Memory profiling captures programs' dynamic memory behavior, assisting programmers in
debugging, tuning, and enabling advanced compiler optimizations like speculation-based …

General purpose Gpus provide massive compute power, but are notoriously difficult to
program. In this paper we present a complete compilation strategy to exploit Gpus for the …

Iterators prescribe the traversal of data structures and determine loop termination, and many
loop analyses and transformations require their exact identification. While recognition of …

Speculative multithreading (SpMT) is a thread-level automatic parallelization technique to
accelerate sequential programs. Machine learning has been successfully brought into SpMT …

Data dependence analysis is a must-do operation for parallelisation since it reveals the safe
parallelisable regions of serial codes. Generally, it relies on dynamic analysis, which incurs …

Dynamic analyses rely on the ability to identify points within or across executions. In spite of
this being a core task for dynamic analyses, new solutions are frequently developed without …

Thread-level speculation and profile-guided parallelization techniques exploit the fact that
many statically detected data and control flow dependences do not manifest themselves in …

Among techniques for parallelizing sequential codes, privatization is a common and
significant transformation performed by both compilers and runtime parallelizing systems …

In this paper we present a computational framework that provides the automatic analysis of
spotted DNA microarray image data. The challenges are in providing an accurate …

Automatic parallelization has largely failed to keep its promise of extracting parallelism from
sequential legacy code to maximize performance on multi-core systems outside the …