Pydgin: a (Py)thon (D)SL for (G)enerating (In)struction set simulators.

Pydgin provides a collection of classes and functions which act as an embedded architectural description language (embedded-ADL) for concisely describing the behavior of instruction set simulators (ISS). An ISS described in Pydgin can be directly executed in a Python interpreter for rapid prototyping and debugging, or alternatively can be used to automatically generate a performant, JIT-optimizing C executable more suitable for application development.

Automatic generation of JIT-enabled ISS from Pydgin is enabled by the RPython Translation Toolchain, an open-source tool used by developers of the PyPy JIT-optimizing Python interpreter.

An ISS described in Pydgin implements an interpretive simulator which can be directly executed in a Python interpreter for rapid prototyping and debugging. However, Pydgin ISS can also be automatically translated into a C executable implementing a JIT-enabled interpretive simulator, providing a high-performance implementation suitable for application development. Generated Pydgin executables provide significant performance benefits in two ways. First, the compiled C implementation enables much more efficient execution of instruction-by-instruction interpretive simulation than the original Python implementation. Second, the generated executable provides a trace-JIT to dynamically compile frequently interpreted hot loops into optimized assembly.

Pydgin is offered under the terms of the Open Source Initiative BSD 3-Clause License. More information about this license can be found here:

• http://choosealicense.com/licenses/bsd-3-clause
• http://opensource.org/licenses/BSD-3-Clause

If you end up using Pydgin in your research, please let us know! We'd love to hear your feedback. Also, you can cite our paper! :

@inproceedings{lockhart-pydgin-ispass2015,
  title     = {Pydgin: Generating Fast Instruction Set Simulators from
               Simple Architecture Descriptions with Meta-Tracing JIT
               Compilers},
  author    = {Derek Lockhart and Berkin Ilbeyi and Christopher Batten},
  booktitle = {2015 IEEE Int'l Symp. on Performance Analysis of Systems
               and Software (ISPASS)},
  month     = {Mar},
  year      = {2015},
}

The following directories Pydgin libraries and simulator implementations for executing ELF binaries compiled with a cross-compiler.

• pydgin: Library for describing instruction set simulators (ISS).
• arm: Pydgin ISS for executing ARMv5 binaries.
• parc: Pydgin ISS for executing PARC binaries.

Please see the README files in each subdirectory for more information.

Pydgin depends on the libraries provided by the RPython translation toolchain for jit annotations and interpreter translation. Before running a Pydgin simulator, please install the PyPy project source code and specify its location by creating a PYDGIN_PYPY_SRC_DIR environment variable:

$ hg clone https://bitbucket.org/pypy/pypy $SOME_DIR
$ export PYDGIN_PYPY_SRC_DIR=$SOME_DIR/pypy

Pydgin simulator generation also works much faster if you have the PyPy binary installed. You can either compile this yourself from source, or download a precompiled version from the PyPy homepage.

• http://pypy.org/download.html

Note that if you download a tarball of the PyPy source instead of cloning it from BitBucket, it must be version 2.5 or newer.

Now that PyPy dependencies are installed, you can run Pydgin simulators directly with Python for debug purposes:

$ cd arm
$ python arm-sim.py <arm-binary>

Finally, you can translate the Pydgin simulators into JIT-enabled simulator binaries using the RPython translation toolchain:

$ cd scripts
$ ./build.py --help
$ ./build.py pydgin-arm-jit

The translation process will take several minutes. After it's done, you'll have a fast simulator to run your binaries:

$ ./builds/pydgin-arm-jit <arm-binary>