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In this work I present a generalization of Amdahl's law on the limits of a parallel implementation with many processors. In particular I establish some mathematical relations involving the number of processors and the dimension of the…

Distributed, Parallel, and Cluster Computing · Computer Science 2007-05-23 Gianluca Argentini

Dense and sparse tensors allow the representation of most bulk data structures in computational science applications. We show that sparse tensor algebra can also be used to express many of the transformations on these datasets, especially…

Mathematical Software · Computer Science 2015-12-02 Edgar Solomonik , Torsten Hoefler

The ability to leverage large-scale hardware parallelism has been one of the key enablers of the accelerated recent progress in machine learning. Consequently, there has been considerable effort invested into developing efficient parallel…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-01-19 Vitaly Aksenov , Dan Alistarh , Janne H. Korhonen

In this paper, first we give a sequential linear-time algorithm for the longest path problem in meshes. This algorithm can be considered as an improvement of [13]. Then based on this sequential algorithm, we present a constant-time parallel…

Data Structures and Algorithms · Computer Science 2012-01-24 Fatemeh Keshavarz-Kohjerdi , Alireza Bagheri

Parametric linear programming is a central operation for polyhedral computations, as well as in certain control applications.Here we propose a task-based scheme for parallelizing it, with quasi-linear speedup over large problems.This type…

Computational Geometry · Computer Science 2020-10-01 Camille Coti , David Monniaux , Hang Yu

In the past, efforts were taken to improve the performance of a processor via frequency scaling. However, industry has reached the limits of increasing the frequency and therefore concurrent execution of instructions on multiple cores seems…

Hardware Architecture · Computer Science 2013-09-24 Irfan Uddin

Asynchronous iterations are more and more investigated for both scaling and fault-resilience purpose on high performance computing platforms. While so far, they have been exclusively applied within space domain decomposition frameworks,…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-10-22 Frederic Magoules , Guillaume Gbikpi-Benissan

In this paper, we introduce a software-defined framework that enables the parallel utilization of all the programmable processing resources available in heterogeneous system-on-chip (SoC) including FPGA-based hardware accelerators and…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-02-12 Jose Nunez-Yanez , Mohammad Hosseinabady , Moslem Amiri , Andrés Rodríguez , Rafael Asenjo , Angeles Navarro , Rubén Gran-Tejero , Darío Suárez-Gracia

Persistent homology is a crucial invariant that is used in many areas to understand data. The $O(N^4)$ run time is a hindrance to its use on most large datasets. We give a parallelization method to utilize multi-core machines and clusters.…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-03-10 Michael G. Rawson

The development of quantum algorithms and protocols calls for adequate modelling and verification techniques, which requires abstracting and focusing on the basic features of quantum concurrent systems, like CCS and CSP have done for their…

Logic in Computer Science · Computer Science 2024-08-28 Lorenzo Ceragioli , Fabio Gadducci , Giuseppe Lomurno , Gabriele Tedeschi

Multi-core and highly-connected architectures have become ubiquitous, and this has brought renewed interest in language-based approaches to the exploitation of parallelism. Since its inception, logic programming has been recognized as a…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-01-25 Agostino Dovier , Andrea Formisano , Gopal Gupta , Manuel V. Hermenegildo , Enrico Pontelli , Ricardo Rocha

In this paper we examine the key elements determining the best performance of computing by increasing the frequency of a single chip and to get the minimum latency during execution of the programs to achieve best possible output. It is not…

Performance · Computer Science 2014-06-03 Kamran Latif

Generalized sparse matrix-matrix multiplication (or SpGEMM) is a key primitive for many high performance graph algorithms as well as for some linear solvers, such as algebraic multigrid. Here we show that SpGEMM also yields efficient…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-03-19 Aydin Buluc , John Gilbert

We introduce an object-oriented framework for parallel programming, which is based on the observation that programming objects can be naturally interpreted as processes. A parallel program consists of a collection of persistent processes…

Programming Languages · Computer Science 2014-04-21 Edward Givelberg

A novel parallel patterns library, Groovy Parallel Patterns, is presented which, from the outset, has been designed to exploit more general process parallelism than the usual data and task parallel architectures. The library executes on a…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-03-23 Jon Kerridge , Neil Urquhart

For microscale heterogeneous PDEs, this article further develops novel theory and methodology for their macroscale mathematical/asymptotic homogenization. This article specifically encompasses the case of quasi-periodic heterogeneity with…

Analysis of PDEs · Mathematics 2022-09-08 A. J. Roberts

Serial and parallel combinations of diodes are studied by first establishing approached equivalence formulae. Sorting diodes enlights the true dispersion of their characteristics. This simple exercice helps students to realize that…

Physics Education · Physics 2016-08-16 Raymond Laagel , Olivier Haeberlé

Regular expression (RE) matching is a very common functionality that scans a text to find occurrences of patterns specified by an RE; it includes the simpler function of RE recognition. Here we address RE parsing, which subsumes matching by…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-03-11 Angelo Borsotti , Luca Breveglieri , Stefano Crespi Reghizzi , Angelo Morzenti

The growing interest for high dimensional and functional data analysis led in the last decade to an important research developing a consequent amount of techniques. Parallelized algorithms, which consist in distributing and treat the data…

Statistics Theory · Mathematics 2017-10-24 Antoine Godichon-Baggioni , Sofiane Saadane

The development of the Parallel ROOT Facility, PROOF, enables a physicist to analyze and understand much larger data sets on a shorter time scale. It makes use of the inherent parallelism in event data and implements an architecture that…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Maarten Ballintijn , Rene Brun , Fons Rademakers , Gunther Roland
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