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This paper introduces Omega, the Ocean Model for E3SM Global Applications. Omega is a new ocean model designed to run efficiently on high performance computing (HPC) platforms, including exascale heterogeneous architect...

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...

Materie / parole chiave: computer theory and algorithm, artificial intelligence and pattern recognition, computer architecture and high performance computing, computer network, software engineering, database and knowledge-based systems; Science:...

The growing demand for intensive artificial intelligence applications, such as deep neural networks and Large Language Models (LLMs), has driven the creation of architecture extensions and accelerators for matrix multipl...

Abstract The current work on emotion recognition considering EEG signals has attracted significant attention due to its advantages in fields like mental health, neural computing, and human-computer interaction. Nonethele...

Abstract In response to the dual challenges of complex static obstacles and frequent dynamic disturbances in the construction site environment, this paper proposes a hybrid path planning strategy that integrates global s...

Abstract Learning to program is not just about writing code. It is a complex process involving trial and error, hesitation, corrections, and sometimes silence. And each student experiences it in their own way. Understand...

This paper addresses the growing need for implementing intelligent Natural Language Processing (NLP) systems on low-power, memory-limited devices such as Raspberry Pi, mobile phones, and IoT edge hardware. As edge comput...

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...

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...

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 ...

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 ...

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...

“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...

The discriminative model learning for image denoising has been recently attracting considerable attentions due to its favorable denoising performance. In this paper, we take one step forward by investigating the construc...