Commodity Hardware Acceleration of Popular Modeling Software for Structural Biolo

描述(由申请人提供)：对维持身体健康和抗击疾病的细胞的实验室和临床研究越来越多地得到对细胞过程和诊断工具的计算建模的补充。涉及纳米级结构和过程的建模在结构细胞生物学、细胞力学和纳米传感器开发方面特别成功。PI的实验室开发了一个软件包NAMD/VMD，由NIH资助的数千名研究人员以及研究病毒感染、开发新抗生素和提供更快基因测序方法的药理学和生物技术公司使用。计算工具的影响通常受到计算速度、硬件成本和建模精度的限制，这些工具提供了以其他方式无法获得的深刻的微观视图。最近计算机技术的巨大进步，即多核处理器和图形处理单元(GPU)，现在有望成为加速生物医学计算的手段，同时降低硬件成本并允许更准确的模拟。所需的主要投资是程序员的独创性和时间，因为多核处理器的有效编程需要不同于传统处理单元的策略和算法。PI和两名合作PI在生物物理、计算机科学和电气工程方面有着互补的背景，他们寻求资金聘请两名程序员和一名研究生研究助理，对多核处理器进行编程，并在生物医学方面服务于三项任务：确定细胞过程中出现的超大型细胞结构，调查细胞动力学背后的机械机制，以及提高纳米设备模拟的准确性，以更好地指导医疗诊断中传感器的开发。五个计算瓶颈将通过涉及具有多核能力的软件的革命性解决方案来解决。在结构生物学中，通过所谓的网格力和互相关优化来合并结晶学和电子显微镜数据将得到极大的增强；在人体细胞的微观力学中，交互式模拟和更好的分析将使研究人员能够在飞行中感觉和看到模拟的细胞机械响应，而不是仅仅在几小时或几天后；在纳米医学中，原子分辨率计算显微镜将为设计工程师提供比以往任何时候都更精确的设备行为视图。所采取的方法以一种独特的方式将生物医学与物理、化学、并行编程和计算机处理单元的知识相结合。所实现的软件改进不仅将服务于所述的应用，而且将服务于现代计算生物医学的许多进一步的应用。 与公共健康相关：该项目寻求通过可以在新一代计算机芯片上运行的新软件来提高生物医学计算的速度和降低成本。该软件目前已被数千名研究人员使用，有助于了解细胞如何维持健康和与疾病作斗争，开发新抗生素等药物，以及设计遗传疾病传感器。计划中的进步需要新的数学算法和编程策略。

DESCRIPTION (provided by applicant): Laboratory and clinical studies of cells maintaining the body's health and battling disease are increasingly complemented by computational modeling of cellular processes and diagnostic tools. Modeling involving nanoscale structures and processes has been particularly successful in structural cell biology, cellular mechanics, and in nanosensor development. The PI's laboratory develops a software package, NAMD/VMD, that is used by thousands of NIH-funded researchers as well as by pharmacological and biotechnological companies studying viral infection, developing new antibiotics, and providing faster gene sequencing methods. The impact of the computational tools, which provide profound microscopic views not available otherwise, is often limited by computing speed, hardware costs, and modeling ac- curacy. Recent dramatic advances in computer technology, namely multi-core processors and graphics processing units (GPUs), promise now a means of accelerating biomedical computing, while decreasing hardware cost and permitting more accurate simulations. The main investment needed is programmer ingenuity and time, as effective programming of multi-core processors requires different strategies and algorithms than used for conventional processing units. The PI and two co-PIs, long time collaborators with complementary backgrounds in biophysics, computer science, and electrical engineering, seek funds to hire two programmers and a graduate student research assistant, to program multi-core processors and serve three missions in biomedicine: the determination of very large cellular structures as they arise in cellular processes, the investigation of mechanical mechanisms underlying cellular dynamics, and the improvement of nanodevice simulation accuracy to better guide the development of sensors in medical diagnostics. Five computational bottlenecks will be addressed through revolutionary solutions involving multi-core capable software. In structural biology the merging of crystallographic and electron microscopy data through so-called grid forces and cross-correlation optimization will be greatly enhanced; in micro-mechanics of the body's cells interactive simulation and better analysis will permit investigators to feel and see simulated cellular mechanical responses on-the-fly, rather than only after hours or days; in nanomedicine an atomic resolution computational microscope will offer design engineers more accurate views of device behavior than ever achieved before. The approach taken combines biomedicine with physics, chemistry, parallel programming, and computer processing unit know-how in a unique way. Software improvements achieved will not only serve the stated applications, but many further applications of modern computational biomedicine. PUBLIC HEALTH RELEVANCE: This project seeks to increase the speed and reduce the cost of biomedical computing through new software that can run on a new generation of computer chips. The software, presently already in use by thousands of investigators, aids in understanding how cells maintain health and battle disease, in developing drugs like new antibiotics, and in designing sensors for genetic diseases. The planned advances require new mathematical algorithms and programming strategies.