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321 results on '"Zhang, Youhui"'

1. Non B Cell-Derived Immunoglobulin, A Brighter Horizon for the Future

Author

Chu, Ming, Fu, Ning, Zhang, Liang, Yu, Meng, Zhang, Youhui, Qiu, Xiaoyan, Crusio, Wim E., Series Editor, Dong, Haidong, Series Editor, Radeke, Heinfried H., Series Editor, Rezaei, Nima, Series Editor, Steinlein, Ortrud, Series Editor, Xiao, Junjie, Series Editor, Qiu, Xiaoyan, editor, Huang, Jing, editor, and Xu, Xiaojun, editor

Published
2024
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2. AIPerf: Automated machine learning as an AI-HPC benchmark

Author

Ren, Zhixiang, Liu, Yongheng, Shi, Tianhui, Xie, Lei, Zhou, Yue, Zhai, Jidong, Zhang, Youhui, Zhang, Yunquan, and Chen, Wenguang

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Machine Learning
Abstract

The plethora of complex artificial intelligence (AI) algorithms and available high performance computing (HPC) power stimulates the expeditious development of AI components with heterogeneous designs. Consequently, the need for cross-stack performance benchmarking of AI-HPC systems emerges rapidly. The de facto HPC benchmark LINPACK can not reflect AI computing power and I/O performance without representative workload. The current popular AI benchmarks like MLPerf have fixed problem size therefore limited scalability. To address these issues, we propose an end-to-end benchmark suite utilizing automated machine learning (AutoML), which not only represents real AI scenarios, but also is auto-adaptively scalable to various scales of machines. We implement the algorithms in a highly parallel and flexible way to ensure the efficiency and optimization potential on diverse systems with customizable configurations. We utilize operations per second (OPS), which is measured in an analytical and systematic approach, as the major metric to quantify the AI performance. We perform evaluations on various systems to ensure the benchmark's stability and scalability, from 4 nodes with 32 NVIDIA Tesla T4 (56.1 Tera-OPS measured), up to 512 nodes with 4096 Huawei Ascend 910 (194.53 Peta-OPS measured), and the results show near-linear weak scalability. With flexible workload and single metric, our benchmark can scale and rank AI-HPC easily.

Published
2020

3. Brain-inspired global-local learning incorporated with neuromorphic computing

Author

Wu, Yujie, Zhao, Rong, Zhu, Jun, Chen, Feng, Xu, Mingkun, Li, Guoqi, Song, Sen, Deng, Lei, Wang, Guanrui, Zheng, Hao, Pei, Jing, Zhang, Youhui, Zhao, Mingguo, and Shi, Luping

Subjects
Computer Science - Neural and Evolutionary Computing, Computer Science - Artificial Intelligence, Quantitative Biology - Neurons and Cognition
Abstract

Two main routes of learning methods exist at present including error-driven global learning and neuroscience-oriented local learning. Integrating them into one network may provide complementary learning capabilities for versatile learning scenarios. At the same time, neuromorphic computing holds great promise, but still needs plenty of useful algorithms and algorithm-hardware co-designs for exploiting the advantages. Here, we report a neuromorphic hybrid learning model by introducing a brain-inspired meta-learning paradigm and a differentiable spiking model incorporating neuronal dynamics and synaptic plasticity. It can meta-learn local plasticity and receive top-down supervision information for multiscale synergic learning. We demonstrate the advantages of this model in multiple different tasks, including few-shot learning, continual learning, and fault-tolerance learning in neuromorphic vision sensors. It achieves significantly higher performance than single-learning methods, and shows promise in empowering neuromorphic applications revolution. We further implemented the hybrid model in the Tianjic neuromorphic platform by exploiting algorithm-hardware co-designs and proved that the model can fully utilize neuromorphic many-core architecture to develop hybrid computation paradigm., Comment: 5 figures, 6 tables

Published
2020

4. FPSA: A Full System Stack Solution for Reconfigurable ReRAM-based NN Accelerator Architecture

Author

Ji, Yu, Zhang, Youyang, Xie, Xinfeng, Li, Shuangchen, Wang, Peiqi, Hu, Xing, Zhang, Youhui, and Xie, Yuan

Subjects
Computer Science - Emerging Technologies, Computer Science - Neural and Evolutionary Computing
Abstract

Neural Network (NN) accelerators with emerging ReRAM (resistive random access memory) technologies have been investigated as one of the promising solutions to address the \textit{memory wall} challenge, due to the unique capability of \textit{processing-in-memory} within ReRAM-crossbar-based processing elements (PEs). However, the high efficiency and high density advantages of ReRAM have not been fully utilized due to the huge communication demands among PEs and the overhead of peripheral circuits. In this paper, we propose a full system stack solution, composed of a reconfigurable architecture design, Field Programmable Synapse Array (FPSA) and its software system including neural synthesizer, temporal-to-spatial mapper, and placement & routing. We highly leverage the software system to make the hardware design compact and efficient. To satisfy the high-performance communication demand, we optimize it with a reconfigurable routing architecture and the placement & routing tool. To improve the computational density, we greatly simplify the PE circuit with the spiking schema and then adopt neural synthesizer to enable the high density computation-resources to support different kinds of NN operations. In addition, we provide spiking memory blocks (SMBs) and configurable logic blocks (CLBs) in hardware and leverage the temporal-to-spatial mapper to utilize them to balance the storage and computation requirements of NN. Owing to the end-to-end software system, we can efficiently deploy existing deep neural networks to FPSA. Evaluations show that, compared to one of state-of-the-art ReRAM-based NN accelerators, PRIME, the computational density of FPSA improves by 31x; for representative NNs, its inference performance can achieve up to 1000x speedup., Comment: Accepted by ASPLOS 2019

Published
2019
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5. Programmable Neural Network Trojan for Pre-Trained Feature Extractor

Author

Ji, Yu, Liu, Zixin, Hu, Xing, Wang, Peiqi, and Zhang, Youhui

Subjects
Computer Science - Cryptography and Security, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Neural and Evolutionary Computing
Abstract

Neural network (NN) trojaning attack is an emerging and important attack model that can broadly damage the system deployed with NN models. Existing studies have explored the outsourced training attack scenario and transfer learning attack scenario in some small datasets for specific domains, with limited numbers of fixed target classes. In this paper, we propose a more powerful trojaning attack method for both outsourced training attack and transfer learning attack, which outperforms existing studies in the capability, generality, and stealthiness. First, The attack is programmable that the malicious misclassification target is not fixed and can be generated on demand even after the victim's deployment. Second, our trojan attack is not limited in a small domain; one trojaned model on a large-scale dataset can affect applications of different domains that reuse its general features. Thirdly, our trojan design is hard to be detected or eliminated even if the victims fine-tune the whole model.

Published
2019

11. Bridging the Gap Between Neural Networks and Neuromorphic Hardware with A Neural Network Compiler

Author

Ji, Yu, Zhang, YouHui, Chen, WenGuang, and Xie, Yuan

Subjects
Computer Science - Neural and Evolutionary Computing, Computer Science - Emerging Technologies, Computer Science - Learning
Abstract

Different from developing neural networks (NNs) for general-purpose processors, the development for NN chips usually faces with some hardware-specific restrictions, such as limited precision of network signals and parameters, constrained computation scale, and limited types of non-linear functions. This paper proposes a general methodology to address the challenges. We decouple the NN applications from the target hardware by introducing a compiler that can transform an existing trained, unrestricted NN into an equivalent network that meets the given hardware's constraints. We propose multiple techniques to make the transformation adaptable to different kinds of NN chips, and reliable for restrict hardware constraints. We have built such a software tool that supports both spiking neural networks (SNNs) and traditional artificial neural networks (ANNs). We have demonstrated its effectiveness with a fabricated neuromorphic chip and a processing-in-memory (PIM) design. Tests show that the inference error caused by this solution is insignificant and the transformation time is much shorter than the retraining time. Also, we have studied the parameter-sensitivity evaluations to explore the tradeoffs between network error and resource utilization for different transformation strategies, which could provide insights for co-design optimization of neuromorphic hardware and software., Comment: Accepted by ASPLOS 2018

Published
2017

12. Linkage Regulation of Back‐To‐Back Connected Dimers as Guest Acceptors Enables Organic Solar Cells with Excellent Efficiency, Stability and Flexibility.

Author

You, Shiyong, Zhang, Youhui, Huang, Bin, Jeong, Sang Young, Shuai, Xiaozhong, Huang, Shuiyuan, Woo, Han Young, Wu, Feiyan, and Chen, Lie

Subjects
*SOLAR cell efficiency, *MOLECULAR shapes, *FLEXIBLE display systems, *SOLAR cells, *CHARGE carrier mobility
Abstract

High efficiency, stability, and flexibility are key prerequisites for the commercial applications of organic solar cells (OSCs). Herein, three back‐to‐back connected dimers (2Qx‐TT, 2Qx‐C3, 2Qx‐C6) are developed as the guest acceptors for OSCs with improved comprehensive performance. By regulating the linkage from rigid bithiophene to flexible alkyl chain, the back‐to‐back connected dimers display quite different molecular geometry and intermolecular interactions, consequently influencing their packing arrangement, film‐forming process, carrier mobilities, and the device efficiency, stability, and flexibility. By introducing these dimer acceptors as the guest into active layer, these dimers form alloy phases with the host acceptor, promoting film‐forming process and charge dynamics. All ternary devices exhibit improved PCEs of over 18% than the control binary device. Among them, 2Qx‐C3‐based ternary device obtains the best efficiency of as high as 19.03%. Moreover, thanks to the stronger entanglement favored by the dimers with flexible linkage, the PM6:BTP‐eC9:2Qx‐C3‐based device shows outstanding stability and flexibility. The flexible device displays an improved PCE of 16.09% with a crack‐onset strain of 15.0%, showing excellent mechanical robustness close to the all‐polymer devices. This work demonstrates the potential of the back‐to‐back connected dimer acceptors as the guest for highly efficient, stable and flexible OSCs. [ABSTRACT FROM AUTHOR]

Published
2024
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13. Influence of hydrocolloids and natural emulsifier in the physical stability of UHT oat beverage.

Author

Zhang, Youhui, Kong, Yu, Yan, Yanjun, Gao, Feng, Ma, He, and Liu, Changjin

Subjects
*XANTHAN gum, *GUAR gum, *POLYSACCHARIDES, *INFRARED absorption, *PARTICLE size distribution, *OATS
Abstract

This study aimed to improve the physical stability of ultra-high temperature (UHT) oat beverage by adding hydrophilic colloids (guar gum [GG] and xanthan gum [XG]) and a natural emulsifier (soluble soybean polysaccharide [SSPS]). The stability of the oat beverage was characterized by particle size, zeta potential, rheological properties, Fourier-transform infrared (FTIR) spectroscopy, backscattered light intensity (ΔBS), and microstructure. The results indicated that XG reduced the average particle size and size distribution of the beverage, indicating that XG could prevent particle aggregation. GG increases the apparent viscosity of the oat beverage without affecting the zeta potential. When SSPS was added to the oat beverage, it increased the absolute value of the zeta potential and the infrared absorption peak intensity, while the average particle size and backscattered light intensity (ΔBS) decreased, resulting in a more uniform microstructure. The zeta potential reached a maximum value of 32.12 when GG, XG, and SSPS were combined, indicating that the physical stability of the oat beverage was effectively improved when all three were present simultaneously. This study may provide some suggestions for the industrial production of low-viscosity cereal beverages with good stability. [ABSTRACT FROM AUTHOR]

Published
2024
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16. A system hierarchy for brain-inspired computing

Author

Zhang, Youhui, Qu, Peng, Ji, Yu, Zhang, Weihao, Gao, Guangrong, Wang, Guanrui, and Song, Sen

Subjects
Hierarchical organization (Computers) -- Research, Machine learning -- Research, Neural networks -- Research, Neural network, Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

Neuromorphic computing draws inspiration from the brain to provide computing technology and architecture with the potential to drive the next wave of computer engineering.sup.1-13. Such brain-inspired computing also provides a promising platform for the development of artificial general intelligence.sup.14,15. However, unlike conventional computing systems, which have a well established computer hierarchy built around the concept of Turing completeness and the von Neumann architecture.sup.16-18, there is currently no generalized system hierarchy or understanding of completeness for brain-inspired computing. This affects the compatibility between software and hardware, impairing the programming flexibility and development productivity of brain-inspired computing. Here we propose 'neuromorphic completeness', which relaxes the requirement for hardware completeness, and a corresponding system hierarchy, which consists of a Turing-complete software-abstraction model and a versatile abstract neuromorphic architecture. Using this hierarchy, various programs can be described as uniform representations and transformed into the equivalent executable on any neuromorphic complete hardware--that is, it ensures programming-language portability, hardware completeness and compilation feasibility. We implement toolchain software to support the execution of different types of program on various typical hardware platforms, demonstrating the advantage of our system hierarchy, including a new system-design dimension introduced by the neuromorphic completeness. We expect that our study will enable efficient and compatible progress in all aspects of brain-inspired computing systems, facilitating the development of various applications, including artificial general intelligence. The concept of neuromorphic completeness and a system hierarchy for neuromorphic computing are presented, which could improve programming-language portability, hardware completeness and compilation feasibility of brain-inspired computing systems, Author(s): Youhui Zhang [sup.1] [sup.2] [sup.3] , Peng Qu [sup.1] [sup.2] [sup.3] , Yu Ji [sup.1] [sup.2] [sup.3] , Weihao Zhang [sup.2] [sup.4] , Guangrong Gao [sup.5] , Guanrui Wang [...]

Published
2020
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19. Asymmetric Alloy Acceptor Strategy Guided by Similarity Principle Enables Highly Efficient and Stable Organic Solar Cells

Author

Zhang, Youhui, primary, Deng, Jiawei, additional, You, Shiyong, additional, Huang, Xuexiang, additional, Liu, Jiabin, additional, Cheng, Yujun, additional, Huang, Bin, additional, Chen, Xi, additional, Sun, Zhe, additional, Yang, Changduk, additional, Cao, Qian‐Yong, additional, Wu, Feiyan, additional, and Chen, Lie, additional

Published
2023
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21. Regulating the Sequence Structure of Conjugated Block Copolymers Enables Large‐Area Single‐Component Organic Solar Cells with High Efficiency and Stability

Author

Cheng, Yujun, primary, Mao, Qilong, additional, Zhou, Chunxiang, additional, Huang, Xuexiang, additional, Liu, Jiabin, additional, Deng, Jiawei, additional, Sun, Zhe, additional, Jeong, Seonghun, additional, Cho, Yongjoon, additional, Zhang, Youhui, additional, Huang, Bin, additional, Wu, Feiyan, additional, Yang, Changduk, additional, and Chen, Lie, additional

Published
2023
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24. Optimized Mapping Spiking Neural Networks onto Network-on-Chip

Author

Ji, Yu, Zhang, Youhui, Liu, He, Zheng, Weimin, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Carretero, Jesus, editor, Garcia-Blas, Javier, editor, Ko, Ryan K.L., editor, Mueller, Peter, editor, and Nakano, Koji, editor

Published
2016
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26. Asymmetric Alloy Acceptor Strategy Guided by Similarity Principle Enables Highly Efficient and Stable Organic Solar Cells.

Author

Zhang, Youhui, Deng, Jiawei, You, Shiyong, Huang, Xuexiang, Liu, Jiabin, Cheng, Yujun, Huang, Bin, Chen, Xi, Sun, Zhe, Yang, Changduk, Cao, Qian‐Yong, Wu, Feiyan, and Chen, Lie

Subjects
*SOLAR cells, *ALLOYS, *ENERGY dissipation, *DIPOLE moments, *PHOTOVOLTAIC power systems
Abstract

Introducing the guest materials into binary active layer to construct ternary organic solar cells (OSCs) is widely used to improve device performance. Nevertheless, designing the guest materials is a challenging task. Herein, asymmetric alloy acceptor strategy guided by similarity principle to design the guest materials is employed. Two small molecular acceptors (ZH1 with symmetric end groups and ZH2 with asymmetric end groups) with the same skeleton to the host acceptor are synthesized and compared. Compared to symmetric ZH1, asymmetric ZH2 delivers a remarkably higher efficiency (3.86% vs 13.03%) when paired with PM6, benefiting from the larger dipole moment to facilitate charge dynamics and more favorable morphology. More importantly, by introducing ZH1 and ZH2 as the guest materials into the PM6:BTP‐eC9 blend, both ZH1 and ZH2 well alloy with acceptor BTP‐eC9 due to the similar skeleton, not only providing a complementary absorption, but also optimizing and stabilizing the blend morphology. Notably, the asymmetric alloy acceptor distinctly outperforms symmetric alloy acceptor, PM6:BTP‐eC9:ZH2‐based device achieves an outstanding efficiency of 18.75% with better stability and reduced non‐radiative energy loss. Therefore, developing asymmetric alloy acceptor is an effective strategy to develop high‐performance and stable OSCs. [ABSTRACT FROM AUTHOR]

Published
2024
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27. Supplementary Data from A Self-Propagating c-Met–SOX2 Axis Drives Cancer-Derived IgG Signaling That Promotes Lung Cancer Cell Stemness

Author

Huang, Xinmei, primary, Zhang, Shenghua, primary, Tang, Jingshu, primary, Tian, Tian, primary, Pan, Yilin, primary, Wu, Lina, primary, Zhang, Jingxuan, primary, Liu, Yang, primary, Huang, Jing, primary, Dai, Hui, primary, Xu, Weiyan, primary, Zhang, Youhui, primary, Chen, Jinfeng, primary, Cao, Mengshu, primary, Zhang, Liang, primary, and Qiu, Xiaoyan, primary

Published
2023
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28. Data from A Self-Propagating c-Met–SOX2 Axis Drives Cancer-Derived IgG Signaling That Promotes Lung Cancer Cell Stemness

Author

Huang, Xinmei, primary, Zhang, Shenghua, primary, Tang, Jingshu, primary, Tian, Tian, primary, Pan, Yilin, primary, Wu, Lina, primary, Zhang, Jingxuan, primary, Liu, Yang, primary, Huang, Jing, primary, Dai, Hui, primary, Xu, Weiyan, primary, Zhang, Youhui, primary, Chen, Jinfeng, primary, Cao, Mengshu, primary, Zhang, Liang, primary, and Qiu, Xiaoyan, primary

Published
2023
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29. A Self-Propagating c-Met–SOX2 Axis Drives Cancer-Derived IgG Signaling That Promotes Lung Cancer Cell Stemness

Author

Huang, Xinmei, primary, Zhang, Shenghua, additional, Tang, Jingshu, additional, Tian, Tian, additional, Pan, Yilin, additional, Wu, Lina, additional, Zhang, Jingxuan, additional, Liu, Yang, additional, Huang, Jing, additional, Dai, Hui, additional, Xu, Weiyan, additional, Zhang, Youhui, additional, Chen, Jinfeng, additional, Cao, Mengshu, additional, Zhang, Liang, additional, and Qiu, Xiaoyan, additional

Published
2023
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30. Customized Network-on-Chip for Message Reduction

Author

Wang, Hongwei, Lu, Siyu, Zhang, Youhui, Yang, Guangwen, Zheng, Weimin, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Kobsa, Alfred, Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Sun, Xian-he, editor, Qu, Wenyu, editor, Stojmenovic, Ivan, editor, Zhou, Wanlei, editor, Li, Zhiyang, editor, Guo, Hua, editor, Min, Geyong, editor, Yang, Tingting, editor, Wu, Yulei, editor, and Liu, Lei, editor

Published
2014
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32. sj-docx-1-fst-10.1177_10820132231176875 - Supplemental material for Influence of hydrocolloids and natural emulsifier in the physical stability of UHT oat beverage

Author

Zhang, Youhui, Kong, Yu, Yan, Yanjun, Gao, Feng, Ma, He, and Liu, Changjin

Subjects
111199 Nutrition and Dietetics not elsewhere classified, FOS: Health sciences
Abstract

Supplemental material, sj-docx-1-fst-10.1177_10820132231176875 for Influence of hydrocolloids and natural emulsifier in the physical stability of UHT oat beverage by Youhui Zhang, Yu Kong, Yanjun Yan, Feng Gao, He Ma and Changjin Liu in Food Science and Technology International

Published
2023
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33. Software/Hardware Hybrid Network-on-Chip Simulation on FPGA

Author

Zhang, Youhui, Qu, Peng, Qian, Ziqiang, Wang, Hongwei, Zheng, Weimin, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Hsu, Ching-Hsien, editor, Li, Xiaoming, editor, Shi, Xuanhua, editor, and Zheng, Ran, editor

Published
2013
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34. Cache Optimizations of Distributed Storage for Software Streaming Services

Author

Zhang, Youhui, Qu, Peng, Li, Yanhua, Wang, Hongwei, Zheng, Weimin, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Kołodziej, Joanna, editor, Di Martino, Beniamino, editor, Talia, Domenico, editor, and Xiong, Kaiqi, editor

Published
2013
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39. Exploring Design Space Using Transaction Level Models

Author

Zhang, Youhui, Dong, Liu, Yu, Gu, Wang, Dongsheng, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Srikanthan, Thambipillai, editor, Xue, Jingling, editor, and Chang, Chip-Hong, editor

Published
2005
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40. Using Model-Based Test Program Generator for Simulation Validation

Author

Zhang, Youhui, Wang, Dongsheng, Wang, Jinglei, Zheng, Weimin, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Wu, Zhaohui, editor, Chen, Chun, editor, Guo, Minyi, editor, and Bu, Jiajun, editor

Published
2005
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41. Parallel Checkpoint/Recovery on Cluster of IA-64 Computers

Author

Zhang, Youhui, Wang, Dongsheng, Zheng, Weimin, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Cao, Jiannong, editor, Yang, Laurence T., editor, Guo, Minyi, editor, and Lau, Francis, editor

Published
2005
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42. A widely expressed free immunoglobulin κ chain with a unique Vκ4-1/Jκ3 pattern promotes colon cancer invasion and metastasis by activating the integrin β1/FAK pathway

Author

Wang, Qianqian, primary, Jiang, Dongyang, additional, Ye, Qing, additional, Zhou, Wenjing, additional, Ma, Junfan, additional, Wang, Chong, additional, Geng, Zihan, additional, Chu, Ming, additional, Zheng, Jie, additional, Chen, Hongchengcheng, additional, Huang, Jing, additional, Dai, Hui, additional, Zhang, Youhui, additional, Shen, Zhanlong, additional, Fu, Ning, additional, and Qiu, Xiaoyan, additional

Published
2022
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44. GaBAN

Author

Chen, Jiajie, primary, Yang, Le, additional, and Zhang, Youhui, additional

Published
2022
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45. A JDO Storage Cluster Based on Object Devices

Author

Zhang, Youhui, Wang, Dongsheng, Gao, Chongnan, Zheng, Weimin, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Jin, Hai, editor, Pan, Yi, editor, Xiao, Nong, editor, and Sun, Jianhua, editor

Published
2004
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46. The Flexible Replication Method in an Object-Oriented Data Storage System

Author

Zhang, Youhui, Hu, Jinfeng, Zheng, Weimin, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Dough, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Jin, Hai, editor, Gao, Guang R., editor, Xu, Zhiwei, editor, and Chen, Hao, editor

Published
2004
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47. An Object-Oriented Data Storage System on Network-Attached Object Devices

Author

Zhang, Youhui, Zheng, Weimin, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Yew, Pen-Chung, editor, and Xue, Jingling, editor

Published
2004
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49. Towards artificial general intelligence with hybrid Tianjic chip architecture

Author

Pei, Jing, Deng, Lei, Song, Sen, Zhao, Mingguo, Zhang, Youhui, Wu, Shuang, and Wang, Guanrui

Subjects
Artificial intelligence -- Equipment and supplies, Integrated circuits -- Design and construction -- Technology application, Semiconductor chips -- Design and construction -- Technology application, Computational neuroscience -- Usage, Standard IC, Artificial intelligence, Technology application, Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

There are two general approaches to developing artificial general intelligence (AGI).sup.1: computer-science-oriented and neuroscience-oriented. Because of the fundamental differences in their formulations and coding schemes, these two approaches rely on distinct and incompatible platforms.sup.2-8, retarding the development of AGI. A general platform that could support the prevailing computer-science-based artificial neural networks as well as neuroscience-inspired models and algorithms is highly desirable. Here we present the Tianjic chip, which integrates the two approaches to provide a hybrid, synergistic platform. The Tianjic chip adopts a many-core architecture, reconfigurable building blocks and a streamlined dataflow with hybrid coding schemes, and can not only accommodate computer-science-based machine-learning algorithms, but also easily implement brain-inspired circuits and several coding schemes. Using just one chip, we demonstrate the simultaneous processing of versatile algorithms and models in an unmanned bicycle system, realizing real-time object detection, tracking, voice control, obstacle avoidance and balance control. Our study is expected to stimulate AGI development by paving the way to more generalized hardware platforms. The 'Tianjic' hybrid electronic chip combines neuroscience-oriented and computer-science-oriented approaches to artificial general intelligence, demonstrated by controlling an unmanned bicycle., Author(s): Jing Pei [sup.1] [sup.2] , Lei Deng [sup.1] , Sen Song [sup.3] [sup.4] , Mingguo Zhao [sup.5] , Youhui Zhang [sup.6] , Shuang Wu [sup.1] [sup.2] , Guanrui Wang [...]

Published
2019
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