Results 71 to 80 of about 46,646 (266)

A High-Level Synthesis Library for Synthesizing Efficient and Functional-Safe CNN Dataflow Accelerators

IEEE Access
Convolution neural networks (CNNs) are widely applied in many machine learning applications. Hardware acceleration for CNNs is crucial, given their high computational intensity and the demand for enhanced energy efficiency and reduced latency in ...
Dionysios Filippas, Christodoulos Peltekis, Vasileios Titopoulos, Ioannis Kansizoglou, Georgios CH. Sirakoulis, Antonios Gasteratos, Giorgos Dimitrakopoulos   +6 more
doaj   +1 more source

RNS-Based FPGA Accelerators for High-Quality 3D Medical Image Wavelet Processing Using Scaled Filter Coefficients

IEEE Access, 2022
Medical imaging using different modalities has many problems. The main ones are low informativeness, various distortion noises, and a large amount of information. Fusion, denoising, and visual data compression are used to solve them in practice. Discrete
Nikolay N. Nagornov, Pavel A. Lyakhov, Maria V. Valueva, Maxim V. Bergerman   +3 more
doaj   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Hardware Accelerated Graph Analytics

, 2022
Hardware Accelerated Graph ...
Deepak, Kumar, Shaler, Michael
openaire   +1 more source

Analytical Cost Metrics : Days of Future Past

, 2018
As we move towards the exascale era, the new architectures must be capable of running the massive computational problems efficiently. Scientists and researchers are continuously investing in tuning the performance of extreme-scale computational problems.
Djidjev, Hristo, Prajapati, Nirmal, Rajopadhye, Sanjay   +2 more
core   +1 more source

Multiscale Structuring of Hydroxyapatite via Two‐Photon Lithography of Nanocomposites

Advanced Functional Materials, EarlyView.
Hydroxyapatite scaffolds are of great interest in bone tissue engineering applications, ranging from 3D cell culture to regenerative medicine. Using two‐photon lithography of a transparent nanocomposite, hydroxyapatite microstructures with features ranging from submicron to centimeter‐scale are fabricated. This allows to mimic the natural bone geometry,
Leonhard Hambitzer, Jan Mathis Hornbostel, Richard Prediger, Sebastian Kluck, Michael Daub, Cornelia Lee‐Thedieck, Frederik Kotz‐Helmer   +6 more
wiley   +1 more source

Glider: A GPU Library Driver for Improved System Security [PDF]

, 2014
Legacy device drivers implement both device resource management and isolation. This results in a large code base with a wide high-level interface making the driver vulnerable to security attacks.
Sani, Ardalan Amiri, Wallach, Dan S., Zhong, Lin   +2 more
core  

Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics

Advanced Functional Materials, EarlyView.
Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha, Yingshan Ma, Yong Nam An, Sung‐Un An, Hyeon Hak Jung, Suvi‐Tuuli Varjamo, Jiwon Yoo, Junho Min, Hanvit Kim, Faisal Ahmed, Sang Hoon Chae, Young Min Song, Weiwei Cai, Tawfique Hasan, Zhipei Sun, Dong‐Ho Kang, Hyeon‐Jin Shin, Yunyun Dai, Hoon Hahn Yoon   +18 more
wiley   +1 more source

APNAS: Accuracy-and-Performance-Aware Neural Architecture Search for Neural Hardware Accelerators

IEEE Access, 2020
Designing resource-efficient deep neural networks (DNNs) is a challenging task due to the enormous diversity of applications as well as their time-consuming design, training, optimization, and evaluation cycles, especially the resource-constrained ...
Paniti Achararit, Muhammad Abdullah Hanif, Rachmad Vidya Wicaksana Putra, Muhammad Shafique, Yuko Hara-Azumi   +4 more
doaj   +1 more source

An Energy-Efficient Reconfigurable DTLS Cryptographic Engine for End-to-End Security in IoT Applications

, 2019
This paper presents a reconfigurable cryptographic engine that implements the DTLS protocol to enable end-to-end security for IoT. This implementation of the DTLS engine demonstrates 10x reduction in code size and 438x improvement in energy-efficiency ...
Arvind, Banerjee, Utsav, Chandrakasan, Anantha P., Juvekar, Chiraag, Wright, Andrew   +4 more
core   +1 more source