Temat: parallel machine - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: The Java profiler based on byte code analysis and instrumentation for many-core hardware accelerators
Autorzy:: Pietroń, M.
Karwatowski, M.
Wiatr, K.
Powiązania:: https://bibliotekanauki.pl/articles/114614.pdf
Data publikacji:: 2015
Wydawca:: Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:: virtual machine
CUDA
GPU
profiling
parallel computing
Opis:: One of the most challenging issues in the case of many and multi-core architectures is how to exploit their potential computing power in legacy systems without a deep knowledge of their architecture. The analysis of static dependence and dynamic data dependences of a program run, can help to identify independent paths that could have been computed by individual parallel threads. The statistics of reusing the data and its size is also crucial in adapting the application in GPU many-core hardware architecture because of specific memory hierarchies. The proposed profiling system accomplishes static data analysis and computes dynamic dependencies for Java programs as well as recommends parts of source code with the highest potential for parallelization in GPU. Such an analysis can also provide starting point for automatic parallelization.
Źródło:: Measurement Automation Monitoring; 2015, 61, 7; 385-387
2450-2855
Pojawia się w:: Measurement Automation Monitoring
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 2.

Tytuł:: Optimization of Machine Learning Process Using Parallel Computing
Autorzy:: Grzeszczyk, Michał K.
Powiązania:: https://bibliotekanauki.pl/articles/102525.pdf
Data publikacji:: 2018
Wydawca:: Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:: parallel computing
machine learning
perceptron
neural networks
OpenMP
Opis:: The aim of this paper is to discuss the use of parallel computing in the supervised machine learning processes in order to reduce the computation time. This way of computing has gained popularity because sequential computing is often insufficient for large scale problems like complex simulations or real time tasks. After presenting the foundations of machine learning and neural network algorithms as well as three types of parallel models, the author briefly characterized the development of the experiments carried out and the results obtained. The experiments on image recognition, ran on five sets of empirical data, prove a significant reduction in calculation time compared to classical algorithms. At the end, possible directions of further research concerning parallel optimization of calculation time in the supervised perceptron learning processes were shortly outlined.
Źródło:: Advances in Science and Technology. Research Journal; 2018, 12, 4; 81-87
2299-8624
Pojawia się w:: Advances in Science and Technology. Research Journal
Dostawca treści:: Biblioteka Nauki

Artykuł

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