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Several different numerical propagation techniques for explicitly time-dependent Hamiltonians are discussed and compared, with the focus on models of pump-probe experiments. The quality of the rotating wave approximation is analyzed analytically, and we point out under which circumstances the modeling becomes inaccurate. For calculations with the fully(More)
MOTIVATION A simultaneous search is necessary for maximizing the power to detect epistatic quantitative trait loci (QTL). The computational complexity demands that the traditional exhaustive search be replaced by a more efficient global optimization algorithm. RESULTS We have the previously known algorithm adapted DIRECT, to the problem of simultaneous(More)
The non-uniform memory access times of modern cc-NUMA systems often impair performance for shared memory applications. This is especially true for applications exhibiting complex access patterns. To improve performance, a mechanism for co-locating threads and data during the execution is needed. In this paper, we study how an <i>affinity-on-next-touch</i>(More)
This work investigates the benefits of transactional memory for high-performance and scientific computing by examining n-body and unstructured mesh applications on a prototype computer system with transactional memory support in hardware. Transactional memory systems have the potential to both improve performance, through reduced lock overhead, and ease(More)
We study the implementation on grid systems of an efficient algorithm for demanding global optimization problems. Specifically, we consider problems arising in the genetic mapping of quantitative trait loci (QTL), i.e. locations in the genome that affect a trait that is measured on a continuous scale. The scheme used in standard serial codes for(More)
Recent technological development in genetics has made large-scale marker genotyping fast and practicable, facilitating studies for detection of QTL in large general pedigrees. We developed a method that speeds up restricted maximum-likelihood (REML) algorithms for QTL analysis by simplifying the inversion of the variance-covariance matrix of the trait(More)
Rapid advances in molecular genetics push the need for efficient data analysis. Advanced algorithms are necessary for extracting all possible information from large experimental data sets. We present a general linear algebra framework for quantitative trait loci (QTL) mapping, using both linear regression and maximum likelihood estimation. The formulation(More)