Loop fusion is a key program transformation for data locality optimization that is
implemented in production compilers. But optimizing compilers for imperative languages …

Existing dynamic determinacy race detectors for task-parallel programs are limited to
programs with strict computation graphs, where a task can only wait for its descendant tasks …

While GPUs play an increasingly important role in today's high-performance computers,
optimizing GPU performance continues to impose large burdens upon programmers. A …

This paper describes the design and implementation of a layered domain-specific compiler
to support MADNESS—Multiresolution ADaptive Numerical Environment for Scientific …

We present an approach to optimize the cache locality for recursive programs by
dynamically splicing---recursively interleaving---the execution of distinct function …

Parallel libraries such as OpenMP distribute the iterations of parallel-for-loops among the
threads, using a programmer-specified scheduling policy. While the existing scheduling …

This paper combines complex signal processing with kernel methods for applications in
wind prediction. Specifically, we consider developing least squares kernel algorithms for …

Many algorithms for analyzing parallel programs, for example to detect deadlocks or data
races or to calculate the execution cost, are based on a model variously known as a cost …

Futures are an elegant approach to expressing parallelism in functional programs. However,
combining futures with imperative programming (as in C++ or in Java) can lead to pernicious …

A compiler's intermediate representation (IR) defines a program's execution plan by
encoding its instructions and their relative order. Compiler optimizations aim to replace a …