Results 51 to 60 of about 79,266 (321)
Doklady Belorusskogo gosudarstvennogo universiteta informatiki i radioèlektroniki, 2019 Parallel algorithm searching the maximum of the objective function using CUDA technology based on the modified method of dynamic programming is presented.
E. N. Seredin
doaj
Analysis and development tools for efficient programs on parallel architectures
Труды Института системного программирования РАН, 2018 The article proposes methods for supporting development of efficient programs for modern parallel architectures, including hybrid systems. Specialized profiling methods designed for programmers tasked with parallelizing existing code are proposed.
Alexander Monakov +3 more
doaj +1 more source
GPU Computing with Python: Performance, Energy Efficiency and Usability
Computation, 2020 In this work, we examine the performance, energy efficiency, and usability when using Python for developing high-performance computing codes running on the graphics processing unit (GPU).
Håvard H. Holm +2 more
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Real-Time Ego-Lane Detection in a Low-Cost Embedded Platform using CUDA-Based Implementation
Semina: Ciências Exatas e Tecnológicas, 2023 This work assesses the effectiveness of heterogeneous computing based on a CUDA implementation for real-time ego-lane detection using a typical low-cost embedded computer. We propose and evaluate a CUDA-optimized algorithm using a heterogeneous approach
Guilherme Brandão da Silva +4 more
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Programming GPUs with CUDA [PDF]
, 2015 El documento contiene el material de un tutorial impartido en el congreso. No es una artículo científico en formato tradicional.Analizamos las prestaciones y características de las distintas generaciones de procesadores gráficos desarrollados por Nvidia ...
Ujaldon-Martinez, Manuel
core
, 2018 AbstractWe add CUDA GPU C program code to RNAfold to enable both it to be run on nVidia gaming graphics hardware and so that many thousands of RNA secondary structures can be computed in parallel. RNAfold predicts the folding pattern for RNA molecules by using O(n3) dynamic programming matrices to minimise the free energy of treating them as a sequence
Langdon, W. B., Lorenz, Ronny
openaire +1 more source
Advanced Science, EarlyView.This study constructed the first D‐amino acid antimicrobial peptide dataset and developed an AI model for efficient screening of substitution sites, with 80% of candidate peptides showing enhanced activity. The lead peptide dR2‐1 demonstrated potent antimicrobial activity in vitro and in vivo, high stability, and low toxicity.
Yinuo Zhao +14 more
wiley +1 more source
Efficient Use of GPU Memory for Large-Scale Deep Learning Model Training
Applied Sciences, 2021 To achieve high accuracy when performing deep learning, it is necessary to use a large-scale training model. However, due to the limitations of GPU memory, it is difficult to train large-scale training models within a single GPU.
Hyeonseong Choi, Jaehwan Lee
doaj +1 more source
High‐Conductivity Electrolytes Screened Using Fragment‐ and Composition‐Aware Deep Learning
Advanced Science, EarlyView.We present a new deep learning framework that hierarchically links molecular and functional unit attributions to predict electrolyte conductivity. By integrating molecular composition, ratios, and physicochemical descriptors, it achieves accurate, interpretable predictions and large‐scale virtual screening, offering chemically meaningful insights for ...
Xiangwen Wang +6 more
wiley +1 more source
Neural network training acceleration using NVIDIA CUDA technology for image recognition
Vestnik Samarskogo Gosudarstvennogo Tehničeskogo Universiteta. Seriâ: Fiziko-Matematičeskie Nauki, 2012 In this paper, an implementation of neural network trained by algorithm based on Levenberg-Marquardt method is presented. Training of neural network increased by almost 9 times using NVIDIA CUDA technology.
Alexander A Fertsev
doaj