Trace-based simulation

In this article we are going to analyze Trace-based simulation, a topic that has generated great interest in recent times. Trace-based simulation is a topic that has captured the attention of many people due to its relevance in different areas, from science to popular culture. Furthermore, Trace-based simulation has been the subject of numerous debates and discussions, which has contributed to its growing importance in today's society. Throughout this article, we will explore different aspects related to Trace-based simulation, from its origin and evolution to its impact today. Through detailed analysis, we will try to shed light on this topic and provide a more complete and deeper insight into Trace-based simulation.

In computer science, trace-based simulation refers to system simulation performed by looking at traces of program execution or system component access with the purpose of performance prediction.

Trace-based simulation may be used in a variety of applications, from the analysis of solid state disks to the message passing performance on very large computer clusters.

Traced-based simulators usually have two components: one that executes actions and stores the results (i.e. traces) and another which reads the log files of traces and interpolates them to new (and often more complex) scenarios.

For instance, in the case of large computer cluster design, the execution takes place on a small number of nodes, and traces are left in log files. The simulator reads those log files and simulates performance on a much larger number of nodes, thus providing a view of the performance of very large applications, based on the execution traces on a much smaller number of nodes.

See also

References

  1. ^ a b Software Technologies for Embedded and Ubiquitous Systems edited by Sunggu Lee and Priya Narasimhan 2009 ISBN 3642102646 page 28
  2. ^ a b c Languages and Compilers for Parallel Computing edited by Keith Cooper, John Mellor-Crummey and Vivek Sarkar 2011 ISBN 3642195946 pages 202-203
  3. ^ Petascale Computing: Algorithms and Applications by David A. Bader 2007 ISBN 1584889098 pages 435-435
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