Metadata-Version: 1.1
Name: kerncraft
Version: 0.2.dev1
Summary: Loop Kernel Analysis and Performance Modeling Toolkit
Home-page: https://github.com/cod3monk/kerncraft
Author: Julian Hammer
Author-email: julian.hammer@fau.de
License: AGPLv3
Description: 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 kerncraft``
        
        Additional requirements are:
         * Intel IACA tool, with (working) ``iaca.sh`` in PATH environment variable (used by ECM, ECMCPU and Roofline 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/cod3monk/kerncraft/master/examples/machine-files/phinally.yaml``
        
        ``wget https://raw.githubusercontent.com/cod3monk/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
        
        License
        =======
        AGPLv3
        
Keywords: hpc performance
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development
Classifier: Topic :: Utilities
Classifier: License :: OSI Approved :: GNU Affero General Public License v3
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
