Michael Wolfe

Learn More
Following your need to always fulfil the inspiration to obtain everybody is now simple. Connecting to the internet is one of the short cuts to do. There are so many sources that offer and connect us to other world condition. As one of the products to see in internet, this website becomes a very available place to look for countless high performance(More)
Dependence graphs can be used as a vehicle for formulating and implementing compiler optimizations. This paper defines such graphs and discusses two kinds of transformations. The first are simple rewriting transformations that remove dependence arcs. The second are abstraction transformations that deal more globally with a dependence graph. These(More)
Linear induction variable detection is usually associated with the strength reduction optimization. For restructuring compilers, eeective data dependence analysis requires that the compiler detect and accurately describe linear and nonlinear induction variables as well as more general sequences. In this paper we present a practical technique for detecting a(More)
Subdividing the iteration space of a loop into blocks or <italic>tiles</italic> with a fixed maximum size has several advantages. Tiles become a natural candidate as the unit of work for parallel task scheduling. Synchronization between processors can be done between tiles, reducing synchronization frequency (at some loss of potential parallelism). The(More)
The PGI Accelerator model is a high-level programming model for accelerators, such as GPUs, similar in design and scope to the widely-used OpenMP directives. This paper presents some details of the design of the compiler that implements the model, focusing on the <i>Planner</i>, the element that maps the program parallelism onto the hardware parallelism.
Induction variable detection is usually closely tied to the strength reduction optimization. This paper studies induction variable analysis from a different perspective, that of finding induction variables for data dependence analysis. While classical induction variable analysis techniques have been used successfully up to now, we have found a simple(More)
This paper introduces a data dependence decision algorithm, called the Power Test; the Power Test is a combination of Banerjee's Generalized GCD dependence algorithm and the Fourier-Motzkin method t o eliminate variables in a system of inequalities. In addition t o having certain advantages over previous dependence algorithms (such as increased precision,(More)