POLYCHRONOUS WAVEFRONT COMPUTATIONS

Polychronous Wavefront Computations

There is great interest in methods for computing that do not involve digital machines. Many computational paradigms were inspired by brain research, such as Boolean neuronal logic [McCulloch & Pitts, 1943], the perceptron [Rosenblatt, 1958], attractor neural networks [Hopfield, 1982] and cellular neural nets [Chua & Yang, 1988]. All these paradigms abstract biological circuits to artificial neu...

Pipelining Wavefront Computations: Experiences and Performance

Wavefront computations are common in scientific applications. Although it is well understood how wavefronts are pipelined for parallel execution, the question remains: How are they best presented to the compiler for the effective generation of pipelined code? We address this question through a quantitative and qualitative study of three approaches to expressing pipelining: programmer implemente...

Language Support for Pipelining Wavefront Computations

Wavefront computations, characterized by a data dependent flow of computation across a data space, are receiving increasing attention as an important class of parallel computations. Though sophisticated compiler optimizations can often produce efficient pipelined implementations from sequential representations, we argue that a language-based approach to representing wavefront computations is a ...

Adaptation of Spike-Timing-Dependent Plasticity to Unsupervised Learning for Polychronous Wavefront Computing

Array Language Support for Wavefront and Pipelined Computations

Array languages such as Fortran 90, High Performance Fortran and ZPL are convenient vehicles for expressing data parallel computation. Unfortunately, array language semantics prohibit the natural expression of wavefront and pipelined computations, characterized by a sequential propagation of computed values across one or more dimensions of the problem space. As a result, programmers scalarize (...