Proceedings of the sixth workshop on Declarative aspects of multicore programming - DAMP '11

2011 ◽  
Keyword(s):  
Multicore Programming

scholarly journals High-level multicore programming with C++11

2012 ◽  
Vol 9 (3) ◽  
pp. 1187-1202
Author(s):  
Zalán Szűgyi ◽  
Márk Török ◽  
Norbert Pataki ◽  
Tamás Kozsik
Keyword(s):  
Programming Languages ◽  
Multicore Processors ◽  
Multicore Programming ◽  
C Programming Language ◽  
C Programming ◽  
Template Library ◽  
Standard Template ◽  
High Level ◽  
Standard Template Library ◽  
Standard Library

Nowadays, one of the most important challenges in programming is the efficient usage of multicore processors. All modern programming languages support multicore programming at native or library level. C++11, the next standard of the C++ programming language, also supports multithreading at a low level. In this paper we argue for some extensions of the C++ Standard Template Library based on the features of C++11. These extensions enhance the standard library to be more powerful in the multicore realm. Our approach is based on functors and lambda expressions, which are major extensions in the language. We contribute three case studies: how to efficiently compose functors in pipelines, how to evaluate boolean operators in parallel, and how to efficiently accumulate over associative functors.

scholarly journals Nonblocking Algorithms and Scalable Multicore Programming

Queue ◽  
2013 ◽  
Vol 11 (5) ◽  
pp. 40-64 ◽  
Author(s):  
Samy Al Bahra
Keyword(s):  
Multicore Programming

Low-pain, high-gain multicore programming in Haskell

2009 ◽  
Vol 44 (5) ◽  
pp. 8-9 ◽  
Author(s):  
Abdallah Deeb I. Al Zain ◽  
Kevin Hammond ◽  
Jost Berthold ◽  
Phil Trinder ◽  
Greg Michaelson ◽  
...  
Keyword(s):  
High Gain ◽  
Multicore Programming

DSMC: Fast direct simulation Monte Carlo solver for the Boltzmann equation by Multi-Chain Markov Chain and multicore programming

2016 ◽  
Vol 07 (02) ◽  
pp. 1650009
Author(s):  
Di Zhao ◽  
Haiwu He
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Markov Chain Monte Carlo ◽  
Boltzmann Equation ◽  
Direct Simulation Monte Carlo ◽  
Collision Term ◽  
Direct Simulation ◽  
Multicore Programming ◽  
The Boltzmann Equation ◽  
Simulation Monte Carlo

Direct Simulation Monte Carlo (DSMC) solves the Boltzmann equation with large Knudsen number. The Boltzmann equation generally consists of three terms: the force term, the diffusion term and the collision term. While the first two terms of the Boltzmann equation can be discretized by numerical methods such as the finite volume method, the third term can be approximated by DSMC, and DSMC simulates the physical behaviors of gas molecules. However, because of the low sampling efficiency of Monte Carlo Simulation in DSMC, this part usually occupies large portion of computational costs to solve the Boltzmann equation. In this paper, by Markov Chain Monte Carlo (MCMC) and multicore programming, we develop Direct Simulation Multi-Chain Markov Chain Monte Carlo (DSMC3): a fast solver to calculate the numerical solution for the Boltzmann equation. Computational results show that DSMC3 is significantly faster than the conventional method DSMC.

A Light-weight API for Portable Multicore Programming

2010 ◽  
Author(s):  
Christopher G. Baker ◽  
Michael A. Heroux ◽  
H. Carter Edwards ◽  
Alan B. Williams
Keyword(s):  
Light Weight ◽  
Multicore Programming
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