We study five popular auto‐parallelization frameworks (Cetus, Par4all, Rose, ICC, and
Pluto) and compare them qualitatively as well as quantitatively. All the frameworks primarily …

Parallelization schemes are essential in order to exploit the full benefits of multi-core
architectures, which have become widespread in recent years, especially for scientific …

Automatic parallelization of sequential code has become increasingly relevant in multicore
programming. In particular, loop parallelization continues to be a promising optimization …

This paper provides an examination of OpenMP based auto-parallelizers and their
limitations encountered during parallelization of NAS parallel benchmarks. It also elucidates …

This paper presents results on development of the auto-tuning framework named
TuningGenie aimed at automating adjustment of parallel tasks to target platform. The …

With the collapse of single-processor computing in the high performance computing (HPC)
field, a wave of parallel-computing has emerged. Alongside the paradigm shift of …

High Performance Computing (HPC) technologies are emphasizing to increase the system
performance across many disciplines. The primary challenge in HPC systems is how to …

In this paper, we propose a model-based workflow to generate parallel code on a multiple
instruction stream, multiple data stream (MIMD) processor with vector accelerator (MIMDV) …

Programming for concurrent platforms, such as multicore cpus, is very time consuming and
requires fine tuning of the final program in order to optimize the program parallel layout to …

Developing and optimizing software applications for high performance and energy efficiency
is a very challenging task, even when considering a single target machine. For instance …