Allan L. Fisher

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Irregular loop nests in which the loop bounds are determined dynamically by indexed arrays are difficult to compile into expressive parallel constructs, such as segmented scans and reductions. In this paper, we describe a suite of transformations to automatically parallelize such irregular loop nests, even in the presence of recurrences. We describe a(More)
This paper describes a parallel algorithm for a line-finding Hough transform that runs on a linearly connected, SIMD vector of processors. We show that a high-precision transform, usually considered to be an expensive global operation, can be performed efficiently , in two to three times real time, with only local communication on a long vector. The(More)
Data-parallel programming languages have many desirable features , such as single-thread semantics and the ability to express fine-grained parallelism. However, it is challenging to implement such languages efficiently on conventional MIMD multipro-cessors, because these machines incur a high overhead for small grain sizes. This paper presents compile-time(More)
In recent years, many systolic algorithms have been proposed as solutions to computationally demanding problems in signal and image processing and other areas. Such algorithms exploit the regularity and parallelism of problems to achieve high performance and low I/O requirements. Since systolic algorithms generally consist of a few types of simple(More)
We consider a class of practically useful Boolean functions, called Linearly Inductive Functions (LIFs), and present a canonical representation as well as algorithms for their automatic symbolic manipulation. LIFs can be used to capture structural induction in parameterized circuit descriptions, whereby our LIF representation provides a fixed-sized(More)