Various research communities have independently arrived at stream processing as a
programming model for efficient and parallel computing. These communities include digital …

Virtual machines face significant performance challenges beyond those confronted by
traditional static optimizers. First, portable program representations and dynamic language …

Determining the best set of optimizations to apply to a kernel to be executed on the graphics
processing unit (GPU) is a challenging problem. There are large sets of possible …

We present the design and implementation of an automatic polyhedral source-to-source
transformation framework that can optimize regular programs (sequences of possibly …

Fast changing, increasingly complex, and diverse computing platforms pose central
problems in scientific computing: How to achieve, with reasonable effort, portable optimal …

It is often impossible to obtain a one-size-fits-all solution for high performance algorithms
when considering different choices for data distributions, parallelism, transformations, and …

The polyhedral model provides powerful abstractions to optimize loop nests with regular
accesses. Affine transformations in this model capture a complex sequence of execution …

Iterative compiler optimization has been shown to outperform static approaches. This,
however, is at the cost of large numbers of evaluations of the program. This paper develops …

We present the design and implementation of a fully automatic polyhedral source-to-source
transformation framework that can optimize regular programs (sequences of possibly …

In this paper, we address the question of how to automatically map computational kernels to
highly efficient code for a wide range of computing platforms and establish the correctness of …