠、酶催化、与双分子功能相关的构象变化、蛋白质、DNA和生物膜复合物的分子识别以及小化合物与生物分子的对接/结合。