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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)

In the current version, the format of generated traces is the JSON Batsim workload format, compatible with the Resource and Jobs Management System (RJMS) simulator Batsim.

Installation

pip3 install grog

Usage

usage: grog-tool [-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        server speed in Gflops, default = 14.72 (similar to Taurus a cluster in Grid5000, France)

Example

Simple example, uses the default values to generate a file called workload.json

grog-tool workload.json

Longer example, uses some flags to generate a longer duration (here one year).

grog-tool --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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