A self-adapting distributed memory package for fast signal transforms

Summary form only given. We present a self-adapting distributed memory package for computing the Walsh-Hadamard transform (WHT), a prototypical fast signal transform, similar to the fast Fourier transform. A family of distributed memory algorithms are derived from different factorizations of the WHT matrix. Different factorizations correspond to different data distributions and communication patterns. Thus, searching over the space of factorizations leads to the best data distribution and communication pattern for a given platform. The distributed memory WHT package provides a framework for converting factorizations of the WHT matrix into MPl programs and exploring their performance by searching the space of factorizations.