Automatic translation of FORTRAN programs to vector form
ACM Transactions on Programming Languages and Systems (TOPLAS)
CODE: A Unified Approach to Parallel Programming
IEEE Software
GASPARD " A Visual Parallel Programming Environment
PARELEC '02 Proceedings of the International Conference on Parallel Computing in Electrical Engineering
Model-Driven Development: A Metamodeling Foundation
IEEE Software
Modeling in Software Engineering
ICSE COMPANION '07 Companion to the proceedings of the 29th International Conference on Software Engineering
CUDA-Lite: Reducing GPU Programming Complexity
Languages and Compilers for Parallel Computing
OpenMP to GPGPU: a compiler framework for automatic translation and optimization
Proceedings of the 14th ACM SIGPLAN symposium on Principles and practice of parallel programming
hiCUDA: a high-level directive-based language for GPU programming
Proceedings of 2nd Workshop on General Purpose Processing on Graphics Processing Units
CuPP - A framework for easy CUDA integration
IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
A model-driven approach to support engineering changes in industrial robotics software
MODELS'12 Proceedings of the 15th international conference on Model Driven Engineering Languages and Systems
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Programming languages that can utilize the underlying parallel architecture in shared memory, distributed memory or Graphics Processing Units (GPUs) are used extensively for solving scientific problems. However, from our observation of studying multiple parallel programs from various domains, such programming languages have a substantial amount of sequential code mixed with the parallel code. When rewriting the parallel code for another platform, the same sequential code is often reused without much modification. Although this is a common occurrence, existing tools and programming environments do not offer much support for this process. In this paper, we introduce a tool named PPmodel, which was designed and implemented to assist programmers in separating the core computation from the details of a specific parallel architecture. Using PPmodel, a programmer can identify and retarget the parallel section of a program to execute in a different platform. With PPmodel, a programmer is better enabled to focus on the parallel section of interest, while ignoring other parallel and sequential sections in a program. The tool is explained by example execution of the parallel section of an OpenMP program for the circuit satisfiability problem in a cluster using the Message Passing Interface (MPI).