Results 101 to 110 of about 20,255 (223)
Coarse-Grained Reconfigurable Arrays (CGRAs) enable ease of programmability and result in low development costs. They enable the ease of use specifically in reconfigurable computing applications.
Fricke, Florian +4 more
core
ABSTRACT Massive Open Online Courses (MOOCs) have established a new paradigm in education, enabling asynchronous, remote learning. Although MOOCs offer diverse educational content to students, comprehensive and realistic education requires hands‐on training.
Manuel J. Gomez +6 more
wiley +1 more source
This paper presents a structural design of the hardware-efficient module for implementation of convolution neural network (CNN) basic operation with reduced implementation complexity.
Cariow, Aleksandr, Cariowa, Galina
core
Scalable Hydrodynamics on multiple Field-Programmable Gate Arrays (FPGAs)
This paper presents scalable 2D and 3D Hydrodynamics solver implementations on FPGAs using Intel’s oneAPI framework, addressing challenges in porting stencil-based computations from CPU/GPU architectures on FPGAs.FPGAs offer customizable hardware with on-chip memory that can be custom-tailored for High Performance Computing (HPC) applications.
Mordant, François-Xavier +3 more
openaire +2 more sources
Dynamic Multifunctional Metasurfaces Based on Passive Cascade Structure
A dynamic multifunctional metasurface is proposed in this paper. Unlike mainstream multifunctional metasurface based on programmable metasurfaces, it consists of two passive metasurfaces, presenting a significant cost advantage. By controlling the displacement, different functions such as beam steering, focusing, and OAM wave generation can be realized
Xiangming Wu +5 more
wiley +1 more source
Optimization and Benchmarking of Lightweight Neural Networks for Efficient Embedded AI Deployment
A hardware‐aware optimization and benchmarking framework for lightweight neural networks is presented for deployment on heterogeneous embedded platforms including CPU, GPU, TPU, and MCU architectures. Model compression techniques such as quantization, pruning, knowledge distillation, and mixed‐precision computation reduce inference latency, memory ...
Vidapankal Mohammad Fridous +4 more
wiley +1 more source
Reprogrammable All‐Photonic Molecular Logic With Ln3+ Luminescent Hybrids in Solid State
Mario P. de‐Saralegui et al. report an Eu3⁺/Tb3⁺‐doped organic–inorganic hybrid material that enables multiple reprogrammable logic operations using only physical stimuli. Additionally, this solid‐state, all‐photonic platform represents the first example in the literature performing reversible Feynman logic operations, marking a major step toward ...
Mario P. de‐Saralegui +4 more
wiley +1 more source
This paper describes a novel way to exploit the computation capabilities delivered by modern Field-Programmable Gate Arrays (FPGAs), not only towards a higher performance, but also towards an improved reliability. Computation-specific pieces of circuitry
Xabier Iturbe +5 more
doaj +1 more source
A Hardware Generator of Multi-point Distributed Random Numbers for Monte Carlo Simulation [PDF]
Monte Carlo simulation of weak approximations of stochastic differential equations constitutes an intensive computational task. In applications such as finance, for instance, to achieve "real time" execution, as often required, one needs highly efficient
Eckhard Platen +3 more
core
A high‐throughput field‐programmable gate array (FPGA)‐accelerated data‐reduction and ‐analysis pipeline combined with high‐performance computing enables the continuous handling of a 216 Gbps data stream from quasi‐elastic gamma‐ray scattering experiments at SPring‐8.We present a data‐acquisition and ‐analysis framework for quasi‐elastic gamma‐ray ...
Haruki Nishino +10 more
wiley +1 more source

