Customizable Domain-Specific Computing

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"This award is funded under the American Recovery and Reinvestment Act of 2009(Public Law 111-5)."Customizable Domain-Specific ComputingTo meet ever-increasing computing needs and overcome power density limitations, the computing industry has entered the era of parallelization, with tens to hundreds of computing cores integrated into a single processor; and hundreds to thousands of computing servers connected in warehouse-scale data centers. However, such highly parallel, general-purpose computing systems still face serious challenges in terms of performance, energy, heat dissipation, space, and cost. In this project we look beyond parallelization and focus on domain-specific customization as the next disruptive technology to bring orders-of-magnitude power-performance efficiency improvement to important application domains. The intellectual merit of this project includes development of a general methodology for creating novel customizable architecture platforms and the associated compilation tools and runtime management environment to support domain-specific computing to: 1) achieve orders-of-magnitude computing efficiency improvement for applications in a specific domain; and 2) demon-strate that such improvement can be obtained with little or no impact on design productivity, so that it can be deployed in a wide range of application domains. Our proposed domain-specific customizable computing platform includes: 1) a wide range of customizable computing elements, from heterogeneous fixed cores to coarse-grain customizable cores, and to fine-grain field-programmable circuit fabrics; 2) customizable high-performance radio frequency interconnects; 3) highly automated compilation tools and runtime management software systems for application development; and 4) a general, reusable methodology for customizable computing applicable across different domains. By combining these critical capabilities, we shall deliver a super-computer-in-a-box that is customized to a particular application domain to enable disruptive innovations in that domain. This approach will be demonstrated in several important application domains in healthcare. The broader impact of this project will be measured by the new digital revolution enabled by customized computing. We will demonstrate the feasibility and advantages of the proposed research in the domain of healthcare, given its significant impact on the national economy and quality of life issues. In particular, we focus our effort on revolutionizing the role of medical imaging and hemodynamic modeling in healthcare, providing much more cost-efficient, convenient solutions for preventative, diagnostic, and therapeutic procedures to dramatically improve healthcare quality, efficiency, and patient outcomes. The broader impact of this project also includes the integration of research and education, exposing graduate, undergraduate, and high school stu-dents to the new concepts and research from this project via several new courses jointly developed and shared by researchers in our newly established Center for Domain-Specific Computing (CSDC). Summer research fellowship programs to support high school and undergraduate students will be provided by CSDC. Our goal is to train a new generation of students who are prepared for customized parallelization and computing, and can effectively apply such techniques to many areas of our society, thus furthering the digital revolution. Special efforts are being made to attract underrepresented students at all levels via partnerships with campus organizations focused on diversity, such as the UCLA Center for Excellence in Engineering and Diversity.This research will be carried out as a collaborative effort between four universities: UCLA (the lead institution), Rice, UC Santa Barbara, and Ohio State. The research team consists of a group of highly accomplished researchers with diversified backgrounds, including computer science and engineering, electrical engineering, medicine, and applied mathematics. For more information, please visit http://cdsc.cs.ucla.edu.