|In this talk we present a preliminary investigation on the use of the SPIRAL system
(www.spiral.net) to generate code for modular Fast Fourier Transforms (FFTs). SPIRAL
is a library generation system that automatically generates platform-tuned
implementations of digital signal processing algorithms with an emphasis on fast
transforms. Currently, SPRIAL can generate highly optimized fixed point and
floating-point FFTs for a variety of platforms including vectorization, multi-threaded
and distributed memory parallelization. The code produced is competitive with the best
available code for these platforms and SPIRAL is used by Intel for its IPP (Intel
Performance Primitives) and MKL (Math kernel Library) libraries.
The SPIRAL system uses a mathematical framework for representing and deriving algorithms.
Algorithms are derived using rewrite rules and additional rules are used to symbolically
manipulate algorithms into forms that take advantage of the underlying hardware. A
search engine with a feedback loop is used to tune implementations to particular
platforms. New transforms are added by introducing new symbols and their definition
and new algorithms can be generated by adding new rules.
We extended SPIRAL to generate algorithms for FFT computation over finite fields.
This addition required adding a new data type, several new rules and a new transform
(ModDFT) definition. In addition, the unparser (where code is generated) was extended
so that it can generate code for modular arithmetic. With these enhancements, the
SPRIAL machinery can be applied to modular transforms that are of interest to the
computer algebra community. This provides a framework for systematically optimizing
these transforms, utilizing vector and parallel computation, and for automatically
tuning them to different platforms. In this talk we present preliminary results from