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An Optimal Execution Time Estimate of Static versus Dynamic Allocation in Multiprocessor Systems
No full textConsider a multiprocessor with identical processors,
executing parallel programs consisting of processes.
Let and denote the execution times for the program
with optimal static and dynamic allocations respectively, i. e. allocations
giving minimal execution time.
We derive a general and explicit formula for the maximal execution time ratio
,
where the maximum is taken over all programs consisting of processes.
Any interprocess dependency structure for the programs is allowed, only
avoiding deadlock.
Overhead for synchronization and reallocation is neglected.
Basic properties of the function are established, from which we obtain
a global description of the function. Plots of are included.
The results are obtained by investigating a mathematical formulation. The
mathematical tools involved are essentially tools of
elementary combinatorics. The formula is a combinatorial function applied on
certain extremal matrices corresponding to
extremal programs. It is mathematically complicated but rapidly computed for
reasonable and , in contrast to
the np-completeness of the problems of finding optimal allocations
Performance Comparison of Bursty Traffic Models
No full textModels of bursty arrival processes are reviewed and compared with re-
spect to their in uence on the performance of a single server system.
Considerable
variations are found between different models fitted to the same traffic, though
some models exhibit similar behaviour. Comparing the ability of the models to
reproduce the performance of an explicitly given parcel they all tend to fail
Evaluating Business Intelligence Software - Testing the SSAV Model
No full textChoosing the right Business Intelligence (BI) software is critical to
increasing productivity and effectiveness in organizations today. At the same
time it is a very elaborating and complex process to choose the right software
due to the fact that a large number of BI products exist on the market, which
are quite different and updated frequently. The objective of this study is to
develop and test a model for the evaluation of BI Software. The findings of the
study revealed that it is difficult to declare what is the most competitive BI
software as what is good for one user might not be good for another depending
on their different business needs. Having said that the study initiated a new
classification of BI Software vendors depending on the degree to which they
comply with the functions in the Competitive Intelligence (CI) cycle. The
software tested was divided into five categories: Fully complete, Complete,
Semi Complete, Incomplete and Insubstantial. We conclude that the SSAV (Solberg
Søilen, Amara, Vriens) Model Together with some proposed non technological
variables and a classification developed can be used as a user's selection tool
for deciding which BI Software to purchase