Practical aspects of high-level parallel programming PAPP 2010

Practical Aspects of High-Level Parallel Programming

SCALABLE COMPUTING Practice and Experience Special Issue: Practical Aspects of High-Level Parallel Programming

The PMLS parallelizing compiler for Standard ML is based upon the automatic instantiation of algorithmic skeletons at sites of higher order function (HOF) use. Rather than mechanically replacing HOFs with skeletons, which in general leads to poor parallel performance, PMLS seeks to predict run-time parallel behaviour to optimise skeleton use. Static extraction of analytic cost models from progr...

CGiS: high-level data-parallel GPU programming

In the last few years, PC technology underwent a paradigm shift. The current trend leads aways from raising sequential performance to enhancing the available parallelism. The rapid performance increase of Graphics Processing Units (GPUs) is a part of this trend. However, it is difficult to harness the computational potential because for the longest time GPUs could be directed only through graph...

High-Level Data Parallel Programming in PROMOTER

Implementing realistic scientific applications on parallel platforms requires a high–level, problem–adequate and flexible programming environment. The hybrid system PROMOTER pursues a two–level approach allowing easy and flexible programming at both language and library levels. The core concept of PROMOTER’s language model is its highly abstract and unified concept of data and communication str...

High-Level vs Low-Level Parallel Programming for Scientific Computing

This talk briefly reviews some of the most popular high-level and low-level parallel programming languages used for scientific computing. We will report our experiences of using these languages in our research and compare the performance of several parallel scientific equation solvers implemented in different parallel languages. Major features and comparisons of these languages will be discusse...