Justin Y. Shi

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  • Justin Y. Shi
  • 2009 11th IEEE International Conference on High…
  • 2009
The “main-stream” inter-process communication models (share-memory and message-passing) require the programmers responsible for the construction of a very complex state machine for parallel processing. This has resulted multiple difficulties including programming, performance tuning, debugging, job scheduling and fault tolerance. The most(More)
The availability of high performance computing (HPC) clouds requires scalability analysis of parallel programs for multiple different environments in order to maximize the promised economic benefits. Unlike traditional HPC application performance studies that aim to predict performances of like-kind processors, this paper reports an instrumentation assisted(More)
Before the emergence of commercial cloud computing, interests in parallel algorithm analysis have been mostly academic. When computing and communication resources are charged by hours, cost effective parallel processing would become a required skill. This paper reports a resource planning study using a method derived from classical program time complexity(More)
General purpose GPU (GPGPU) computing has produced the fastest running supercomputers in the world. For continued sustainable progress, GPU computing at scale also need to address two open issues: a) how increase applications mean time between failures (MTBF) as we increase supercomputer's component counts, and b) how to minimize unnecessary energy(More)
This paper reports an application dependent network design for extreme scale high performance computing (HPC) applications. Traditional scalable network designs focus on fast point-to-point transmission of generic data packets. The proposed network focuses on the sustainability of high performance computing applications by statistical multiplexing of(More)
Traditional HPC (High Performance Computing) clusters are best suited for well-formed calculations. The orderly batch-oriented HPC cluster offers maximal potential for performance per application, but limits resource efficiency and user flexibility. An HPC cloud can host multiple virtual HPC clusters, giving the scientists unprecedented flexibility for(More)
Extreme scale computing has no implied scaling limit. The impossibility of implementing reliable communication between crashing hosts prohibits explicit-communication primitives in extreme scale applications. However, the alternatives are not well investigated. This paper reports the development and experimentation of a prototype implicit communication(More)
For the last three decades, end-to-end computing has been the de facto paradigm for distributed and parallel computing. MPI (Message Passing Interface), RPC (Remote Procedure Call), OpenMP (share memory) and RMI (Remote Method Invocation) are all end-to-end protocols from the same computing paradigm. A myth persisted since 1990's that while the data(More)