Recent workload trends indicate rapid growth in the deployment of machine learning,
genomics and scientific workloads on cloud computing infrastructure. However, efficiently …

Michael Mascagni Monte Carlo methods (MCMs) have been, and continue to be, very
popular algorithms for solving a wide variety of problems in science, engineering, and …

Advances in networking technologies will soon make it possible to use the global
information infrastructure in a qualitatively different way—as a computational as well as an …

High Performance Fortran (HPF) is a high-level data-parallel programming system based on
Fortran. The effort to standardize HPF began in 1991, at the Supercomputing Conference in …

The SUIF Explorer is an interactive parallelization tool that is more effective than previous
systems in minimizing the number of lines of code that require programmer assistance. First …

In the future, many computers will contain multiple processors, in part because the marginal
cost of adding a few additional processors is so low that only minimal performance gain is …

We describe the Java runtime parallelizing machine (Jrpm), a complete system for
parallelizing sequential programs automatically. Jrpm is based on a chip multiprocessor …

This paper studies techniques to improue the performance of memory consistency models
for shared-memory multi-processors with ILP processors. The first part of this paper extends …

It is increasingly difficult for complex scientific programs to attain a significant fraction of peak
performance on systems that are based on microprocessors with substantial instruction-level …

In this paper, we provide examples of how thread-level speculation (TLS) simplifies manual
parallelization and enhances its performance. A number of techniques for manual …