Parallel Extension of a Dynamic Performance Forecasting Tool

Eddy Caron, Frédéric Desprez, Frédéric Suter

Abstract


This paper presents an extension of a performance evaluation library called Fast to handle parallel routines. Fast is a dynamic performance forecasting tool in a grid environment. We propose to combine estimations given by Fast about sequential computation routines and network availability to parallel routine models coming from code analysis.

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