kerncraft 0.4.3

Loop Kernel Analysis and Performance Modeling Toolkit

kerncraft

Loop Kernel Analysis and Performance Modeling Toolkit

This tool allows automatic analysis of loop kernels using the Execution Cache Memory (ECM) model, the Roofline model and actual benchmarks. kerncraft provides a framework to investigate the data reuse and cache requirements by static code analysis. In combination with the Intel IACA tool kerncraft can give a good overview of both in-core and memory bottlenecks and use that data to apply performance models.

For a detailed documentation see publications in doc/.

Installation

Run: pip install --user kerncraft for the latest release, or python ./setup.py install if you cloned this repository.

Additional requirements are:

• Intel IACA tool, with (working) iaca.sh in PATH environment variable (used by ECM, ECMCPU and RooflineIACA models)

• likwid (used in Benchmark model and by likwid_bench_auto.py)

Usage

1. Get an example kernel and machine file from the examples directory

wget https://raw.githubusercontent.com/RRZE-HPC/kerncraft/master/examples/machine-files/phinally.yaml

wget https://raw.githubusercontent.com/RRZE-HPC/kerncraft/master/examples/kernels/2d-5pt.c

2. Have a look at the machine file and change it to match your targeted machine (above we downloaded a file for a Sandy Bridge EP machine)

3. Run kerncraft

kerncraft -p ECM -m phinally.yaml 2d-5pt.c -D N 10000 -D M 10000 add -vv for more information on the kernel and ECM model analysis.

Credits

Implementation: Julian Hammer ECM Model (theory): Georg Hager, Holger Stengel, Jan Treibig LC generalization: Julian Hammer

License

AGPLv3