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Accelerating molecular dynamics computing using iteration space slicing

100%

Palkowski M.

Journal of Applied Computer Science

2013

tom Vol. 21, nr 2

85--96

Molecular dynamics is an important computational tool to simulate and understand biochemical processes at the atomic level. Accurate modelling of processes such as simulation of the Newtonian equations of motion requires a large number of computation steps for systems with hundreds to millions of particles. In this paper, we present an approach to accelerate molecular dynamics simulations by means of automatic program loop parallelization. To parallelize code of applications, we have used the Iteration Space Slicing framework. The scope of the applicability of the approach is illustrated using the Gromacs package. Results of a performance analysis for parallelized loops executed on a multi-core computer are presented. The future work is discussed.

Performance assessment of OpenMP constructs and benchmarks using modern compilers and multi-core CPUs

100%

Gawrych B. , Czarnul P.

Annals of Computer Science and Information Systems

2023

tom Vol. 35

973--978

Considering ongoing developments of both modern CPUs, especially in the context of increasing numbers of cores, cache memory and architectures as well as compilers there is a constant need for benchmarking representative and frequently run workloads. The key metric is speed-up as the computational power of modern CPUs stems mainly from using multiple cores. In this paper, we show and discuss results from running codes such as: batch normalization, convolution, linear function, matrix multiplication, prime number test and wave equation; using compilers such as: GNU gcc, LLVM clang, icx, icc; run on four different 1 or 2-socket systems: 1 x Intel Core i7-5960X, 1 x Intel Core i9-9940X, 2 x Intel Xeon Platinum 8280L, 2 x Intel Xeon Gold 6130. Results can be regarded as suggestions concerning scaling on particular CPUs including recommended thread number configurations.

Automatic Extraction of Parallelism for Mobile Devices

100%

Pałkowski M.

Przegląd Elektrotechniczny

2015

tom R. 91, nr 11

162-166

This paper presents the Iteration Space Slicing (ISS) framework aimed at automatic parallelization of code for Mobile Internet Devices (MID). ISS algorithms permit us to extract coarse-grained parallelism available in arbitrarily nested parameterized loops. The loops are parallelized and transformed to multi-threaded application for the Android OS. Experimental results are carried out by means of the benchmark suites (UTDSP and NPB) using an ARM quad core processor. Performance benefits and power consumption are studied. Related and future work are discussed.

Artykuł przedstawia ekstrakcję niezależnych fragmentów kodu dla urządzeń przenośnych. Narzędzie pozwala na zrównoleglenie gruboziarniste dowolnie zagnieżdżonych pe˛ tli programowych z parametrami do kodu wielowątkowego dla systemu Android. Eksperymenty przeprowadzono na zestawach pętli testowych (UTDSP i NPB) za pomocą czterordzeniowego procesora ARM. Przedstawiono analizę wydajności i poboru mocy oraz pokrewne rozwiązania.

The scalability in terms of the time and the energy for several matrix factorizations on a multicore machine

100%

Bylina B. , Piekarz M.

Annals of Computer Science and Information Systems

2023

tom Vol. 35

895--900

Scalability is an important aspect related to time and energy savings on modern multicore architectures. In this paper, we investigate and analyze scalability in terms of time and energy. We compare the execution time and consumption energy of the LU factorization (without pivoting) and Cholesky, both with Math Kernel Library (MKL) on a multicore machine. In order to save the energy of these multithreaded factorizations, the dynamic voltage and frequency scaling (DVFS) technique was used. This technique allows the clock frequency to be scaled without changing the implementation. An experimental scalability evaluation was performed on an Intel Xeon Gold multicore machine, depending on the number of threads and the clock frequency. Our test results show that scalability in terms of the execution time expressed by the Speedup metric has values close to a linear function with an increase in the number of threads. In contrast, scalability in terms of the energy consumed expressed by the Greenup metric has values close to a logarithmic function with an increase in the number of threads. Both kinds of scalability depend on the clock frequency settings and the number of threads.