Resampling with Feedback: A New Paradigm of Using Workload Data for Performance Evaluation

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations


Reliable performance evaluations require representative workloads. This has led to the use of accounting logs from production systems as a source for workload data in simulations. But using such logs directly suffers from various deficiencies, such as providing data about only one specific situation, and lack of flexibility, namely the inability to adjust the workload as needed. Creating workload models solves some of these problems but creates others, most notably the danger of missing out on important details that were not recognized in advance, and therefore not included in the model. Resampling solves many of these deficiencies by combining the best of both worlds. It is based on partitioning real workloads into basic components (e.g. the jobs contributed by different users), and then generating new workloads by sampling from this pool of basic components. The generated workloads are adjusted dynamically to the conditions of the simulated system using a feedback loop, which may adjust the throughput. Using this methodology analysts can create multiple varied (but related) workloads from the same original log, all the time retaining much of the structure that exists in the original workload. Resampling with feedback thus provides a new way to use workload logs which benefits from the realism of logs while eliminating many of their drawbacks. In addition, it enables evaluations of throughput effects that are impossible with static workloads.
Original languageEnglish
Title of host publicationEuro-Par 2016: Parallel Processing
Subtitle of host publication22nd International Conference on Parallel and Distributed Computing, Grenoble, France, August 24-26, 2016, Proceedings
EditorsPierre-François Dutot, Denis Trystram
Place of PublicationSwitzerland
PublisherSpringer International Publishing
Number of pages19
ISBN (Electronic)9783319436593
ISBN (Print)9783319436586
StatePublished - 9 Aug 2016
Event22nd International Conference on Parallel and Distributed Computing, Euro-Par 2016 - Grenoble, France
Duration: 24 Aug 201626 Aug 2016

Publication series

NameLecture Notes in Computer Science
PublisherSpringer International Publishing
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference22nd International Conference on Parallel and Distributed Computing, Euro-Par 2016

Bibliographical note

Funding Information:
The work described here was by and large performed by several outstanding students, especially Edi Shmueli, Netanel Zakay, and Dan Tsafrir. Our work was supported by the Israel Science Foundation (grants no. 219/99 and 167/03) and the Ministry of Science and Technology, Israel.

Publisher Copyright:
© Springer International Publishing Switzerland 2016.


  • Temporary User
  • Simulated User
  • Workload Model
  • Real Workload
  • Representative Workload


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