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https://software.intel.com/en-us/oneapi/dpc-compiler
An Evolution of C++ for Direct Programming. Data Parallel C++ (DPC++) is an open alternative to single-architecture proprietary languages. It allows developers to reuse code across hardware targets (CPUs and accelerators such as GPUs and FPGAs) and also perform custom tuning for a specific accelerator.
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.15.3975
BibTeX @TECHREPORT{Crummey95compilersupport, author = {John Mellor- Crummey and Vikram Adve and Charles Koelbel and Charles Koelbel and John M. Mellor-crummey}, title = {Compiler Support for Analysis and Tuning Data Parallel Programs}, institution = {In Proceedings of the 1994 Workshop on Parallel Processing Tools and Environments}, year = {1995}}
https://software.intel.com/en-us/fortran-compiler-developer-guide-and-reference-parallel-processing-model
Mar 07, 2019 · A program containing OpenMP* API compiler directives begins execution as a single thread, called the initial thread of execution. The initial thread executes sequentially until the first parallel construct is encountered.
https://insidehpc.com/2006/03/what-is-data-parallel-programming/
Mar 21, 2006 · In the task-parallel model represented by OpenMP, the user specifies the distribution of iterations among processors and then the data travels to the computations. In data-parallel programming, the user specifies the distribution of arrays among processors, and then only those processors owning the data will perform the computation. In OpenMP’s master / slave approach, all …
https://www.researchgate.net/publication/220768928_Data-Parallel_Compiler_Support_for_Multipartitioning
Data-Parallel Compiler Support for Multipartitioning. ... we describe a cost model for selecting d, the dimensionality of the best partitioning, and the number of cuts along each partitioned ...
https://www.sciencedirect.com/science/article/pii/S0927545204800066
To support the systematic development of mixed task and data parallel programs the TwoL model has been introduced. The model provides a stepwise development process which is subdivided into several phases. Applications are hierarchically composed of predefined or user …Cited by: 3
https://en.wikipedia.org/wiki/Data_parallelism
Data parallelism is parallelization across multiple processors in parallel computing environments. It focuses on distributing the data across different nodes, which operate on the data in parallel. It can be applied on regular data structures like arrays and matrices by working on each element in parallel.
https://pdfs.semanticscholar.org/8f4b/782d59fbdedb2108ec331ede2be53917c703.pdf
model, with an emphasis on the integration of this new model into the compiler’s existing OpenMP framework, and explain how the generated multithreaded code works. Given the importance of run-time support of the workqueuing execution model, we also present details of its implementation. Finally,
https://simplecore-ger.intel.com/techdecoded/wp-content/uploads/sites/11/Webinar-Slides-DPC-Part-1-An-Introduction-to-the-New-Programming-Model-.pdf
Introducing Data Parallel C++: A Standards-based, Cross-Architecture ... Inconsistent tool support across platforms Each platform requires unique software ... hierarchical single program multiple data (SPMD) model Execution Model in Kernels dimension 2 of ND-range dimension 1 of ND-range dimension 0
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.42.7170
1 Introduction Data parallel languages such as High-Performance Fortran (HPF) [9, 15] and Fortran D [11] support an abstract model of parallel programming. The principal advantage of these abstract languages is that they insulate programmers from the intricacies of concurrent programming and managing distributed data.
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