Results 41 to 50 of about 2,053,524 (303)

Deep Reinforcement Learning Acceleration for Real-Time Edge Computing Mixed Integer Programming Problems

IEEE Access, 2022
In this work, we present the design and implementation of an ultra-low latency Deep Reinforcement Learning (DRL) FPGA based accelerator for addressing hard real-time Mixed Integer Programming problems.
Gerasimos Gerogiannis, Michael Birbas, Aimilios Leftheriotis, Eleftherios Mylonas, Nikolaos Tzanis, Alexios Birbas   +5 more
doaj   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source

A Scheduling Method of Moldable Parallel Tasks Considering Speedup and System Load on the Cloud

IEEE Access, 2019
The moldable parallel task (MPT) is a kind of parallel task that their sub-tasks hold the resources exclusively, which has been widely used in different areas. Our paper focuses on the scheduling of moldable tasks when every sub-task supports time-slice.
Jianmin Li, Ying Zhong, Xin Zhang
doaj   +1 more source

Monolithic Oxidation Enables Ultrathin Vertically Graded Tantalum Oxide for Low‐Voltage, Low‐Variability Memristive Switching

Advanced Functional Materials, EarlyView.
Monolithic UV‐ozone oxidation of Ta forms an ultrathin Ta2O5/TaOx bilayer enabling resistive switching with a vertical defect gradient. A stoichiometric surface layer over an oxygen‐deficient sublayer promotes localized filament nucleation near the top interface, enabling low‐voltage operation, and reduced cycle‐to‐cycle variability.
Seunghoon Yang, Dong Hyun Lee, Conan Weiland, Won‐Il Lee, Kim Kisslinger, Mingzhao Liu, Aswin kumar Anbalagan, Xiao Tong, Soumyajit Mandal, Nikhil Tiwale, Houk Jang, Chang‐Yong Nam   +11 more
wiley   +1 more source

Task Mapping and Scheduling on RISC-V MIMD Processor With Vector Accelerator Using Model-Based Parallelization

IEEE Access
In this paper, we propose a model-based workflow to generate parallel code on a multiple instruction stream, multiple data stream (MIMD) processor with vector accelerator (MIMDV) from a Simulink model. Solving data- and task-parallelism is crucial during
Shanwen Wu, Satoshi Kumano, Kei Marume, Masato Edahiro   +3 more
doaj   +1 more source

Parallelism Strategies for Big Data Delayed Transfer Entropy Evaluation

Algorithms, 2019
Generated and collected data have been rising with the popularization of technologies such as Internet of Things, social media, and smartphone, leading big data term creation. One class of big data hidden information is causality.
Jonas R. Dourado, Jordão Natal de Oliveira Júnior, Carlos D. Maciel   +2 more
doaj   +1 more source

Basic principles of odontopreparation for non-removable orthopedic structures (literature review)

Вестник медицинского института «Реавиз»: Реабилитация, врач и здоровье, 2021
Introduction. The actual problem of dentists-orthopedists at the present time is a violation of the odontopreparation protocol and, as a result, poor-quality fixation of various non-removable orthopedic structures.
D. I. Dmitriev, A. M. Nesterov, I. O. Buentsov   +2 more
doaj   +1 more source

Task superscalar: an out-of-order task pipeline [PDF]

, 2010
We present Task Superscalar, an abstraction of instruction-level out-of-order pipeline that operates at the tasklevel. Like ILP pipelines, which uncover parallelism in a sequential instruction stream, task superscalar uncovers tasklevel parallelism ...
Badia, Rosa, Ayguadé Parra, Eduard, Rico, Alejandro, Felipe Cabarcas, Mateo Valero, Etsion, Yoav, Yoav Etsion, Ramirez, Alex, Valero, Mateo, Eduard Ayguade, Labarta, Jesús, Rico Carro, Alejandro, Cabarcas, Felipe, Ramírez Bellido, Alejandro, Badia Sala, Rosa Maria, Rosa M. Badia, Alejandro Rico, Ayguadé, Eduard, Jesus Labarta, Valero Cortés, Mateo, Labarta Mancho, Jesús José, Alex Ramirez   +21 more
core   +1 more source

Emerging Post‐CMOS Hardware Neurons for Brain‐Inspired Computing: Devices, Circuits, and System Integration

Advanced Functional Materials, EarlyView.
The physical realization of artificial neurons is a critical challenge for energy‐efficient neuromorphic computing. This review presents a comprehensive analysis of the evolution of artificial neuron implementations from conventional CMOS to emerging post‐CMOS technologies.
Kannan Udaya Mohanan, Hocheon Yoo, Benoît H. Lessard, Ioannis Kymissis, Chang‐Hyun Kim   +4 more
wiley   +1 more source

Executing linear algebra kernels in heterogeneous distributed infrastructures with PyCOMPSs

Oil & Gas Science and Technology, 2018
Python is a popular programming language due to the simplicity of its syntax, while still achieving a good performance even being an interpreted language. The adoption from multiple scientific communities has evolved in the emergence of a large number of
Amela Ramon, Ramon-Cortes Cristian, Ejarque Jorge, Conejero Javier, Badia Rosa M.   +4 more
doaj   +1 more source