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Efficient Parallel Programming on Datacenter Platforms with Disciplined Memory Access
MPhil Thesis Defence Title: "Efficient Parallel Programming on Datacenter Platforms with Disciplined Memory Access" By Mr. Xiang GAO Abstract Many distributed system technologies and programming frameworks are developed to support parallelized computation on the datacenter platform. While simplifying data-centric parallel computation, existing system technologies and application frameworks, however, exhibit limitation in their capability, efficacy and programmability in supporting sophisticated applications. In this paper, we present a distributed multitasking engine, together with a new programming language and a compiler, to support large-scale parallel computing on compute clusters with loosely-coupled commodity servers. The system, called Disciplined Runtime, is built under the principle of a disciplined memory access model, which means the programmer and the compiler furnish memory access information to the system so that the latter can detect memory access patterns and locality preferences at run time. Without limiting the expressing capability, this makes the memory access behavior known to the memory subsystem and the scheduler, and this information can be utilized to significantly improve the efficiency and performance of the system. The Disciplined Runtime provides distributed multitasking in a large uniform memory space with transactional semantics, and the new programming language enables programmers to provide memory access information of parallel tasks in a straightforward way so that the programs naturally follow the disciplined memory access model. Evaluation on both our research testbed and Amazon EC2 show that the new multitasking engine provides high performance and scalability on 32 physical compute servers and 256 large EC2 instances. Date: Friday, 21 September 2012 Time: 2:00pm – 4:00pm Venue: Room 3402 Lifts 17/18 Committee Members: Dr. Lin Gu (Supervisor) Dr. Charles Zhang (Supervisor) Dr. Qiong Luo (Chairperson) Prof. Shing-Chi Cheung **** ALL are Welcome ****