Temat: OpenCL - Prolib Integro

Skocz do pozycji: 1.

Tytuł:: Heterogeneous GPU&CPU cluster for High Performance Computing in cryptography
Autorzy:: Marks, M.
Jantura, J.
Niewiadomska-Szynkiewicz, E.
Strzelczyk, P.
Góźdź, K.
Tematy:: parallel computing
HPC
clusters
GPU computing
OpenCL
cryptography
cryptanalysis; Pokaż więcej
Wydawca:: Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Powiązania:: https://bibliotekanauki.pl/articles/305288.pdf Link otwiera się w nowym oknie
Opis:: This paper addresses issues associated with distributed computing systems and the application of mixed GPU&CPU technology to data encryption and decryption algorithms. We describe a heterogenous cluster HGCC formed by two types of nodes: Intel processor with NVIDIA graphics processing unit and AMD processor with AMD graphics processing unit (formerly ATI), and a novel software framework that hides the heterogeneity of our cluster and provides tools for solving complex scientific and engineering problems. Finally, we present the results of numerical experiments. The considered case study is concerned with parallel implementations of selected cryptanalysis algorithms. The main goal of the paper is to show the wide applicability of the GPU&CPU technology to large scale computation and data processing.
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 2.

Tytuł:: A Novel GPU-Enabled Simulator for Large Scale Spiking Neural Networks
Autorzy:: Szynkiewicz, P.
Tematy:: GPU computing
OpenCL programming technology
parallel simulation
spiking neural networks; Pokaż więcej
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Powiązania:: https://bibliotekanauki.pl/articles/307680.pdf Link otwiera się w nowym oknie
Opis:: The understanding of the structural and dynamic complexity of neural networks is greatly facilitated by computer simulations. An ongoing challenge for simulating realistic models is, however, computational speed. In this paper a framework for modeling and parallel simulation of biological-inspired large scale spiking neural networks on high-performance graphics processors is described. This tool is implemented in the OpenCL programming technology. It enables simulation study with three models: Integrate-andfire, Hodgkin-Huxley and Izhikevich neuron model. The results of extensive simulations are provided to illustrate the operation and performance of the presented software framework. The particular attention is focused on the computational speed-up factor.
Dostawca treści:: Biblioteka Nauki

Artykuł

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