https://github.com/Functional-AutoDiff/STALINGRAD
Raw File
Tip revision: 8a782171872d5caf414ef9f8b9b0efebaace3b51 authored by Barak A. Pearlmutter on 22 February 2018, 11:14:43 UTC
terminal newline
Tip revision: 8a78217
README.md
# Stalin∇

Stalin∇ is a brutally optimizing compiler for the VLAD language, a pure dialect of Scheme with first-class automatic differentiation operators.

## Authors

Written by [Jeffrey Mark Siskind](http://www.ece.purdue.edu/~qobi), with [Barak A. Pearlmutter](http://barak.pearlmutter.net) doing a little cheerleading.

## Building

Requires a Scheme compiler and the QobiScheme infrastructure.

## Installing

cp stalingrad /usr/local/bin/

## Usage

Enjoy!

## References

* Barak A. Pearlmutter and Jeffrey Mark Siskind, [*Reverse-Mode AD in a functional framework: Lambda the ultimate backpropagator*](http://barak.pearlmutter.net/papers/toplas-reverse.pdf). TOPLAS *30*_(2)_:1-36, Mar 2008, doi:10.1145/1330017.1330018.

* Jeffrey Mark Siskind and Barak A. Pearlmutter, [*Using Polyvariant Union-Free Flow Analysis to Compile a Higher-Order Functional-Programming Language with a First-Class Derivative Operator to Efficient Fortran-like Code*](http://docs.lib.purdue.edu/ecetr/367), Technical Report, School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, USA, Jan 2008, TR-ECE-08-01.

* Jeffrey Mark Siskind and Barak A. Pearlmutter, [*Efficient Implementation of a Higher-Order Language with Built-In AD*](http://barak.pearlmutter.net/papers/ad2016b.pdf), Extended abstract presented at the 7th International Conference on Algorithmic Differentiation (AD), Oxford, UK, 12-15 September 2016.

* For older materials, see the [old stalin∇ page](http://www.bcl.hamilton.ie/~qobi/stalingrad/)

## Acknowledgements

This material is based upon work supported by the National Science
Foundation under Grant No. 0438806.
Any opinions, findings, and conclusions or recommendations expressed in
this material are those of the author(s) and do not necessarily reflect
the views of the National Science Foundation.
back to top