memory simulation, memory hierarchy, automatic program parallelisation This paper describes a performance estimating system developed at the University of Southampton for estimating the execution time of SPMD Fortran programs on distributed memory parallel systems. The system called PERFORM

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Scalability has been used extensively as a de facto performance criterion for evaluating parallel algorithms and architectures. However, for many, scalability has theoretical interests only since it does not reveal execution time. In this paper, the relation between scalability and execution time

be used to do more accurate CPU scheduling. We found that by considering both frame type and size, it is possible to construct a linear model of MPEG decoding with R 2 values of 0.97 and higher. Moreover, this model can be used to predict decoding times at both the frame and packet level that are almost

that the computations are completed within their associated time bounds; otherwise severe damages may result, or the system may be unusable. Therefore, a schedulability analysis has to be performed which guarantees that all timing constraints will be met. Schedulability analyses require upper bounds for the execution

Abstract This paper presents an implementation of an Execution Time Monitor (ETM) which can be applied in a resource management framework, such as the one proposed in the Open Media Platform (OMP)

this paper, we address the question of what to communicate. We describe two paradigms for representing limitations on communication and present an algorithm that enables multi-agent teams to make execution-time decisions on how to e#ectively utilize available communication resources

¢   predictable = adjective, able to be predicted ¢   to predict = verb, state that a specified event will happen in the future Fuzzy term in the WCET community. May refer to the ability to predict: ¢   the WCET precisely, ¢   the execution time precisely, ¢   the WCET efficiently. Notion

f their execution time on non-local references. Anal- ogous results for UMA multiprocessors [6] suggest that applications spend 20-30% of their time on cache misses. These percentages will vary depending on the scheduling policy; Gaussian elimination spends 33% of its execution time on non

Wireless ad-hoc sensor networks have emerged as an interesting and important research area in the last few years. The applications envisioned for such networks require collaborative execution of a distributed task amongst a large set of sensor nodes. This is realized by exchanging messages