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DEVS (Discrete Event Systems Specification) models are widely employed for simulation-based performance evaluation of discrete event systems. Performance modeling of such a system requires a pruning of a set of components, or objects, within the system in its subset which are eventually transformed into simulation models. Such modeling is objective-driven in that simulation models may be abstra...

What do you do to start reading probability stochastic processes and queueing theory the mathematics of computer performance model? Searching the book that you love to read first or find an interesting book that will make you want to read? Everybody has difference with their reason of reading a book. Actuary, reading habit must be from earlier. Many people may be love to read, but not a book. I...

despite the extensive deployment of multi-core architectures in the past few years, the design and optimization of each single processing core is still a fresh field in computing .on the other hand, having a design procedure (used to solve the problems related to the design of a single processing core )makes it possible to apply the proposed solutions to specific-purpose processing cores .the i...

The query-performance prediction task is estimating retrieval effectiveness in the absence of relevance judgments. The task becomes highly challenging over the Web due to, among other reasons, the effect of low quality (e.g., spam) documents on retrieval performance. To address this challenge, we present a novel prediction approach that utilizes queryindependent document-quality measures. While...

The goal of this project was to try and accurately model the performance of the F-104C Starfighter which achieved a new world altitude record on December 14 th , 1959. In completing the project, the goal was to gain a better understanding of the performance modeling of today and flight test methods from the past while creating a drag polar and engine deck which could be used for future applicat...

The query-performance prediction task is estimating the effectiveness of a search performed in response to a query in lack of relevance judgments. Post-retrieval predictors analyze the result list of top-retrieved documents. While many of these previously proposed predictors are supposedly based on different principles, we show that they can actually be derived from a novel unified prediction f...

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The learning curves of optimisation algorithms, plotting the evolution of the objective vs. runtime spent. can be viewed as a sample of longitudinal data. In this paper we describe mixed-effects modeling, a standard technique in longitudinal data analysis, and give an example of its application to algorithm performance modeling.

Workload characterization is an important and basic step for performance modeling and capacity planning. Traditional approaches for workload characterization often require sophisticated and time-consuming user assistance. In this paper we describe a number of algorithms for automatically classifying workloads and for determining what resources a workload used even when the operating system does...