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A Concurrent Object-Oriented Approach to the Eigenproblem Treatment in Shared Memory Multicore Environments

机译:共享内存多核环境中特征问题处理的并行面向对象方法

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This work presents an object-oriented approach to the concurrent computation of eigenvalues and eigenvectors in real symmetric and Hermitian matrices on present memory shared multicore systems. This can be considered the lower level step in a general framework for dealing with large size eigenproblems, where the matrices are factorized to a small enough size. The results show that the proposed parallelization achieves a good speedup in actual systems with up to four cores. Also, it is observed that the limiting performance factor is the number of threads rather than the size of the matrix. We also find that a reasonable upper limit for a "small" dense matrix to be treated in actual processors is in the interval 10000-30000.
机译:这项工作提出了一种面向对象的方法,用于在当前内存共享多核系统上的实数对称和Hermitian矩阵中并发计算特征值和特征向量。在处理大型特征问题的通用框架中,可以将其视为较低级别的步骤,其中将矩阵分解为足够小的尺寸。结果表明,所提出的并行化在具有多达四个核的实际系统中实现了良好的加速。同样,可以观察到,限制性能因素是线程数而不是矩阵的大小。我们还发现,在实际处理器中要处理的“小”密集矩阵的合理上限在10000-30000之间。

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