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Modeling and Simulation Challenges and Solutions in Cooling Systems for Nanoscale Integrated Circuits[Feature] 纳米级集成电路冷却系统的建模和仿真挑战与解决方案[Feature]
IF 6.9 2区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2023-01-01 DOI: 10.1109/MCAS.2023.3234727
F. Terraneo, A. Leva, W. Fornaciari, David Atienza Alonso
The power density in modern Integrated Circuits (ICs) is tremendous. For example, Multi-Processor Systems-on-Chip (MPSoCs) nowadays undergo temperature swings of 40 degrees in 100 milliseconds or less, with rapidly emerging and vanishing sub-millimeter hot spots. As such, not only a simulation-based cooling assessment is vital, but one has to simulate the on-chip thermal phenomena jointly with the heat dissipation system - historically, a challenge. In recent years, however, the idea of coupling traditional 3D chip simulators with heat dissipation models written in Equation-Based Modeling (EBM) languages has proven to be a game changer. EBM languages allow one to compose a model by assembling components described in terms of Differential and Algebraic Equations (DAE) and have the simulation code generated automatically. In this article, we take a tutorial viewpoint on the matter just sketched, to put the reader in the position of exploiting the above technology. We also present the first nucleus of a model library for cooling systems, that we release as free software for the scientific and engineering community.
现代集成电路的功率密度是巨大的。例如,现在的多处理器片上系统(mpsoc)在100毫秒或更短的时间内经历40度的温度波动,亚毫米热点迅速出现和消失。因此,不仅基于模拟的冷却评估是至关重要的,而且必须与散热系统一起模拟芯片上的热现象-这在历史上是一个挑战。然而,近年来,将传统的3D芯片模拟器与用基于方程的建模(EBM)语言编写的散热模型相结合的想法已被证明是一个改变游戏规则的想法。EBM语言允许人们通过组装用微分和代数方程(DAE)描述的组件来组成模型,并自动生成仿真代码。在本文中,我们对刚刚概述的问题采取教程的观点,使读者能够利用上述技术。我们还提出了冷却系统模型库的第一个核心,我们将其作为科学和工程社区的免费软件发布。
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引用次数: 0
Women in Circuits and Systems (WiCAS) and Young Professionals (YP) at PRIME-SMACD 2022 [CAS in the World] 电路和系统领域的女性(WiCAS)和年轻专业人士(YP)参加PRIME-SMACD 2022[全球CAS]
IF 6.9 2区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2023-01-01 DOI: 10.1109/mcas.2023.3234731
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引用次数: 0
IEEE App IEEE软件
2区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2023-01-01 DOI: 10.1109/mcas.2023.3313826
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引用次数: 0
IEEE CASS Tour Ecuador 2023 IEEE CASS厄瓜多尔之旅
2区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2023-01-01 DOI: 10.1109/mcas.2023.3302394
Ricardo Reis, Ramiro Taco
The IEEE CASS Tour Ecuador 2023 was organized in February 22 and 23, visiting two cities, Cuenca and Guayaquil, the week before LASCAS 2023 that was held in Quito, Ecuador. The tour included technical talks, as well a special talk about the IEEE CASS and opportunities provided by the society. The main goal of the CASS Tour is to motivate professionals and students in Ecuador to become active members of the society, as well to motivate professionals and students to organize new CASS Chapters and CASS Student Chapters.
IEEE CASS厄瓜多尔之旅于2月22日和23日组织,参观了昆卡和瓜亚基尔两个城市,这是在厄瓜多尔基多举行的LASCAS 2023的前一周。参观活动包括技术讲座、IEEE CASS专题讲座以及学会提供的机会。中国社科院之旅的主要目标是激励厄瓜多尔的专业人士和学生成为社会的积极成员,并激励专业人士和学生组织新的中国社科院分会和中国社科院学生分会。
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引用次数: 0
Heinrich Hertz [Pioneers in CAS] 海因里希·赫兹[CAS的先驱]
IF 6.9 2区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2023-01-01 DOI: 10.1109/mcas.2023.3234728
W. Mathis, Emeritus
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引用次数: 0
IEEE IoT Technical Community and IEEE CASS [CAS in the World] IEEE物联网技术社区与IEEE CASS
2区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2023-01-01 DOI: 10.1109/mcas.2023.3302393
Ricardo Reis
The IEEE IoT Technical Community (TC) is an IEEE’s important, multi-disciplinary, cross-platform initiative. It has a lead society, the ComSoc, four major societies, including IEEE CASS, and seven participating societies. The IEEE World Forum on IoT and the IEEE IoT Magazine are significant activities of the IEEE IoT TC.
IEEE物联网技术社区(TC)是IEEE重要的、多学科、跨平台的倡议。它有一个领导协会,ComSoc,四个主要协会,包括IEEE中国社会科学院,和七个参与协会。IEEE物联网世界论坛和IEEE物联网杂志是IEEE物联网技术委员会的重要活动。
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引用次数: 0
An Interview With Gene Frantz, Innovative Thinker and Father of DSP [Interview] 专访创新思想家、DSP之父Gene Frantz
2区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2023-01-01 DOI: 10.1109/mcas.2023.3302181
Gene Frantz
In May of 2023, Fan Chen, the associate editor of IEEE CAS-M, had a wonderful opportunity to interview Gene Frantz, an innovative thinker and the Father of DSP by many in the industry 1 . During this interview this interview, Gene shared numerous historic stories in DSP, his incredibly inspiring life journey, and offered valuable suggestions for the younger generation. We have compiled this interview into eight thought-provoking questions, hoping that our CAS readers will both enjoy and benefit from it.
2023年5月,IEEE CAS-M副主编樊晨有幸采访到被业界誉为DSP之父的创新思想家Gene Frantz。在这次采访中,Gene分享了许多在DSP的历史故事,以及他令人难以置信的人生历程,并为年轻一代提供了宝贵的建议。我们将这次采访整理成八个发人深省的问题,希望我们的中科院读者能从中受益。
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引用次数: 0
Tiny Machine Learning: Progress and Futures [Feature] 微型机器学习:进步与未来[专题]
2区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2023-01-01 DOI: 10.1109/mcas.2023.3302182
Ji Lin, Ligeng Zhu, Wei-Ming Chen, Wei-Chen Wang, Song Han
Tiny machine learning (TinyML) is a new frontier of machine learning. By squeezing deep learning models into billions of IoT devices and microcontrollers (MCUs), we expand the scope of applications and enable ubiquitous intelligence. However, TinyML is challenging due to the hardware constraints: the tiny memory resource is difficult hold deep learning models designed for cloud and mobile platforms. There is also limited compiler and inference engine support for bare-metal devices. Therefore, we need to co-design the algorithm and system stack to enable TinyML. In this review, we will first discuss the definition, challenges, and applications of TinyML. We then survey the recent progress in TinyML and deep learning on MCUs. Next, we will introduce MCUNet, showing how we can achieve ImageNet-scale AI applications on IoT devices with system-algorithm co-design. We will further extend the solution from inference to training and introduce tiny on-device training techniques. Finally, we present future directions in this area. Today’s “large” model might be tomorrow’s “tiny” model. The scope of TinyML should evolve and adapt over time.
微型机器学习(TinyML)是机器学习的新前沿。通过将深度学习模型压缩到数十亿个物联网设备和微控制器(mcu)中,我们扩展了应用范围并实现了无处不在的智能。然而,由于硬件的限制,TinyML是具有挑战性的:微小的内存资源很难容纳为云和移动平台设计的深度学习模型。对裸机设备的编译器和推理引擎支持也很有限。因此,我们需要共同设计算法和系统堆栈来启用TinyML。在这篇综述中,我们将首先讨论TinyML的定义、挑战和应用。然后,我们调查了TinyML和深度学习在mcu上的最新进展。接下来,我们将介绍MCUNet,展示如何通过系统算法协同设计在物联网设备上实现imagenet规模的AI应用。我们将进一步将解决方案从推理扩展到训练,并引入微小的设备上训练技术。最后,提出了该领域的发展方向。今天的“大”模型可能是明天的“小”模型。TinyML的范围应该随着时间的推移而发展和适应。
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引用次数: 0
An Interview with Professor Sung-Mo Steve Kang [Interview] 专访姜圣模教授
IF 6.9 2区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2023-01-01 DOI: 10.1109/mcas.2023.3272088
S. Kang
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引用次数: 0
IEEE CASS Rio de Janeiro Tour 2022 [Education] IEEE CASS里约热内卢de Janeiro Tour 2022[教育]
IF 6.9 2区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2023-01-01 DOI: 10.1109/mcas.2023.3267939
F. Olivera, R. Reis
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引用次数: 0
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