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...
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...
Heterogeneous network-based distributed and parallel computing is gaining increasing acceptance as an alternative or complementary paradigm to multiprocessor-based parallel processing as well as to conventional supercomputing. While algorithmic and programming aspects of heterogeneous concurrent computing are similar...
Message passing, as implemented in message passing interface (MPI), has become the industry standard for programming on distributed memory parallel architectures, while the threading on shared memory machines is typically implemented in OpenMP. Outstanding performance has been achieved with these methods,...
A Survey of Parallel Programming Models and Tools in the Multi and Many-Core Era The work is completed by considering languages with specific parallel support and the distributed programming paradigm. In all cases, we present characteristics... J Diaz,C Muñoz-Caro,A Niño - 《IEEE ...
dispy works with Python versions 2.7+ and 3.1+ on Linux, Mac OS X and Windows; it may work on other platforms (e.g., FreeBSD and other BSD variants) too. Features dispy is implemented withpycos, an independent framework for asynchronous, concurrent, distributed, network programming with tas...
摘要: A distributed data mining algorithm to improve the detection accuracy when classifying malicious or unauthorized network activity is presented. The algorithm is based on genetic programming (GP) extended with the ensemble paradigm. GP ensemble is particularly ......
However, specially because of the legacy of the sequential programming paradigm, computational workloads are more likely to resemble those of Amdahl’s pessimistic assumptions. In an attempt to make Amdahl’s law relevant to future multi-core chip generations, Hill and Marty presented a corollary ...
I have now circled around to a class of problems that are not motivated by the shift to multicore but rather, like Web servers, have concurrency as core characteristics that must be addressed as part of the overall architecture of the application. Similar concerns apply to distributed application...