Titlebook: High Performance Computing; Third Latin American Carlos Jaime Barrios Hernández,Isidoro Gitler,Jaim Conference proceedings 2017 Springer In

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A Taxonomy of Workflow Scheduling Algorithmscal images. Workflow applications commonly require large computational resources. Hence, distributed computing approaches (such as Grid and Cloud computing) emerge as a feasible solution to execute them. Two important factors for executing workflows in distributed computing platforms are (1) workflo

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An Efficient Implementation of Boolean Gröbner Basis Computationaphy. This technique has been used to solve some cryptosystems for the first time. In this paper, we describe a new concurrent algorithm for boolean Gröbner basis computation that is capable of solving the first HFE challenge. We also discuss implementation details, including optimal runtime paramet

投票

Accelerating Hash-Based Query Processing Operations on FPGAs by a Hash Table Caching Techniqueabase management systems (DBMS). In a query processing system, hash-based computational primitives such as the hash join and the group-by are the most time-consuming operations, as they frequently need to access the hash table on the high-latency off-chip memories and also to traverse whole the tabl

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Distributed Big Data Analysis for Mobility Estimation in Intelligent Transportation Systemsstems. Extracting useful mobility information from large volumes of data is crucial to improve decision-making processes in smart cities. We study the problem of estimating demand and origin-destination matrices based on ticket sales and location of buses in the city. We introduce a framework for mo

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Reducing the Overhead of Message Logging in Fault-Tolerant HPC Applicationsems. Resilience raises as one of the major hurdles in making those systems usable for the advance of science and industry. Message logging is a well-known strategy to provide fault tolerance, one that is promising due to its ability to avoid global restart. However, message-logging protocols may suf

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Dense and Sparse Matrix-Vector Multiplication on Maxwell GPUs with PyCUDAlysis is performed over different memory management schemes. We identify the approaches that result in higher performance in current GPU generations when using dense matrices. The found guidelines are then applied to the implementation of the sparse matrix-vector product, covering structured (DIA) a

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