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Efficient memory allocation is crucial for data-intensive applications, as a smaller memory footprint ensures better cache performance and allows one to run a larger problem size given a fixed amount of main memory. In this article, we describe a new ...

The polyhedral model provides an expressive intermediate representation that is convenient for the analysis and subsequent transformation of affine loop nests. Several heuristics exist for achieving complex program transformations in this model. ...

Over the last two decades, processor speeds have improved much faster than memory speeds. As a result, memory access delay is a major performance bottleneck in today's systems. Compilers often fail to choreograph data and computation automatically to ...

Array contraction is an optimization that transforms array variables into scalar variables within a loop. While the opposite transformation, scalar expansion, is used for enabling parallelism (with a penalty in memory size), array contraction is used to ...

Array contraction is a program transformation which reduces array size while preserving the correct output. In this paper, we present an aggressive array-contraction technique and study its impact on memory system performance. This technique, called ...

Storage mapping optimization is a flexible approach to folding array dimensions in numerical codes. It is designed to reduce the memory footprint after a wide spectrum of loop transformations, whether based on uniform dependence vectors or more ...

In this paper, we propose memory reduction as a new approach to data locality enhancement. Under this approach, we use the compiler to reduce the size of the data repeatedly referenced in a collection of nested loops. Between their reuses, the data will ...