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Energy consumption is one of the main limiting factors for designing large scale Clouds. Evaluating the energy consumption of Clouds networking architectures and providing multi-level views required by providers and users, is a challenging issue. In this paper, we show how to evaluate and understand network choices (protocols, topologies) in terms of contributions to the energy consumption of the...
Modern parallel computing platforms exhibit substantial variation in communication performance between on-socket, on-node and inter-rack locations. When application interaction patterns are irregular, communication-aware process placement on such platforms can be critical for overall runtime. Understanding program interaction patterns can be valuable in order to minimize the impact of capacity variations...
Recently, a new environment for high performance peer-to-peer distributed computing was proposed. This environment, named P2PDC, addresses stable or volatile systems communicating in a decentralized manner using the self-adaptive protocol P2PSAP. P2PDC is devoted to task parallel applications like numerical simulation problems or optimization problems solved via parallel or distributed iterative algorithms...
Predicting distributed application performance is a constant challenge to researchers, with an increased difficulty when heterogeneous systems are involved. Research conducted so far is limited by application type, programming language, or targeted system. The employed models become too complex and prediction cost increases significantly. We propose dPerf, a new performance prediction tool. In dPerf,...
P2PDC is an environment for high performance peer to peer computing that allows direct communication between peers. This environment is based on P2PSAP, a self adaptive communication protocol. P2PDC is suited to the solution of large scale numerical simulation problems via distributed iterative methods. dPerf is a performance prediction environment for parallel and distributed applications, with primary...
An ongoing work is presented for accurately predicting the performance of distributed applications in heterogeneous systems. We are developing dPerf, a tool built using the Rose framework for performing static analysis and an automatic instrumentation on the input source code of programs written in C, C++ or Fortran. The accuracy in predicting program computation time resides in using hardware counters,...
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