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The main purpose of the FireHose Streaming Benchmarks is to enable comparison of streaming software and hardware, both quantitatively vis-a-vis the rate at which they can process data, and qualitatively by judging the effort involved to implement and run the benchmarks.

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FireHose suite of stream processing benchmarks.

FireHose is meant to invoke the imagery of drinking from a firehose of streaming data.

Copyright (2013) Sandia Corporation. Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation, the U.S. Government retains certain rights in this software. This software is distributed under the Berkeley Software Distribution (BSD) License.


The main purpose of the FireHose Streaming Benchmarks is to enable comparison of streaming software and hardware, both quantitatively vis-a-vis the rate at which they can process data, and qualitatively by judging the effort involved to implement and run the benchmarks.

The benchmarks themsleves each have a generator and analytic. Code for the generators is provided and is meant to be run as-is. Reference implementations for the analytics are also provided; users are free to re-implement them for other streaming frameworks or to optimize them for their hardware.

The originators of FireHose are Karl Anderson and Steve Plimpton, who can be contacted at keander@sandia.gov and sjplimp@sandia.gov. The FireHose WWW Site at http://firehose.sandia.gov (when it is put on-line) has more information as well as tabulated performance results.

This FireHose distribution includes the following files and directories:

README      this file
LICENSE     the BSD License
analytics   code for the analytics
doc         HTML documentation
generators  code for the generators
tools       auxiliary scripts useful in running the benchmarks
results     output files of correct benchmark answers

Point your browser at doc/README.html to get started.

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The main purpose of the FireHose Streaming Benchmarks is to enable comparison of streaming software and hardware, both quantitatively vis-a-vis the rate at which they can process data, and qualitatively by judging the effort involved to implement and run the benchmarks.

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