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Wyświetlanie 1-15 z 61
Tytuł:
Wykorzystanie CPU i GPU do obliczeń w Matlabie
The use of CPU and GPU for calculations in Matlab
Autorzy:
Woźniak, Jarosław
Powiązania:
https://bibliotekanauki.pl/articles/98264.pdf
Data publikacji:
2019
Wydawca:
Politechnika Lubelska. Instytut Informatyki
Tematy:
CPU
GPU
Matlab
Opis:
W artykule zostały przedstawione wybrane rozwiązania wykorzystujące procesory CPU oraz procesory graficzne GPU do obliczeń w środowisku Matlab. Porównywano różne metody wykonywania obliczeń na CPU, jak i na GPU. Zostały wskazane różnice, wady, zalety oraz skutki stosowania wybranych sposobów obliczeń.
The article presents selected solutions using CPU processors and GPUs for calculations in the Matlab environment. Various methods of performing calculations on the CPU as well as on the GPU were compared. Differences, disadvantages, advantages and effects of using selected calculation methods have been indicated.
Źródło:
Journal of Computer Sciences Institute; 2019, 10; 32-35
2544-0764
Pojawia się w:
Journal of Computer Sciences Institute
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
GPU enhanced simulation of angiogenesis
Autorzy:
Worecki, M.
Wcisło, R.
Powiązania:
https://bibliotekanauki.pl/articles/305573.pdf
Data publikacji:
2012
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
GPU
angiogenesis
tumor
Opis:
In the paper we present the use of graphic processor units to accelerate the most time-consuming stages of a simulation of angiogenesis and tumor growth. By the use of advanced CUDA mechanisms such as shared memory, textures and atomic operations, we managed to speed up the CUDA kernels by a factor of 57x. However, in our simulation we used the GPU as a co-processor and data from CPU was copied back and forth in each phase. It decreased the speedup of rewritten stages by 40%. We showed that the performance of the entire simulation can be improved by a factor of 10 up to 20.
Źródło:
Computer Science; 2012, 13 (1); 35-48
1508-2806
2300-7036
Pojawia się w:
Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Assessment of various GPU acceleration strategies in text categorization processing flow
Autorzy:
Korduła, Ł.
Wielgosz, M.
Karwatowski, M.
Pietroń, M.
Żurek, D.
Wiatr, K.
Powiązania:
https://bibliotekanauki.pl/articles/114132.pdf
Data publikacji:
2017
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
GPU
NLP
text categorization
OpenCL
Opis:
Automatic text categorization presents many difficulties. Modern algorithms are getting better in extracting meaningful information from human language. However, they often significantly increase complexity of computations. This increased demand for computational capabilities can be facilitated by the usage of hardware accelerators like general purpose graphic cards. In this paper we present a full processing flow for document categorization system. Gram-Schmidt process signatures calculation up to 12 fold decrease in computing time of system components.
Źródło:
Measurement Automation Monitoring; 2017, 63, 6; 203-205
2450-2855
Pojawia się w:
Measurement Automation Monitoring
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Real Time Processing of Networked Passive Coherent Location Radar System
Autorzy:
John, M.
Inggs, M.
Petri, D.
Powiązania:
https://bibliotekanauki.pl/articles/226268.pdf
Data publikacji:
2011
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
passive
PCL
real-time
GPU
Opis:
A Passive Coherent Location (PCL) Radar system, consisting of spatially distributed transmitters and receivers is currently being integrated at the University of Cape Town (UCT). The paper investigates the feasibility of real-time processing of PCL system signals using Graphic Processing Units (GPUs), specifically a study of two distinct clutter cancellation algorithms: ECA (Extensive Cancellation Algorithm) and NLMS (Normalised Least Mean Square). Clutter cancellation is the most computationally demanding part of PCL signal processing. This investigation compares the processing speed-up achieved by GPU over CPU implementations, with very encouraging results.
Źródło:
International Journal of Electronics and Telecommunications; 2011, 57, 3; 363-368
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Accelerating SELECT WHERE and SELECT JOIN queries on a GPU
Autorzy:
Pietroń, M.
Russek, P.
Wiatr, K.
Powiązania:
https://bibliotekanauki.pl/articles/305797.pdf
Data publikacji:
2013
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
SQL
CUDA
relational databases
GPU
Opis:
This paper presents implementations of a few selected SQL operations using the CUDA programming framework on the GPU platform. Nowadays, the GPU’s parallel architectures give a high speed-up on certain problems. Therefore, the number of non-graphical problems that can be run and sped-up on the GPU still increases. Especially, there has been a lot of research in data mining on GPUs. In many cases it proves the advantage of offloading processing from the CPU to the GPU. At the beginning of our project we chose the set of SELECT WHERE and SELECT JOIN instructions as the most common operations used in databases. We parallelized these SQL operations using three main mechanisms in CUDA: thread group hierarchy, shared memories, and barrier synchronization. Our results show that the implemented highly parallel SELECT WHERE and SELECT JOIN operations on the GPU platform can be significantly faster than the sequential one in a database system run on the CPU.
Źródło:
Computer Science; 2013, 14 (2); 243-252
1508-2806
2300-7036
Pojawia się w:
Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Modeling and rendering of convective cumulus clouds for real-time graphics purposes
Autorzy:
Kobak, P.
Alda, W.
Powiązania:
https://bibliotekanauki.pl/articles/305238.pdf
Data publikacji:
2017
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
computer graphics
natural phenomena
GPU programming
Opis:
The paper presents a simulation and rendering model of three dimensional covective cloud evolution. The model is physically based, however its purpose is graphical. The main stress is put on balancing two parts of a model: the atmsphere simulation with convective motion of air and water vapor combined with rendering of semi-transparent and light-scattering clouds, in order to achieve realistic animation in real-time. We examine and compare two algorithmic approaches based on CPU and GPU computations.
Źródło:
Computer Science; 2017, 18 (3); 241-268
1508-2806
2300-7036
Pojawia się w:
Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Exploiting multi-core and many-core parallelism for subspace clustering
Autorzy:
Datta, Amitava
Kaur, Amardeep
Lauer, Tobias
Chabbouh, Sami
Powiązania:
https://bibliotekanauki.pl/articles/331126.pdf
Data publikacji:
2019
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
data mining
subspace clustering
multicore processor
many core processor
GPU computing
eksploracja danych
procesor wielordzeniowy
obliczenia GPU
Opis:
Finding clusters in high dimensional data is a challenging research problem. Subspace clustering algorithms aim to find clusters in all possible subspaces of the dataset, where a subspace is a subset of dimensions of the data. But the exponential increase in the number of subspaces with the dimensionality of data renders most of the algorithms inefficient as well as ineffective. Moreover, these algorithms have ingrained data dependency in the clustering process, which means that parallelization becomes difficult and inefficient. SUBSCALE is a recent subspace clustering algorithm which is scalable with the dimensions and contains independent processing steps which can be exploited through parallelism. In this paper, we aim to leverage the computational power of widely available multi-core processors to improve the runtime performance of the SUBSCALE algorithm. The experimental evaluation shows linear speedup. Moreover, we develop an approach using graphics processing units (GPUs) for fine-grained data parallelism to accelerate the computation further. First tests of the GPU implementation show very promising results.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2019, 29, 1; 81-91
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
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
Tytuł:
Analiza efektywności sprzętowych implementacji algorytmów detekcji twarzy w obrazach cyfrowych
Effectiveness analysis of hardware implementations of face detection algorithms in digital images
Autorzy:
Wujek, P.
Pełka, R.
Powiązania:
https://bibliotekanauki.pl/articles/156623.pdf
Data publikacji:
2012
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
detekcja twarzy
FPGA
GPU
GPGPU
face detection
Opis:
W artykule przedstawiono i porównano wyniki implementacji przykładowego algorytmu detekcji twarzy w obrazach cyfrowych na trzech platformach sprzętowych: z użyciem CPU (Matlab), w strukturze programowalnej FPGA z procesorem sprzętowym PowerPC [1], oraz z wykorzystaniem CPU z akceleracją GPU. Powyższe implementacje przebadano eksperymentalnie pod względem złożoności implementacji i szybkości działania poszczególnych fragmentów algorytmu. Porównano je ze sobą oraz przedstawiono najlepsze obszary zastosowań poszczególnych z nich.
This paper describes comparison of hardware implementations of a face detection algorithm using three different platforms: (1) classic CPU implementation (Matlab), (2) implementation with use of programmable logic - FPGA with hardware processor PowerPC [1], and (3) CPU based version with GPU acceleration. These tree versions have been experimentally tested and compared in terms of the required hardware resources and operating speed, which is of great importance in most practical applications. We also discuss advantages and drawbacks of these three approaches to hardware implementation of face detection algorithms. In particular, we formulate some important conditions that the analyzed image must meet to obtain the optimum effectiveness of the face detection algorithm implemented on each platform. Finally, we show that use of GPU acceleration can take advantage of the classic CPU and parallel computing accessible to FPGA. The proposed solution of skin color detection time for the CPU with GPU acceleration is over 100 times shorter than that for the solution with the classical CPU. As a programmable device we have used FPGA Virtex-4 chip from Xilinx, and as a GPU accelerator we have utilized graphic card nVidia GeForce 8600 GT.
Źródło:
Pomiary Automatyka Kontrola; 2012, R. 58, nr 7, 7; 581-583
0032-4140
Pojawia się w:
Pomiary Automatyka Kontrola
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Using shared memory as a cache in cellular automata water flow simulations on GPUs
Autorzy:
Topa, P.
Młocek, P.
Powiązania:
https://bibliotekanauki.pl/articles/305529.pdf
Data publikacji:
2013
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
cellular automata
GPU computation
modelling physical phenomena
Opis:
Graphics processors (GPU – Graphic Processor Units) recently have gained a lot of interest as an efficient platform for general-purpose computation. Cellular Automata approach which is inherently parallel gives the opportunity to implement high performance simulations. This paper presents how shared memory in GPU can be used to improve performance for Cellular Automata models. In our previous works, we proposed algorithms for Cellular Automata model that use only a GPU global memory. Using a profiling tool, we found bottlenecks in our approach. With this paper, we will introduce modifications that takes an advantage of fast shared memory. The modified algorithm is presented in details, and the results of profiling and performance test are demonstrated. Our unique achievement is comparing the efficiency of the same algorithm working with a global and shared memory.
Źródło:
Computer Science; 2013, 14 (3); 385-401
1508-2806
2300-7036
Pojawia się w:
Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
G-DNA – a highly efficient multi-GPU/MPI tool for aligning nucleotide reads
Autorzy:
Frohmberg, W.
Kierzynka, M.
Blazewicz, J.
Gawron, P.
Wojciechowski, P.
Powiązania:
https://bibliotekanauki.pl/articles/200827.pdf
Data publikacji:
2013
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
DNA assembly preprocessing
sequence alignment
GPU computing
Opis:
DNA/RNA sequencing has recently become a primary way researchers generate biological data for further analysis. Assembling algorithms are an integral part of this process. However, some of them require pairwise alignment to be applied to a great deal of reads. Although several efficient alignment tools have been released over the past few years, including those taking advantage of GPUs (Graphics Processing Units), none of them directly targets high-throughput sequencing data. As a result, a need arose to create software that could handle such data as effectively as possible. G-DNA (GPU-based DNA aligner) is the first highly parallel solution that has been optimized to process nucleotide reads (DNA/RNA) from modern sequencing machines. Results show that the software reaches up to 89 GCUPS (Giga Cell Updates Per Second) on a single GPU and as a result it is the fastest tool in its class. Moreover, it scales up well on multiple GPUs systems, including MPI-based computational clusters, where its performance is counted in TCUPS (Tera CUPS).
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2013, 61, 4; 989-992
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Smoothed particle hydrodynamics simulations using graphics processing units
Autorzy:
Szewc, K.
Powiązania:
https://bibliotekanauki.pl/articles/1954445.pdf
Data publikacji:
2014
Wydawca:
Politechnika Gdańska
Tematy:
fluid dynamics
CFD
particle methods
SPH
GPU calculations
Opis:
Smoothed Particle Hydrodynamics (SPH) is a fully Lagrangian, particle-based technique for fluid-flow modeling. As a gridless method, it appears to be a natural approach to simulate multi-phase flow with complex geometries. Since SPH involves a large set of short-range particle-particle interactions, numerical implementations present a high degree of spatial data locality and a significant number of independent computations. Therefore, the numerical code can be easily written in a massively parallel manner. The main purpose of this study is to discuss the issues related to the implementation of the SPH method for computation using Graphics Processing Units (GPU). The study is supported by two-dimensional validation cases: the lid-driven cavity and oscillation of a droplet. The obtained results show a good accuracy of the method, as well as, high numerical efficiency of its GPU implementation.
Źródło:
TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 2014, 18, 1; 67-80
1428-6394
Pojawia się w:
TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
GPU implementation of atomic fluid MD simulation.
Autorzy:
Dawid, Aleksander
Powiązania:
https://bibliotekanauki.pl/articles/2197547.pdf
Data publikacji:
2022
Wydawca:
Politechnika Gdańska
Tematy:
MD simulabon
GPU
atomic fluid
MD parallel algorithm
Opis:
A computer simulation of an atomic fluid on a GPU was implemented using the CUDA architecture. It was shown that the programming model for efficient numerical computing applications was changing with the development of the CUDA architecture. The introduction of the L2 cache decreased the latency between the global GPU memory and the registers. The performed MD simulation using the global memory and registers showed that the average acceleration relative to the CPU reached 80 times for single-precision calculations. Usually, the shared block memory gives much better results for this kind of calculation. We have found that using the shared memory gives acceleration over 116 times in comparison to the CPU. It is about 49% faster than using the global memory and registers. It is shown here that the performance of generally available graphics cards for double-precision calculations is significantly lower than for single-precision calculations. The recorded double-precision acceleration relative to the CPU in our experiment averaged 6 and 7 times for the global and shared memory, respectively. We performed these calculations on two different CUDA enable device systems.
Źródło:
TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk; 2022, 26, 1; 25-37
1428-6394
Pojawia się w:
TASK Quarterly. Scientific Bulletin of Academic Computer Centre in Gdansk
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
G-PAS 2.0 - an improved version of protein alignment tool with an efficient backtracking routine on multiple GPUs
Autorzy:
Frohmberg, W.
Kierzynka, M.
Blazewicz, J.
Wojciechowski, P.
Powiązania:
https://bibliotekanauki.pl/articles/201593.pdf
Data publikacji:
2012
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
pairwise alignment
GPU computing
alignment with backtracking procedure
Opis:
Several highly efficient alignment tools have been released over the past few years, including those taking advantage of GPUs (Graphics Processing Units). G-PAS (GPU-based Pairwise Alignment Software) was one of them, however, with a couple of interesting features that made it unique. Nevertheless, in order to adapt it to a new computational architecture some changes had to be introduced. In this paper we present G-PAS 2.0 - a new version of the software for performing high-throughput alignment. Results show, that the new version is faster nearly by a fourth on the same hardware, reaching over 20 GCUPS (Giga Cell Updates Per Second).
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2012, 60, 3; 491-494
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Digital image correlation - universal tools versus custom solutions
Cyfrowa Korelacja Obrazu - Uniwersalne narzędzia a rozwiązania użytkownika
Autorzy:
Marciniak, T.
Bujnowski, S.
Lutowski, Z.
Boroński, D.
Giesko, T.
Powiązania:
https://bibliotekanauki.pl/articles/257990.pdf
Data publikacji:
2010
Wydawca:
Sieć Badawcza Łukasiewicz - Instytut Technologii Eksploatacji - Państwowy Instytut Badawczy
Tematy:
metody korelacji
DIC
GPU
CUDA
wielowątkowość
correlation methods
multithreading
Opis:
The development of optoelectronics and increasing the processing speed of processors encourage the use of different measurement methods with the use of data obtained from the digital cameras. The article presents the test results of the time consumption of the normalised 2D-correlation function. The correlation is one of most commonly used functions in image processing. It searches for a correlation between the two images and requires quite a lot of calculation operations. The speed of this function was examined in a variety of tools, such as MatLab, MatLab with tools Parallel Computing, library OpenCV and OpenCV wer.2.2 with the CUDA platform extension. During tests, the speeds of image processing were determined, especially for images acquired with high-resolution cameras. Conclusions presented concern with application possibilities of correlation methods, including multithreaded processing.
Rozwój optoelektroniki i rosnąca szybkość przetwarzania procesorów zachęca do stosowania różnorodnych metod pomiarowych wykorzystujących dane pozyskane z kamer cyfrowych. W artykule zaprezentowano wyniki badań szybkości działania funkcji korelacji wykorzystywanych przy obróbce obrazów. Jedną z najczęściej wykorzystywanych funkcji w przetwarzaniu obrazów jest funkcja korelacji. Polega ona na poszukiwaniu współzależności pomiędzy dwoma obrazami i wymaga stosunkowo dużego nakładu obliczeniowego. Szybkość działania funkcji sprawdzono podczas wykorzystania różnych narzędziach takich, jak MatLab, MatLab z biblioteką Parallel Computing, biblioteka OpenCV oraz OpenCV wer.2.2 z możliwością wykorzystania technologii CUDA. W trakcie testów wyznaczono uzyskiwane prędkości przetwarzania obrazów, zwłaszcza w przypadku obrazów rejestrowanych za pomocą kamer wysokiej rozdzielczości. Przedstawiono wnioski dotyczące możliwości zastosowania funkcji korelacji, w tym z wykorzystaniem mechanizmu wielowątkowości.
Źródło:
Problemy Eksploatacji; 2010, 4; 19-28
1232-9312
Pojawia się w:
Problemy Eksploatacji
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-15 z 61

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