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Data parallelism

Known as: Data level parallelism, Data-parallelism, Data-level parallelism 
Data parallelism is a form of parallelization across multiple processors in parallel computing environments. It focuses on distributing the data… 
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Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2017
2017
Hadoop distributed file system (HDFS) and MapReduce model have become popular technologies for large‐scale data organization and… 
2014
2014
The tooling landscape of deep learning is fragmented by a growing gap between the generic and productivity-oriented tools that… 
2011
2011
The development of standard processors changed in the last years moving from bigger, more complex, and faster cores to putting… 
2005
2005
Approaches for dealing with scheduling and load-balancing in PC-based cluster systems are famous and well known. In such… 
2004
2004
A popular approach to providing nonexperts in parallel computing with an easy-to-use programming model is to design a software… 
1995
1995
There has been a great deal of recent interest in parallel I/O. This paper discusses issues in the design and implementation of a… 
1995
1995
There has been an increasing trend towards using a network of non-dedicated workstations for parallel programming. In such an… 
1992
1992
The massively parallel computer Connection Machine is utilized to map an improved version of the direct simulation Monte Carlo… 
Highly Cited
1991
Highly Cited
1991
An algorithm for rendering of orthographic views of volume data on data-parallel computer architectures is described. In… 
1991
1991
C is a data parallel programming language origi nally developed for the Connection Machine E orts are now underway to standardize…