000			01913naa a2200241 a 4500
003			AR-LpUFIB
005			20250311170359.0
008			230201s2012 xx o 000 0 eng d
024	8		_aDIF-M6647 _b6785 _zDIF005355
040			_aAR-LpUFIB _bspa _cAR-LpUFIB
100	1		_aTinetti, Fernando Gustavo
245	1	0	_aSequential optimization and shared and distributed memory parallelization in clusters : _bn-body/particle simulation
300			_a1 archivo (532 KB)
500			_aFormato de archivo: PDF. -- Este documento es producción intelectual de la Facultad de Informática - UNLP (Colección BIPA/Biblioteca)
520			_aThe particle-particle method for N-Body problems is one of the most commonly used methods in computer driven physics simulation. These algorithms are, in general, very simple to design and code, and highly parallelizable. In this article, we present the most important approaches for the application of the three performance improvement areas on these algorithms when executed on high performance computing (HPC) clusters: 1) sequential optimization (a single core in a node of the cluster), 2) shared memory parallelism (in a single node with multiple CPUs available, just like a multiprocessor), and 3) distributed memory parallelism (in the whole cluster). For each one of the improvement areas we present the employed techniques and the obtained performance gain. Also, we will show how some (sequential/classical) code optimizations are almost essential for obtaining at least acceptable parallel performance and scalability.
534			_aConference on Parallel and Distributed Computing and Systems (24ta : 2012 nov. 12-14 : Las Vegas). Proceedings . ACTA, 2012.
650		4	_aCOMPUTACIÓN PARALELA
650		4	_aOPTIMIZACIÓN
650		4	_aGENERACIÓN DE CÓDIGO
700	1		_aMartín, Sergio M.
856	4	0	_uhttp://dx.doi.org/10.2316/P.2012.789-056
942			_cCP
999			_c55144 _d55144