María Isabel Castillo

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The increase in performance of the last generations of graphics processors (GPUs) has made this class of platform a coprocessing tool with remarkable success in certain types of operations. In this paper we evaluate the performance of the Level 3 operations in CUBLAS, the implementation of BIAS for NVIDIAreg GPUs with unified architecture. From this study,(More)
Solving Dense Linear Systems on GPUs 1 Barrachina et al. The power and versatility of modern GPU have transformed them into the first widely extended HPC platform Solving Dense Linear Systems on GPUs 2 Barrachina et al. The solution of dense linear systems arises in a wide variety of fields How does the new generation of GPUs adapt to this type of problems?(More)
Energy efficiency is a major concern in modern high-performance-computing. Still, few studies provide a deep insight into the power consumption of scientific applications. Especially for algorithms running on hybrid platforms equipped with hardware accelerators, like graphics processors, a detailed energy analysis is essential to identify the most costly(More)
In this paper we introduce a novel parallel pipeline for fast and accurate mapping of RNA sequences on servers equipped with multicore processors. Our software, named HPG-aligner, leverages the speed of the Burrows-Wheeler Transform to map a large number of RNA fragments (reads) rapidly, as well as the accuracy of the Smith-Waterman algorithm, that is(More)
We present several algorithms to compute the solution of a linear system of equations on a GPU, as well as general techniques to improve their performance, such as padding and hybrid GPU-CPU computation. We compare single and double precision performance of a modern GPU with unified architecture, and show how iterative refinement with mixed precision can be(More)
In this paper, we analyze the power consumption of different GPU-accelerated iterative solver implementations enhanced with energy-saving techniques. Specifically, while conducting kernel calls on the graphics accelerator, we manually set the host system to a power-efficient idle-wait status so as to leverage dynamic voltage and frequency control. While the(More)
In this paper, we analyze the interactions occurring in the triangle performance-power-energy for the execution of a pivotal numerical algorithm, the iterative conjugate gradient (CG) method, on a diverse collection of parallel multithreaded architectures. This analysis is especially timely in a decade where the power wall has arisen as a major obstacle to(More)
BACKGROUND Survivors of intensive care units (ICUs) commonly present with symptoms of anxiety, depression and post-traumatic stress disorder (PTSD) during recovery. A number of factors have been identified as predictors of these adverse emotional outcomes, but the role of state anxiety during critical illness in the development of these emotional problems(More)
In this paper we analyze the impact that energy-saving strategies, like the application of DVFS via Linux governors and the MPI communication mode, have on the performance and energy consumption of message-passing dense linear algebra operations. In the study, we employ codes from ScaLAPACK for three matrix kernels, the matrix-matrix and matrix-vector(More)
We present a concurrent algorithm for mapping short and long RNA sequences on multicore processors. Our solution processes the data, initially stored on disk, in batches of reads which are passed between the consecutive stages of a pipeline. A major operational reorganization of the original static pipeline, combined with a complete reimplementation based(More)