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The impact of vectorization and parallelization of the slope algorithm on performance and energy efficiency on multi-core architecture

Bylina Beata, Potiopa Joanna, Klisowski Michał, Bylina Jarosław

Annals of Computer Science and Information Systems

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2021

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Vol. 25

283--290

EN

Calculation of land-surface parameters (e.g. slope, aspect, curvature) is an important part of many geospatial analyses. Current research trends are aimed at developing new software techniques to achieve the best performance and energy trade-off. In our work, we concentrate on the vectorization and parallelization to improve overall energy efficiency and performance of the neighborhood raster algorithms for the computation of land-surface parameters. We chose the slope calculation algorithm as the basis for our investigation. The parallelization was achieved through redesigning the the original sequential code with OpenMP SIMD vectorization hints for compiler, OpenMP loop parallelization, and the hybrid of these techniques. To evaluate both performance and energy savings, we tested our vector-parallel implementations on a multi-core computer for various data sizes. RAPL interface was used to measure energy consumption. The results showed that optimization towards high performance can also be an effective strategy for improving energy efficiency.

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The parallel tiled WZ factorization algorithm for multicore architectures

Bylina Beata, Bylina Jarosław

International Journal of Applied Mathematics and Computer Science

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2019

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Vol. 29, no. 2

407--419

EN

The aim of this paper is to investigate dense linear algebra algorithms on shared memory multicore architectures. The design and implementation of a parallel tiled WZ factorization algorithm which can fully exploit such architectures are presented. Three parallel implementations of the algorithm are studied. The first one relies only on exploiting multithreaded BLAS (basic linear algebra subprograms) operations. The second implementation, except for BLAS operations, employs the OpenMP standard to use the loop-level parallelism. The third implementation, except for BLAS operations, employs the OpenMP task directive with the depend clause. We report the computational performance and the speedup of the parallel tiled WZ factorization algorithm on shared memory multicore architectures for dense square diagonally dominant matrices. Then we compare our parallel implementations with the respective LU factorization from a vendor implemented LAPACK library. We also analyze the numerical accuracy. Two of our implementations can be achieved with near maximal theoretical speedup implied by Amdahl’s law.

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Effective expectation maximization algorithm implementation using multicore computer systems

Kasitskij A., Bidyuk P., Gozhyi A.

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska

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2014

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nr 4

35--37

EN

A popular expectation maximization algorithm that is widely used in modern data processing systems to solve various problems including optimization and parameter estimation is considered in the paper. The task of the study was to enhance effectiveness of the algorithm execution in time. An enhancement of execution rate for the EM algorithm using multicore architecture of modern computer systems was carried out. Necessary modifications aimed at better parallelism were proposed for implementation of the EM algorithm. An efficiency of the software implementation was tested on the classic problem of Gaussian random variables mixture separation. It is shown that in the mixture separation problem EM algorithm performance degrades when the distance between mean values of distributions is less than three standard deviations, which is totally in the spirit of three sigma law. In such cases, it is very important to have an efficient EM algorithm implementation to be able to process such test cases in a reasonable time.

PL

W artykule opisany jest popularny algorytm EM (expectation maximization), który jest powszechnie stosowany w nowoczesnych systemach przetwarzania danych do rozwiązywania różnych problemów, w tym optymalizacji i estymacji parametrów. Celem badań było zwiększenie efektywności czasu wykonywania algorytmu. Zwiększenie szybkości wykonania algorytmu EM użyto wielordzeniowy architektury nowoczesnych systemów komputerowych. Zostały zaproponowane niezbędne modyfikacje mające na celu lepszą równoległość realizacji algorytmu EM. Skuteczność implementacji programu była testowana na klasycznym problemie separacji Gaussowskich zmiennych losowych. Wykazano, że w przypadku rozdziału mieszaniny wydajność algorytmu EM ulega degradacji, kiedy odległość między średnimi wartościami rozkładu wynosi mniej niż trzy odchylenia standardowe, co jest całkowicie zgodnie z regułą trzech sigm. W takich przypadkach, jest bardzo ważne, aby mieć efektywną realizację algorytmu EM móc przetworzyć takie przypadki w rozsądnym czasie.