Personal tools
You are here: Home Publications An Adaptive Mesh Refinement Benchmark for Modern Parallel Programming Languages
Document Actions

Tong Wen, Jimmy Su, Phillip Colella, Katherine Yelick, and Noel Keen (2007)

An Adaptive Mesh Refinement Benchmark for Modern Parallel Programming Languages

In: Proceedings of Supercomputing (SC07), Reno, Nevada, ACM.

We present an Adaptive Mesh Refinement benchmark for evaluating programmability and performance of modern parallel programming languages. Benchmarks employed today by language developing teams, originally designed for performance evaluation of computer architectures, do not fully capture the complexity of state-of-the-art computational software systems running on today's parallel machines or to be run on the emerging ones from the multi-cores to the peta-scale High Productivity Computer Systems. This benchmark, extracted from a real application framework, presents challenges for a programming language in both expressiveness and performance. It consists of an infrastructure for finite difference calculations on block-structured adaptive meshes and a solver for elliptic Partial Differential Equations built on this infrastructure. Adaptive Mesh Refinement algorithms are challenging to implement due to the irregularity introduced by local mesh refinement. We describe those challenges posed by this benchmark through two reference implementations (C++/Fortran/MPI and Titanium) and in the context of three programming models.

To appear.
by admin last modified 2007-12-10 16:38
« November 2017 »
Su Mo Tu We Th Fr Sa
1234
567891011
12131415161718
19202122232425
2627282930
 

Powered by Plone

CScADS Collaborators include:

Rice University ANL UCB UTK WISC