Computing Architectures and Programming Methodologies for Heterogeneous High-Performance Computing and Embedded Applications

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Modern compilers and programming tools have made computers accessible to the experts in many domains so that they can develop their own applications. However, the need to use parallelism to get performance today adds significant programming challenges that are not easily understood by the average programmer. Moreover, programming is becoming even more difficult as we move to specialized architectures such as GPGPUs (General-Purpose Graphics Processing Units) and FPGAs (Field-Programmable Gate Arrays) to find more performance and better energy efficiency. Most domain experts do not have the expertise to make effective use of such computing technologies. The plan in this proposal is to work with several domain experts who must have significant computational requirements of a grand challenge nature -- large problems with significant impact. Modeling the brain is one example. The key element of the proposed work is that a computer engineering (CE) graduate student will be "embedded" with the collaborating group that needs help developing an application. This will allow the CE student to gain intimate knowledge about the requirements of the domain experts while helping them with their application. The expectation is that this collaboration will inspire new approaches to computing that will result in novel changes to computer architectures and systems. Most computer architects address very specific low-level aspects of systems, such as the memory, the interconnect and the organization of the processors. This proposal recognizes that working applications are the tools of the domain-specific users. Building working applications on real systems will better inform the computer architect of the requirements for next-generation computing systems. At the same time, this approach to research provides a significant benefit to the domain-specific users by helping them to implement the most efficient and highest-performing applications that they can use to advance their own scientific research. This has the potential to create more immediate impact than the computer architecture study!