Zobrazeno 1 - 10
of 1 162
pro vyhledávání: '"Co-optimization"'
Publikováno v:
Opto-Electronic Advances, Vol 7, Iss 4, Pp 1-11 (2024)
Extreme ultraviolet (EUV) lithography with high numerical aperture (NA) is a future technology to manufacture the integrated circuit in sub-nanometer dimension. Meanwhile, source mask co-optimization (SMO) is an extensively used approach for advanced
Externí odkaz:
https://doaj.org/article/2feb540431a94d1194b5de2f44e7a687
Autor:
Leandro M. Giacomini Rocha, Mohamed Naeim, Guilherme Paim, Moritz Brunion, Priya Venugopal, Dragomir Milojevic, James Myers, Mustafa Badaroglu, Marian Verhelst, Julien Ryckaert, Dwaipayan Biswas
Publikováno v:
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits, Vol 10, Pp 125-134 (2024)
High-performance edge artificial intelligence (Edge-AI) inference applications aim for high energy efficiency, memory density, and small form factor, requiring a design-space exploration across the whole stack—workloads, architecture, mapping, and
Externí odkaz:
https://doaj.org/article/226b40e97ae0451ba5bc686ec2cc116c
Autor:
Jose E. Chillogalli, Santiago P. Torres, Ruben A. Romero, Wilson E. Chumbi, Fabian Astudillo-Salinas, Danny Ochoa-Correa
Publikováno v:
IEEE Access, Vol 12, Pp 116428-116441 (2024)
Generation and transmission network expansion planning (GTNEP) co-optimization models have been developed to enable simultaneous decisions considering investment and operational components. Most works solve the GTNEP using linearized models without c
Externí odkaz:
https://doaj.org/article/ffa9263645774e5294bb82466ec5906f
Publikováno v:
IEEE Journal of the Electron Devices Society, Vol 12, Pp 495-501 (2024)
Neural Compact Models (NCMs) have emerged as a crucial tool to meet the stringent demands of Design-Technology Co-Optimization (DTCO) and to overcome the complexities and prolonged development cycles encountered in traditional compact model creation.
Externí odkaz:
https://doaj.org/article/8e362d1f2b75420297ce1ef9640ab19f
Autor:
Shih-Nung Chen, Shi-Hao Chen
Publikováno v:
IEEE Access, Vol 12, Pp 6532-6545 (2024)
This study explores the application of Generative Adversarial Networks (GANs) for generating wafer-level Wafer Acceptance Test (WAT) and Chip Probe (CP) test data in chip manufacturing processes, with a focus on Design-Technology Co-Optimization (DTC
Externí odkaz:
https://doaj.org/article/ab26c186a55e4b3588a1a5193f806f8e
Publikováno v:
Energies, Vol 17, Iss 21, p 5239 (2024)
Supercritical multicomponent thermal fluid injection is a new technology with great potential for offshore heavy oil thermal recovery. In the process of thermal fluid generation, the reaction conditions including temperature, pressure, and the organi
Externí odkaz:
https://doaj.org/article/20c6b3694cd14a8fa0f735d3d76a56ab
Publikováno v:
Chip, Vol 3, Iss 1, Pp 100082- (2024)
Low temperature complementary metal oxide semiconductor (CMOS) or cryogenic CMOS is a promising avenue for the continuation of Moore's law while serving the needs of high performance computing. With temperature as a control “knob” to steepen the
Externí odkaz:
https://doaj.org/article/1dc7919b5ada4629908c4fcdea9bae84
Publikováno v:
Data-Centric Engineering, Vol 5 (2024)
We introduce a novel human-centric deep reinforcement learning recommender system designed to co-optimize energy consumption, thermal comfort, and air quality in commercial buildings. Existing approaches typically optimize these objectives separately
Externí odkaz:
https://doaj.org/article/5e4cc0ae33a44d4dbb8e796f97d7dec1
Autor:
Jongun Won, Jaehyeon Kang, Sangjun Hong, Narae Han, Minseung Kang, Yeaji Park, Youngchae Roh, Hyeong Jun Seo, Changhoon Joe, Ung Cho, Minil Kang, Minseong Um, Kwang‐Hee Lee, Jee‐Eun Yang, Moonil Jung, Hyung‐Min Lee, Saeroonter Oh, Sangwook Kim, Sangbum Kim
Publikováno v:
Advanced Science, Vol 10, Iss 29, Pp n/a-n/a (2023)
Abstract Analog in‐memory computing synaptic devices are widely studied for efficient implementation of deep learning. However, synaptic devices based on resistive memory have difficulties implementing on‐chip training due to the lack of means to
Externí odkaz:
https://doaj.org/article/d1e7683bbe904c06bc1ce70aa284f5a2
Autor:
Markos A. Kousounadis-Knousen, Ioannis K. Bazionis, Dimitrios Soudris, Francky Catthoor, Pavlos S. Georgilakis
Publikováno v:
IEEE Access, Vol 11, Pp 84885-84899 (2023)
Wind power generation is characterized by high intermittency and volatility owing to the stochastic nature of wind. In addition to forecasting accuracy, forecasting uncertainty quantification can have a major impact on power system energy management
Externí odkaz:
https://doaj.org/article/ef025a8142a14b26a103358c29399d64