Program optimization for highly-parallel systems has historically been considered an art,
with experts doing much of the performance tuning by hand. With the introduction of …

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 this paper, we present a GSA-based technique that performs more efficient and more
precise symbolic analysis of predicated assignments, recurrences and index arrays. The …

This paper presents an extensive empirical evaluation of an interprocedural parallelizing
compiler, developed as part of the Stanford SUIF compiler system. The system incorporates …

This paper presents novel compiler optimizations for reducing synchronization overhead in
compiler-parallelized scientific codes. A hybrid programming model is employed to combine …

Most current data dependence tests cannot handle loop bounds or array subscripts that are
symbolic, nonlinear expressions (eg A (n* i+ j), where 0/spl les/j/spl les/n). We describe a …

The promise of automatic parallelization, freeing programmers from the error-prone and time-
consuming process of making efficient use of parallel processing resources, remains …

We study five popular auto‐parallelization frameworks (Cetus, Par4all, Rose, ICC, and
Pluto) and compare them qualitatively as well as quantitatively. All the frameworks primarily …

In this paper, we present an almost-linear time algorithm for constructing Gated Single
Assignment (GSA), which is SSA augmented with gating functions at ø-nodes. The gating …

Many analyses and transformations in a parallelizing compiler can benefit from the ability to
compare arbitrary symbolic expressions. In this paper, we describe how one can compare …