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HiFPTuner is a dynamic precision tuner. Different from other tuners, it explores the community structure of the floating-point variables and uses the community structure to guide precision tuning to find better precision configurations in less time.

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HiFPTuner

Exploiting community structure for floating-point precision tuning, ISSTA'18

INSTALL

You can either use docker or build from scratch which is the hard way to use HiFPTuner.

Use docker

Pull Docker Image from Docker Hub

docker pull hguo15/hifptuner:vo
docker run -ti --name=hifptuner hguo15/hifptuner:vo

Or Build a Doker Image by yourself

git clone https://github.com/ucd-plse/HiFPTuner.git
cd HiFPTuner
docker build -t docker-hifptuner .
docker run -ti --name=hifptuner docker-hifptuner

Build from scratch

Prerequisites:

1. llvm 3.0 & 3.8

2. Precimonious
    repo.: https://github.com/ucd-plse/precimonious 

3. NetworkX 2.2 python package
    install: pip install 'networkx==2.2'
    repo.:   https://github.com/networkx/networkx

4. Community python package
    install: pip install python-louvain
    repo.: https://bitbucket.org/taynaud/python-louvain

5. pygraphviz and other graph python packages
    pip install graphviz
    pip install pygraphviz
    apt-get install python-matplotlib
    apt-get install libgraphviz-dev
    apt-get install python-dev

Install HiFPTuner:

1. git clone https://github.com/ucd-plse/HiFPTuner.git
2. cd HiFPTuner/precimonious/logging
3. make clean; make
4. switch to llvm 3.8
   in the docker image of HiFPTuner, switching to llvm 3.8 as following, 
   4.1 modify ~/.bashrc: $LLVM_VERSION=llvm-3.8
   4.2 . ~/.bashrc
5. cd HiFPTuner/src/varDeps
6. make clean; make

Example

To generate HiFPTuner config files : "sorted_partition.json"

1. $cd HiFPTuner/examples/simpsons

2. generate llvm_3.0 bitcode file
    switch to llvm 3.0
    $clang -c -emit-llvm simpsons.c -o simpsons.bc
    $path/to/HiFPTuner/scripts/compile.sh simpsons.bc

3. Run llvm analysis and transformation passes to attain the dependence graph
    switch to llvm 3.8
    $path/to/HiFPTuner/scripts/analyze.sh json_simpsons.bc
    (Check outputs: "varDepPairs_pro.json" and "edgeProfilingOut.json" for the dependece pairs and edge weights.)

4. Run Networkx and community packages to attain the unsorted and sorted hierarchy
    $path/to/HiFPTuner/scripts/config.sh
    (Check outputs: "partition.json", "sorted_partition.json" and "topolOrder_pro.json" for the unsorted hierarchy, sorted hierarchy and the topological ordered variable list)
    (Also, check varDepGraph_pro.png for the visualized dependence graph)

Dynamic TUNING

1. switch to llvm 3.0

2. create current precision configuration file
  $path/to/HiFPTuner/precimonious/scripts/pconfig.sh simpsons .

3. create search space
  $path/to/HiFPTuner/precimonious/scripts/search.sh simpsons .

4. dynamic tuning
  $python -O path/to/HiFPTuner/precimonious/scripts/dd2_prof.py simpsons.bc search_simpsons.json config_simpsons.json sorted_partition.json

About

HiFPTuner is a dynamic precision tuner. Different from other tuners, it explores the community structure of the floating-point variables and uses the community structure to guide precision tuning to find better precision configurations in less time.

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