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

Many advances in automatic parallelization and optimization have been achieved through
the polyhedral model. It has been extensively shown that this computational model provides …

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

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

Performance optimization of stencil computations has been widely studied in the literature,
since they occur in many computationally intensive scientific and engineering applications …

Modern compilers are responsible for translating the idealistic operational semantics of the
source program into a form that makes efficient use of a highly complex heterogeneous …

Automatic parallelization in the polyhedral model is based on affine transformations from an
original computation domain (iteration space) to a target space-time domain, often with a …

We seek to extend the scope and efficiency of iterative compilation techniques by searching
not only for program transformation parameters but for the most appropriate transformations …

High-level loop optimizations are necessary to achieve good performance over a wide
variety of processors. Their performance impact can be significant because they involve in …

Data Access and Storage Management for Embedded Programmable Processors gives an
overview of the state-of-the-art in system-level data access and storage management for …