Results 81 to 90 of about 1,050,120 (328)
Research on the design and optimization method of CNN accelerator based on HLS tools
Dianzi Jishu Yingyong, 2021 Based on the idea of software and hardware co-design, this article uses HLS tools to design and implement a convolutional neural network accelerator on the PYNQ-Z2 platform, and uses the matrix cutting optimization method for convolution operations to ...
Cheng Jiafeng, Wang Hongliang
doaj +1 more source
Stochastic Rounding: Algorithms and Hardware Accelerator [PDF]
IEEE International Joint Conference on Neural Network, 2020 We present algorithms and a hardware accelerator for performing stochastic rounding (SR). Our main goal is to augment the ARM M4F-based multi-core processor SpiNNaker2 with a more flexible rounding functionality than is available in the ARM processor ...
M. Mikaitis
semanticscholar +1 more source
Binarized Convolutional Neural Networks with Separable Filters for Efficient Hardware Acceleration
, 2017 State-of-the-art convolutional neural networks are enormously costly in both compute and memory, demanding massively parallel GPUs for execution. Such networks strain the computational capabilities and energy available to embedded and mobile processing ...
Gupta, Rajesh K. +6 more
core +1 more source
Innovating Aircraft Repair Processes: The Role of Digitalization in Sustainability
Advanced Engineering Materials, EarlyView.This research explores how digitalization—by storing detailed non‐destructive testing data in structured DICONDE databases and creating a standard data model of the component—innovates aviation maintenance and repair processes. Coupled with a developed state‐based simulation model, it enables data‐driven, sustainable repair strategies that reduce waste,
Johanna Aigner +3 more
wiley +1 more source
Automatika, 2019 Video encoding based on novel HEVC standard is an extremely computationally expensive process and achieving efficient encoding requires intelligent utilization of all available resources, from both software and hardware perspective.
Igor Piljić, Leon Dragić, Mario Kovač
doaj +1 more source
Sensors, 2023 Though custom deep learning (DL) hardware accelerators are attractive for making inferences in edge computing devices, their design and implementation remain a challenge. Open-source frameworks exist for exploring DL hardware accelerators.
Dennis Agyemanh Nana Gookyi +4 more
doaj +1 more source
Advanced Engineering Materials, EarlyView.The low cycle fatigue life of additive manufactured HAYNES® 282® superalloy was investigated for conventional and high‐productivity processing: samples of the former lasted 1400–1700 cycles, while samples of the latter failed at ~ 1200 cycles, at 760 °C and 1% strain.
Abdul Shaafi Shaikh +3 more
wiley +1 more source
A compression strategy to accelerate LSTM meta-learning on FPGA
ICT Express, 2022 Driven by edge computing, how to efficiently deploy the meta-learner LSTM in the resource constrained FPGA terminal equipment has become a big problem.
NianYi Wang +4 more
doaj +1 more source
Hardware Accelerated DNA Sequencing [PDF]
2018 IEEE 61st International Midwest Symposium on Circuits and Systems (MWSCAS), 2018 Basecalling is a core function in DNA sequencing. It is responsible for the conversion of measured date to a text representation of the DNA’s molecular make-up. Recent advances in sequencing machinery have greatly accelerated the rate at which DNA data can be gathered using miniaturized platforms.
ZhongPan Wu +4 more
openaire +1 more source
Advanced Engineering Materials, EarlyView.Herein, environmental scanning electron microscopy (ESEM) is discussed as a powerful extension of conventional SEM for life sciences. By combining high‐resolution imaging with variable pressure and humidity, ESEM allows the analysis of untreated biological materials, supports in situ monitoring of hydration‐driven changes, and advances the functional ...
Jendrian Riedel +6 more
wiley +1 more source