Results 111 to 120 of about 1,689,660 (282)

Multi-GPU adaptation of a simulator of heart electric activity

Revista Cubana de Ciencias Informáticas, 2013
The simulation of the electrical activity of the heart is calculated by solving a large system of ordinary differential equations; this takes an enormous amount of computation time.
Víctor M. García, Antonio M. Vidal, Alejandro Liberos, Andreu M. Climent   +3 more
doaj  

Overcoming Artificial Structures in Resolution‐Enhanced Hi‐C Data by Signal Decomposition and Multi‐Scale Attention

Advanced Science, EarlyView.
Deep‐learning‐based signal enhancement is an effective way to recover high‐resolution details from a low‐resolution chromatin contact map. However, due to computational challenges, existing methods commonly divide up the contact map into small patches and create artificial discontinuities at patch boundaries.
Qinyao Li, Kelly Yichen Li, Chiara Nicoletti, Stephen Kwok‐Wing Tsui, Pier Lorenzo Puri, Qin Cao, Kevin Y. Yip   +6 more
wiley   +1 more source

Experiences with porting and modelling wavefront algorithms on many-core architectures [PDF]

, 2010
We are currently investigating the viability of many-core architectures for the acceleration of wavefront applications and this report focuses on graphics processing units (GPUs) in particular.
Pennycook, Simon J., Hammond, Simon D., Mudalige, Gihan R., Jarvis, Stephen A.   +3 more
core   +1 more source

Data‐Driven Modeling of Composition–Processing–Microstructure Relations for Recycled Aluminum Cast Alloys

Advanced Science, EarlyView.
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang, Waleed Mohammed, Dierk Raabe   +2 more
wiley   +1 more source

Neuromorphic Near‐Sensor and In‐Sensor Computing Enabled by Next‐Generation Material‐Based Sensors

Advanced Science, EarlyView.
This Review presents a structural framework that classifies neuromorphic sensing into near‐sensor and in‐sensor architectures, clarifying physical coupling between sensing and computation. The framework connects neural and synaptic device functions with recent advances in optical, mechanical, and chemical sensing, compares energy consumption and ...
Su Yeon Jung, Gwang Ya Kim, Sejin Kim, Hyunjong Seo, Se Gi Lee, Sang Min Won, Dongjoon Rhee, Joohoon Kang   +7 more
wiley   +1 more source

Electromagnetic scattering and imaging simulation of extremely large-scale sea-ship scene based on GPU parallel technology

Journal of Electronic Science and Technology
Aiming to solve the bottleneck problem of electromagnetic scattering simulation in the scenes of extremely large-scale seas and ships, a high-frequency method by using graphics processing unit (GPU) parallel acceleration technique is proposed.
Cheng-Wei Zhang, Zhi-Qin Zhao, Wei Yang, Li-Lai Zhou, Hai-Yu Zhu   +4 more
doaj   +1 more source

CMSA: a heterogeneous CPU/GPU computing system for multiple similar RNA/DNA sequence alignment. [PDF]

BMC Bioinformatics, 2017
Chen X, Wang C, Tang S, Yu C, Zou Q.
europepmc   +1 more source

Photonic‐Enabled Energy‐Efficient Transparent Neuromorphic Computing Devices: A Review

Advanced Science, EarlyView.
Transparent photonic neuromorphic computing devices merge optics and brain‐inspired computing to overcome von Neumann bottlenecks with ultrafast, low‐energy processing. By exploiting transparent oxides, 2D materials, phase‐change materials, and hybrid heterostructures, these platforms enable photonic synapses, memory, and logic for see‐through edge ...
Shuvaraj Ghosh, Ki‐bum Lee, Junghyeon Lee, Seunghee Cho, Malkeshkumar Patel, Hangfei Li, Yu Wen, Ye Zhou, Joondong Kim   +8 more
wiley   +1 more source

Accelerating Probabilistic Forecasting: A GPU-Based Approach to Reducing Computational Time

Forecasting
High-performance computing based on general-purpose graphical processing units (GPUs) is a powerful tool for reducing computational time. In a context where big data is becoming increasingly relevant, GPUs may play a crucial role. This study analyzes the
Juan R. Trapero, Enrique Holgado de Frutos, Francisco Ramos   +2 more
doaj   +1 more source

GPU Computing: An Introduction

, 2019
The graphics processing unit GPU is a computer chip that performs rapid mathematical calculations. GPU is a ubiquitous device which appears in every computing systems such PC, laptop, desktop, and workstation.
Adedamola A. Omotoso, Matthew N. O. Sadiku, Sarhan M. Musa   +2 more
core   +1 more source