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‣ Efficient computation of the matrix square root in heterogeneous platforms

Costa, Pedro Filipe Araújo
Fonte: Universidade do Minho Publicador: Universidade do Minho
Tipo: Dissertação de Mestrado
Publicado em //2013 Português
Relevância na Pesquisa
Dissertação de mestrado em Engenharia Informática; Matrix algorithms often deal with large amounts of data at a time, which impairs efficient cache memory usage. Recent collaborative work between the Numerical Algorithms Group and the University of Minho led to a blocked approach to the matrix square root algorithm with significant efficiency improvements, particularly in a multicore shared memory environment. Distributed memory architectures were left unexplored. In these systems data is distributed across multiple memory spaces, including those associated with specialized accelerator devices, such as GPUs. Systems with these devices are known as heterogeneous platforms. This dissertation focuses on studying the blocked matrix square root algorithm, first in a multicore environment, and then in heterogeneous platforms. Two types of hardware accelerators are explored: Intel Xeon Phi coprocessors and NVIDIA CUDA-enabled GPUs. The initial implementation confirmed the advantages of the blocked method and showed excellent scalability in a multicore environment. The same implementation was also used in the Intel Xeon Phi, but the obtained performance results lagged behind the expected behaviour and the CPU-only alternative. Several optimizations techniques were applied to the common implementation...