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James D. Stevens

Researcher at University of Illinois at Urbana–Champaign

Publications -  4
Citations -  657

James D. Stevens is an academic researcher from University of Illinois at Urbana–Champaign. The author has contributed to research in topics: Load balancing (computing) & Job scheduler. The author has an hindex of 1, co-authored 4 publications receiving 651 citations.

Papers
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Proceedings ArticleDOI

Wire routing by optimizing channel assignment within large apertures

TL;DR: The purpose of this paper is to introduce a new wire routing method for two layer printed circuit boards based on the newly developed channel assignment algorithm and requires many via holes.
Journal ArticleDOI

A mechanism for balancing accuracy and scope in cross-machine black-box GPU performance modeling

TL;DR: This work presents an approach for constructing customizable, cross-machine performance models for GPU kernels, including a mechanism to automatically and symbolically gather performance-relevant kernel operation counts, a tool for formulating mathematical models using these counts, and a customizable parameterized collection of benchmark kernels used to calibrate models to GPUs in a black-box fashion.
Posted Content

A Unified, Hardware-Fitted, Cross-GPU Performance Model

TL;DR: A mechanism to symbolically gather performance-relevant operation counts from numerically-oriented subprograms (`kernels') expressed in the Loopy programming system are presented, and these counts are applied in a simple, linear model of kernel run time.
Journal ArticleDOI

A mechanism for balancing accuracy and scope in cross-machine black-box GPU performance modeling

TL;DR: In this paper, the authors present an approach for constructing customizable, cross-machine performance models for GPU kernels, including a mechanism to automatically and symbolically gather performance-relevant kernel operation counts, a tool for formulating mathematical models using these counts, and a customizable parameterized collection of benchmark kernels used to calibrate models to GPUs.