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Learn the basics of choosing data structures for parallel algorithms, and the pros and cons of common data structures for parallelism.
Learn the basic principles and steps for writing algorithms for parallel processing, a technique that enhances the performance and efficiency of complex algorithms.
STL-provided algorithms and typical user-written algorithms use one or more iterators as arguments and traverse, build, and update containers using these iterators. In providing parallel ...
Pipelined data-parallel algorithms are a class of algorithms which use pipelined operations and data level partitioning to achieve parallelism. Applications which involve data parallelism and ...
A combination of pipelining and data-parallel execution on multiprocessor systems is proposed. The use of pipelining in coarse-grained data-parallel applications can be more advantageous, than the ...
An improvement is also given for the randomized algorithm, and this algorithm is shown to be the fastest of those tested. These comparisons are presented with NESL data-parallel code as executed on a ...
Learn all about array and list data structures in Java, and the algorithms you can use to search and sort the data they contain ...
Parallel Algorithms The Parallel Patterns Library (PPL) provides algorithms that concurrently perform work on collections of data. These algorithms resemble those provided by the C++ Standard Library.
Data Parallel Algorithms STL-provided algorithms and typical user-written algorithms use one or more iterators as arguments and traverse, build, and update containers using these iterators. In ...
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