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GeneRic wOrkload Generator

Project description

GROG a GeneRic wOrkload Generator

GROG is a generic workload generator (Cloud and HPC like) to create datasets of tasks for scheduling evaluation.

This workload generator is based on a dataset from Google studied in Modeling, classifying and generating large-scale Google-like workload published in the SUSCOM journal (open access version)

The current version only generate traces for the BatSim simulator of DataCenters.

Installation

pip3 install grog

Usage

usage: grog [-h] [--seed SEED] [--offline] [--duration DURATION] [--density DENSITY] [--speed SPEED] output_file

positional arguments:
  output_file          filename to store the workload

options:
  -h, --help           show this help message and exit
  --seed SEED          change seed, default: 42
  --offline            to change from online to offline
  --duration DURATION  duration in days, default: 3
  --density DENSITY    hourly density, default:50
  --speed SPEED        processor density in GHz, default = 1.4

Example

grog workload.json
grog --offline --seed 128 --duration 365 --density 5 long_workload.json

Citation

Please cite (bibtex version) the following if you use this tool

Georges da Costa, Léo Grange, Inès De Courchelle. Modeling, classifying and generating large-scale Google-like workload. Sustainable Computing : Informatics and Systems, Elsevier, 2018, 19, pp.305-314. ff10.1016/j.suscom.2017.12.004ff.

Misc

  • This software is under the GPLv3.
  • The current point of contact is Georges.Da-Costa@irit.fr
  • The last version is available here : https://gitlab.irit.fr/sepia-pub/grog
  • The current internal API migh evolve, but command line interface should be stable
  • The time needed for generating dense and/or long duration traces might be long

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