We used a parallel and distributed computing architecture based on Python Remote Objects and Python Optimization Modelling Objects (PyRO-PyOMO), for UPL determination problem. The results show that exploiting parallelism help in achieving 70 % speedup in computation time on various mining datasets. We...
Big Data is the next frontier for innovation, competition, and productivity, and many solutions continue to appear, partly supported by the considerable enthusiasm around the MapReduce paradigm for large-scale data analysis. We review various parallel and distributed programming paradigms, analyzing how...
Similar concerns apply to distributed applications outside of the robotics domain, but these are beyond the scope of this discussion.Streaming ParallelismBeyond multiple cores, a second important feature of computer architecture is the multiple layers of memory hierarchy: registers, one or more levels ...
Similar concerns apply to distributed applications outside of the robotics domain, but these are beyond the scope of this discussion.Streaming ParallelismBeyond multiple cores, a second important feature of computer architecture is the multiple layers of memory hierarchy: registers, o...
1 BACKGROUND The increasing intensity and variety of computation in solving modern science, engineering, and social application problems have brought numerous challenges to parallel and distributed computing and enriched its research content in multiple folds from architecture design to computation paradigm ...
Examples include use of Microsoft Visual Studio and the .NET extension for parallel computing, Microsoft Windows HPC Server, decentralized distributed service-oriented programming, grid computing, and so on. Many of these are rich in ideas that are based on decades of research; side-effect–free ...
A new paradigm, called "parallel module" ( parmod), is defined which, in addition to expressing the semantics of several skeletons as particular cases, is able to express more general parallel and distributed program structures, including both data-flow and nondeterministic reactive computations. ...
Distributed computing is a special version of parallel computing where the processors are in different computers and tasks are distributed to computers over a network. It’d be like Lady Gaga asking Beyoncé, “Please text this guy while I drink.” Although you can do distributed programming in ...
R Raman, R Raman - Parallel and Distributed Processing, 1998 - link.springer.com We now describe a simple but clever idea due to Karger et al. [14] which allows us to use thepruning paradigm to suggest an avenue for practical ... R Raman 被引量: 12发表: 1998年 IMAGE PROCESSING APPAR...
Discover SIMD (Intel intrinsics) and MIMD architectures and parallel programming models: Shared Memory, distributed memory, PGAS, DSM, OpenMP, MPI, DGAS,CUDA..