Results 131 to 140 of about 79,266 (321)

Performance and Cost Evaluation of StarPU on AWS: Case Studies With Dense Linear Algebra Kernels and N‐Body Simulations

open access: yesConcurrency and Computation: Practice and Experience, Volume 38, Issue 3, February 2026.
ABSTRACT Task‐based programming interfaces introduce a paradigm in which computations are decomposed into fine‐grained units of work known as “tasks”. StarPU is a runtime system originally developed to support task‐based parallelism on on‐premise heterogeneous architectures by abstracting low‐level hardware details and efficiently managing resource ...
Vanderlei Munhoz   +5 more
wiley   +1 more source

Extending real‐time MRI of the oral cavity using simultaneous multislice and compressed sensing

open access: yesMagnetic Resonance in Medicine, Volume 95, Issue 2, Page 881-896, February 2026.
Abstract Purpose To demonstrate a real‐time MRI (rtMRI) sequence that can image multiple slices simultaneously and apply them to image the dynamics of the oral cavity. Specifically, we demonstrate the imaging of tongue movement, speech, and swallowing. Methods We developed a radial rtMRI sequence with multiband excitation.
Isaac Watson   +5 more
wiley   +1 more source

ProteinDJ: A high‐performance and modular protein design pipeline

open access: yesProtein Science, Volume 35, Issue 2, February 2026.
Abstract Leveraging artificial intelligence and deep learning to generate proteins de novo (a.k.a. ‘synthetic proteins’) has unlocked new frontiers of protein design. Deep learning models trained on protein structures can generate novel protein designs that explore structural landscapes unseen by evolution.
Dylan Silke   +6 more
wiley   +1 more source

Two-Phase PFAC Algorithm for Multiple Patterns Matching on CUDA GPUs [PDF]

open access: gold, 2019
Wei-Shen Lai   +3 more
openalex   +1 more source

Machine Learning for CUDA+MPI Design Rules.

open access: gold, 2022
Carl M. Pearson   +2 more
openalex   +1 more source

Guiding AlphaFold predictions with experimental knowledge to inform dynamics and interactions with VAIRO

open access: yesProtein Science, Volume 35, Issue 2, February 2026.
Abstract Structural predictions have reached unprecedented accuracy. They leverage sequence‐specific data to capture all potential interactions a sequence has evolved to fulfill. AlphaFold derives information from three sources: learned parameters capturing intrinsic amino acid secondary structure and environment propensity; models of related proteins ...
Josep Triviño   +14 more
wiley   +1 more source

NLML: A Deep Neural Network Emulator for the Exact Nonlinear Interactions in a Wind Wave Model

open access: yesJournal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 1, February 2026.
Abstract Nonlinear wave interactions describe the resonant energy transfer between wave components, playing a fundamental role in the evolution of ocean wave spectra. Nonlinear wave interactions significantly influence wave growth and development, making them essential for accurate wave modeling.
Olawale James Ikuyajolu   +3 more
wiley   +1 more source

Differentiable River Routing for End‐to‐End Learning of Hydrological Processes

open access: yesJournal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 1, February 2026.
Abstract Deep Learning (DL) approaches have shown high accuracy in rainfall runoff modeling. Currently, however, large‐scale DL hydrological simulations at national and global scales still rely on external routing schemes to propagate runoff outputs through river networks, preventing them from leveraging the benefits of end‐to‐end learning of ...
Tristan Hascoet   +3 more
wiley   +1 more source

Optimising Image Feature Extraction and Selection: A Comprehensive Review With Spark Case Studies

open access: yesExpert Systems, Volume 43, Issue 2, February 2026.
ABSTRACT As benchmark image datasets expand in sample size and feature complexity, the challenge of managing increased dimensionality becomes apparent. Contrary to the expectation that more features equate to enhanced information and improved outcomes, the curse of dimensionality often hampers performance.
J. Guzmán Figueira‐Domínguez   +2 more
wiley   +1 more source

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