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Issues on the Scalability in Designing a Massively Parallel Processor

Lu Xicheng

Strategic Study of CAE 2000, Volume 2, Issue 10,   Pages 105-109

Abstract:

The massively parallel processor (MPP) has been designed to meet the requirements for the high performance computing in many application fields of both national defense and economy. The structural scalability and the friendly programming are the two important and conflicting goals in designing a MPP system. Based on practice, the issues on the scalable design of MPPs are discussed in this paper.

Keywords： architecture     MPP     SMP     CC-NUMA     cluster     hypernode    

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Experience gained in analyzing severe accidents for WWER RP using CC SOCRAT

Frontiers in Energy 2021, Volume 15, Issue 4,   Pages 872-886 doi: 10.1007/s11708-021-0796-2

Abstract: For a rigorous calculational justification of BDBAs and SAs, it is necessary to develop an integral CCTo perform analyses using CC SOCRAT/1, the experience gained during execution of thermohydraulic codesThis study presents the results of the work performed in 2010–2020 in OKB Gidropress JSC using the CCApproaches have been considered to develop calculational models and analyze SAs using CC SOCRAT.

Keywords： of severe accidents (SOCRAT)     design basis accidents (DBAs)     severe accidents (SAs)     computer code (CC    

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CC@BCN@PANI core-shell nanoarrays as ultra-high cycle stability cathode for Zn-ion hybrid supercapacitors

Frontiers in Energy 2023, Volume 17, Issue 4,   Pages 555-566 doi: 10.1007/s11708-023-0882-8

Abstract: Because of the excellent specific capacity and conductivity of PANI, the CC@BCN@PANI core-shell nanoarraysTherefore, the CC@BCN@PANI-based ZHSCs exhibit superior electrochemical performances showing a specific

Keywords： CC@BCN@PANI cathode     Zn-ion hybrid supercapacitor     core-shell nanoarrays     high energy density     ultra-high    

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A comparative study of the mechanical properties, fracture behavior, creep, and shrinkage of chemically based self-consolidating concrete

Mahdi AREZOUMANDI, Mark EZZELL, Jeffery S VOLZ

Frontiers of Structural and Civil Engineering 2014, Volume 8, Issue 1,   Pages 36-45 doi: 10.1007/s11709-014-0243-0

Abstract: chemically-based self-consolidating concrete (SCC) mix with that of a corresponding conventional concrete (CCThe CC and SCC mix designs followed conventional proportioning in terms of aggregate type and contentThen, using only chemical admixtures, the authors converted the CC mix to an SCC mix with all of theThe comparison indicated that the SCC and CC mixes had virtually identical tensile splitting strengthsHowever, the SCC mix showed higher compressive strengths and fracture energies than the corresponding CC

Keywords： admixture     conventional concrete (CC)     creep     fracture mechanic     mechanical Properties     self-consolidating    

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HAM: a deep collaborative ranking method incorporating textual information Research Articles

Cheng-wei Wang, Teng-fei Zhou, Chen Chen, Tian-lei Hu, Gang Chen,rr@zju.edu.cn,zhoutengfei@zju.edu.cn,cc33

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 8,   Pages 1119-1266 doi: 10.1631/FITEE.1900382

Abstract: The recommendation task with a textual corpus aims to model customer preferences from both user feedback and item textual descriptions. It is highly desirable to explore a very deep neural network to capture the complicated nonlinear preferences. However, training a deeper recommender is not as effortless as simply adding layers. A deeper recommender suffers from the gradient vanishing/exploding issue and cannot be easily trained by gradient-based methods. Moreover, textual descriptions probably contain noisy word sequences. Directly extracting feature vectors from them can harm the recommender’s performance. To overcome these difficulties, we propose a new recommendation method named the HighwAy recoMmender (HAM). HAM explores a highway mechanism to make gradient-based training methods stable. A multi-head attention mechanism is devised to automatically denoise textual information. Moreover, a method is devised to train a deep neural recommender. Empirical studies show that the proposed method outperforms state-of-the-art methods significantly in terms of accuracy.

Keywords： 深度学习；推荐系统；高速公路网络；块坐标梯度下降    

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Title Author Date Type Operation

Issues on the Scalability in Designing a Massively Parallel Processor

Lu Xicheng

Journal Article

Experience gained in analyzing severe accidents for WWER RP using CC SOCRAT

Journal Article

CC@BCN@PANI core-shell nanoarrays as ultra-high cycle stability cathode for Zn-ion hybrid supercapacitors

Journal Article

A comparative study of the mechanical properties, fracture behavior, creep, and shrinkage of chemically based self-consolidating concrete

Mahdi AREZOUMANDI, Mark EZZELL, Jeffery S VOLZ

Journal Article

HAM: a deep collaborative ranking method incorporating textual information

Cheng-wei Wang, Teng-fei Zhou, Chen Chen, Tian-lei Hu, Gang Chen,rr@zju.edu.cn,zhoutengfei@zju.edu.cn,cc33

Journal Article