Version 23 (modified by hartono, 15 years ago) (diff)



An annotation-based performance optimization tool


Orio is an extensible annotation system, implemented in Python, that aims at improving both performance and productivity by enabling software developers to insert annotations into their source code (in C/C++) that trigger a number of low-level performance optimizations on a specified code fragment. The tool generates many tuned versions of the same operation using different optimization parameters, and performs an empirical search for selecting the best among multiple optimized code variants.


Orio 0.0.1 (alpha)

Software Requirements

Python, which is already available in any Linux/Unix? distribution. Orio has successfully been tested with Python 2.5.1 (or any later version).

Quick Installation

The Orio installation follows the standard Python Module Distribution Utilities, or Disutils for short.

For users who want to quickly install Orio to the standard locations of third-party Python modules (requiring superuser privileges in a Unix system), the installation is straightforward as shown below.

% tar -xvzf orio.tar.gz
% cd orio
% python install

On a Unix platform, the above install command will normally put an orcc script in the /usr/bin location, and also create an orio module directory in the /usr/lib/python2.X/site-packages location.

To test whether Orio has been properly installed in your system, try to execute orcc command as given below as an example.

% orcc --help

description: compile shell for Orio

usage: orcc [options] <ifile> 
  <ifile>   input file containing the annotated code

  -h, --help                     display this message
  -o <file>, --output=<file>     place the output to <file>
  -v, --verbose                  verbosely show details of the results of the running program

In order to install Orio to an alternate location, users need to supply a base directory for the installation. For instance, the following command will install an orcc script under /home/username/bin, and also put an orio module under /home/username/lib/python/site-packages.

% tar -xvzf orio.tar.gz
% cd orio
% python install --prefix=/home/username

It is also important to ensure that the installed Orio module location is included in the PYTHONPATH environment variable. Similarly, users can optionally include the installed orcc script location in the PATH shell variable. To do this for the above example, the following two lines can be added in the .bashrc configuration file (assuming the user uses Bash shell, of course).

export PYTHONPATH=$PYTHONPATH:/home/username/lib/python/site-packages
export PATH=$PATH:/home/username/bin


  1. The Orio Framework?
  2. Using the Code Transformation Modules?
  3. Using Empirical Performance Tuner?
  4. Extending Orio?
  5. Performance Study?


  • Boyana Norris, Albert Hartono, and William Gropp. "Annotations for Productivity and Performance Portability," in Petascale Computing: Algorithms and Applications. Computational Science. Chapman & Hall / CRC Press, Taylor and Francis Group, 2007. Preprint ANL/MCS-P1392-0107. (bib, pdf)