Accelerator-Rich Architectures with Applications to Healthcare

许多医疗保健应用程序都面临着巨大的计算挑战。例如，通用计算技术对个性化癌症治疗的计算需求高得令人望而却步，因为肿瘤的异质性需要很大的测序深度，结构像差很难用今天的方法检测，并且肿瘤具有进化的能力，即，在治疗过程中可能会对同一肿瘤进行多次检测。该项目的目标是应用加州大学洛杉矶分校领域特定计算中心(CDSC)开发的领域特定定制计算技术，以极大地加快一些关键医疗保健应用的计算速度。CDSC在NSF的支持下于2009年成立，着眼于并行化之外，专注于领域特定的定制，作为提高电源性能效率的下一项颠覆性技术。在过去的四年中，CDSC通过在开发可定制的异质计算技术方面的创新，展示了显著的性能和能效。NSF创新过渡计划下的当前提案利用CDSC的研究成果，重点关注关键研究问题和解决方案，使特定领域的可定制计算对于创新过渡到行业具有可行性和实用性，具体而言，该项目将开发加速器丰富的架构以及用于个性化癌症治疗、医学图像处理的统一自适应运行时系统，并将能够部署在几个能够处理海量最先进实时患者数据的高能效可编程平台上。该中心将通过与加州大学洛杉矶分校工程和多样性卓越中心的合作，继续其已经成功的外展计划，让高度多样化的高中生和本科生参与暑期研究。我们项目的成功将使医学成像分析和个性化癌症治疗取得重大进展，这将极大地提高医疗质量，同时降低成本。工业伙伴参与该INTRANS项目将极大地促进研究成果从该项目向能效计算行业的创新过渡。

Many healthcare applications present significant computational challenges. For example, the computational demand for personalized cancer treatment is prohibitively high for the general-purpose computing technologies, as tumor heterogeneity requires great sequencing depths, structural aberrations are difficult to detect with today's methods, and the tumor has the ability to evolve i.e., the same tumor might be assayed a great many times during the course of treatment. The goal of this project is to apply the domain-specific customized computing techniques developed by the Center for Domain-Specific Computing (CDSC) at UCLA to greatly accelerate computation for some key healthcare applications. The CDSC, established in 2009 with the support of the NSF, looks beyond parallelization, and focuses on domain-specific customization as the next disruptive technology for power-performance efficiency improvement. In the past four years, CDSC has demonstrated significant performance and energy efficiency with innovation in developing customizable heterogeneous computing technologies. The current proposal under the NSF Innovation Transition program leverages the research results from CDSC, and focuses on key research problems and solutions to make domain-specific customizable computing feasible and practical for innovation transition to the industry, Specifically, the project will develop accelerator-rich architectures along with unified adaptive runtime systems for personalized cancer treatment, medical image processing, and will enable deployment in several energy efficient programmable platforms capable of handling huge volumes of state of the art real time patient data. The center will continue its already successful outreach program, through a partnership with the UCLA Center for Excellence in Engineering and Diversity, to involve highly diversified high school and undergraduate students for summer research. The success of our project will enable significant advances in medical imaging analysis and personalized cancer treatment, which will greatly improve healthcare quality while reducing cost. The participation of the industrial partner in this InTrans project will greatly facilitate the innovation transition of research results from this project to industry for energy-efficient computing.