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The increase of the complexity of scienti c applications that use high performance computing require more e cient Input/Output (I/O) systems. In order to e ciently use the I/O is necessary to know its performance capacit...

The coordinate rotational digital computer (CORDIC) is an arithmetic algorithm, which has been used for arithmetic units in the fast computing of elementary functions and for special purpose hardware in programmable logi...

1957 marked the beginning of modern education in computing in Argentina. I was lucky enough to live this part of the history. After issuing an international bid that year, all members of a special commission from the Uni...

The Web has became an obiquitous resource for distributed computing making it relevant to investigate new ways of providing efficient access to services available at dedicated sites. Efficiency is an ever-increasing dema...

GROMACS is one of the most widely used open-source and free software codes in chemistry, used primarily for dynamical simulations of biomolecules. It provides a rich set of calculation types, preparation and analysis too...

Networking together hundreds or thousands of cheap microsensor nodes allows users to accurately monitor a remote environment by intelligently combining the data from the individual nodes. These networks require robust wi...

In this paper we describe a new mobile architecture, MobileNetV2, that improves the state of the art performance of mobile models on multiple tasks and benchmarks as well as across a spectrum of different model sizes. We...

This paper addresses digital communication in a Rayleigh fading environment when the channel characteristic is unknown at the transmitter but is known (tracked) at the receiver. Inventing a codec architecture that can re...

Evidence for the superiority of guided instruction is explained in the context of our knowledge of human cognitive architecture, expert-novice differences, and cognitive load. Although un-guided or minimally guided instr...

La creciente cantidad de imágenes transmitidas a través de Internet ha llevado al desarrollo de Sistemas de Minería de Imágenes de propósito general. La performance de un SMI depende en gran medida de una rápida y...

Driven by the visions of Internet of Things and 5G communications, recent years have seen a paradigm shift in mobile computing, from the centralized mobile cloud computing toward mobile edge computing (MEC). The main fea...

In the last few years, the deep learning (DL) computing paradigm has been deemed the Gold Standard in the machine learning (ML) community. Moreover, it has gradually become the most widely used computational approach in ...

Abstract A hallmark of the new economy is the ability of organizations to realize economic value from their collection of knowledge assets as well as their assets of information, production distribution, and affiliation....

The purpose of this study is to introduce new design-criteria for next-generation hyperparameter optimization software. The criteria we propose include (1) define-by-run API that allows users to construct the parameter s...

Caffe provides multimedia scientists and practitioners with a clean and modifiable framework for state-of-the-art deep learning algorithms and a collection of reference models. The framework is a BSD-licensed C++ library...

We present an approach to efficiently detect the 2D pose of multiple people in an image. The approach uses a nonparametric representation, which we refer to as Part Affinity Fields (PAFs), to learn to associate body part...

In parallel systems, a number of measures of performance are not accurate or representative of their functioning. These measures allow to quantify the benefit of parallelism. Very often, programs are designed and tested ...

We present a new open source, extensible and flexible software platform for Bayesian evolutionary analysis called BEAST 2. This software platform is a re-design of the popular BEAST 1 platform to correct structural defic...

Big Data applications are typically associated with systems involving large numbers of users, massive complex software systems, and large-scale heterogeneous computing and storage architectures. The construction of such ...

We propose a deep convolutional neural network architecture codenamed Inception that achieves the new state of the art for classification and detection in the ImageNet Large-Scale Visual Recognition Challenge 2014 (ILSVR...

We introduce an extremely computation-efficient CNN architecture named ShuffleNet, which is designed specially for mobile devices with very limited computing power (e.g., 10-150 MFLOPs). The new architecture utilizes two...

“Grid” computing has emerged as an important new field, distinguished from conventional distributed computing by its focus on large-scale resource sharing, innovative applications, and, in some cases, high performanc...

A new software suite, called Crystallography & NMR System (CNS), has been developed for macromolecular structure determination by X-ray crystallography or solution nuclear magnetic resonance (NMR) spectroscopy. In contra...

The self-organized map, an architecture suggested for artificial neural networks, is explained by presenting simulation experiments and practical applications. The self-organizing map has the property of effectively crea...