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Coarse-grained automatic parallelization approach for branch nested loop

International Journal of Performability engineering 2019年第11期15卷 2871-2881页

作者： Liu, Hui Xu, Jinlong Ding, Lili College of Computer and Information Engineering Henan Normal University Xinxiang453007 China Engineering Technology Research Center for Computing Intelligence and Data Mining in Henan Province Xinxiang453007 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001 China

GCC compiler is a retargetable compiler program that was developed to increase the efficiency of programs in the GNU system. In recent years, compiler optimization based on data dependency analysis has become an important research area of modern compilers. Existing GCC compilers can only conduct dependency analysis on perfect nested loops. In order to better explore the coarse-grained parallelism of the nested loops, we propose a dependence test method that can deal with the branch nested loops. Firstly, we identify the branch nested loop in the programs. Then, we analyze the relationship between the array subscript and the outer index variable of the branch nested loop. Finally, we calculate the distance vector of the outer loop index variable and determine whether the loop has dependence through distance vector detection. Experimental results show that our method can correctly and effectively analyze the dependence relationship of branch nested loops. © 2019 Totem Publisher, Inc. All rights reserved.

关键词： Program compilers

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ZeroSpy: Exploring Software Inefficiency with Redundant Zeros 20

ZeroSpy: Exploring Software Inefficiency with Redundant Zero...

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Supercomputing Conference

作者： Xin You Hailong Yang Zhongzhi Luan Depei Qian Xu Liu Beihang University China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi China North Carolina State University USA

ISBN: (数字)9781728199986

ISBN: (纸本)9781728199993

Redundant zeros cause inefficiencies in which the zero values are loaded and computed repeatedly, resulting in unnecessary memory traffic and identity computation that waste memory bandwidth and CPU resources. optimizing compilers is difficult in eliminating these zero-related inefficiencies due to limitations in static analysis. Hardware approaches, in contrast, optimize inefficiencies without code modification, but are not widely adopted in commodity processors. In this paper, we propose ZeroSpy - a fine-grained profiler to identify redundant zeros caused by both inappropriate use of data structures and useless computation. ZeroSpy also provides intuitive optimization guidance by revealing the locations where the redundant zeros happen in source lines and calling contexts. The experimental results demonstrate ZeroSpy is capable of identifying redundant zeros in programs that have been highly optimized for years. Based on the optimization guidance revealed by ZeroSpy, we can achieve significant speedups after eliminating redundant zeros.

关键词： Optimizing compilers Memory management Redundancy Static analysis Production Software Optimization

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Robust optimization for quantum reinforcement learning control using partial observations

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Physical Review A 2022年第6期105卷 062443-062443页

作者： Chen Jiang Yu Pan Zheng-Guang Wu Qing Gao Daoyi Dong State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control College of Control Science and Engineering Zhejiang University Hangzhou 310027 China The School of Automation Science and Electrical Engineering and Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing 100191 China The School of Engineering and Information Technology University of New South Wales Canberra Australian Capital Territory 2600 Australia

The current quantum reinforcement learning control models often assume that the quantum states are known a priori for control optimization. However, full observation of the quantum state is experimentally infeasible due to the exponential scaling of the number of required quantum measurements on the number of qubits. In this paper, we investigate a robust reinforcement learning method using partial observations to overcome this difficulty. This control scheme is compatible with near-term quantum devices, where the noise is prevalent and predetermining the dynamics of the quantum state is practically impossible. We show that this simplified control scheme can achieve similar or even better performance when compared to the conventional methods relying on full observation. We demonstrate the effectiveness of this scheme on examples of quantum state control and the quantum approximate optimization algorithm (QAOA). It has been shown that high-fidelity state control can be achieved even if the noise amplitude is at the same level as the control amplitude. Besides, an acceptable level of optimization accuracy can be achieved for a QAOA with a noisy control Hamiltonian. This robust control optimization model can be trained to compensate for the uncertainties in practical quantum computing.

关键词： Machine learning Quantum control Quantum engineering

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Magnetoresistance oscillations in vertical junctions of 2D antiferromagnetic semiconductor CrPS4

arXiv

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arXiv 2024年

作者： Shi, Pengyuan Wang, Xiaoyu Zhang, Lihao Song, Wenqin Yang, Kunlin Wang, Shuxi Zhang, Ruisheng Zhang, Liangliang Taniguchi, Takashi Watanabe, Kenji Yang, Sen Zhang, Lei Wang, Lei Shi, Wu Pan, Jie Wang, Zhe MOE Key Laboratory for Nonequilibrium Synthesis and Modulation of Condensed Matter Shaanxi Province Key Laboratory of Advanced Materials and Mesoscopic Physics School of Physics Xi'an Jiaotong University Xi'An710049 China State Key Laboratory of Surface Physics Institute for Nanoelectronic Devices and Quantum Computing Fudan University Shanghai200433 China State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong University Xi'An710049 China Research Center for Materials Nanoarchitectonics National Institute for Materials Science 1-1 Namiki Tsukuba305-0044 Japan Research Center for Electronic and Optical Materials National Institute for Materials Science 1-1 Namiki Tsukuba305-0044 Japan Key Laboratory of Quantum Materials and Devices of Ministry of Education School of Physics Southeast University Nanjing211189 China Zhangjiang Fudan International Innovation Center Fudan University Shanghai201210 China

Magnetoresistance (MR) oscillations serve as a hallmark of intrinsic quantum behavior, traditionally observed only in conducting systems. Here we report the discovery of MR oscillations in an insulating system, the vertical junctions of CrPS4 which is a two dimensional (2D) A-type antiferromagnetic semiconductor. Systematic investigations of MR peaks under varying conditions, including electrode materials, magnetic field direction, temperature, voltage bias and layer number, elucidate a correlation between MR oscillations and spin-canted states in CrPS4. Experimental data and analysis point out the important role of the in-gap electronic states in generating MR oscillations, and we proposed that spin selected interlayer hopping of localized defect states may be responsible for it. Our findings not only illuminate the unusual electronic transport in CrPS4 but also underscore the potential of van der Waals magnets for exploring interesting phenomena. Copyright © 2024, The Authors. All rights reserved.

关键词： Van der Waals forces

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Augmenting photoluminescence of monolayer MoS_(2) using high order modes in a metal dimer-on-film nanocavity

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Photonics Research 2021年第4期9卷 501-506页

作者： Shiyin Cao Liping Hou Qifa Wang Chenyang Li Weixing Yu Xuetao Gan Kaihui Liu Malin Premaratne Fajun Xiao Jianlin Zhao MOE Key Laboratory of Material Physics and Chemistry under Extraordinary Conditions and Shaanxi Key Laboratory of Optical Information TechnologySchool of Physical Science and TechnologyNorthwestern Polytechnical UniversityXi’an 710129China Key Laboratory of Spectral Imaging Technology of Chinese Academy of Sciences Xi’an 710119China State Key Laboratory for Mesoscopic Physics Collaborative Innovation Centre of Quantum MatterSchool of PhysicsPeking UniversityBeijing 100871China Advanced Computing and Simulation Laboratory(AχL) Department of Electrical and Computer Systems EngineeringMonash UniversityClaytonVIC 3800Australia

Plasmonic particle-on-film nanocavities,supporting gap modes with ultra-small volume,provide a great solution to boost light–matter interactions at the *** this work,we report on the photoluminescence(PL)enhancement of monolayer MoS_(2) using high order modes of an Au nanosphere dimer-on-film nanocavity(DoFN).The high order plasmon modes,consisting of two bonding quadrupoles in the dimer and their images in the Au film,are revealed by combining the polarization-resolved scattering spectra with the numerical *** integrating the monolayer MoS_(2) into the DoFN,these high order modes are used to enhance PL intensity through simultaneously boosting the absorption and emission processes,producing a 1350-fold enhancement *** opens an avenue to enhance the light–matter interaction with high order plasmon modes and may find applications in future optoelectronics and nanophotonics devices.

关键词： cavity high integrating

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Wave power extraction from a piezoelectric wave energy converter integrated in a pile-supported breakwater 14th

Wave power extraction from a piezoelectric wave energy conve...

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14th European Wave and Tidal Energy Conference, EWTEC 2021

作者： Zheng, S. Meylan, M.H. Zhang, X. Iglesias, G. Greaves, D. School of Engineering Computing and Mathematics University of Plymouth Drake Circus PlymouthPL4 8AA United Kingdom School of Mathematical and Physical Sciences The University of Newcastle Callaghan2308 Australia State Key Laboratory of Ocean Engineering Shanghai Jiao Tong University Shanghai200240 China MaREI Environmental Research Institute School of Engineering University College Cork College Road Cork Ireland

A submerged flexible plate with piezoelectric layers bonded to both faces of it may work as a piezoelectric wave energy converter (PWEC), the elastic motion of which excited by water waves can be transformed into useful electricity due to the piezoelectric effect. In this paper, wave power extraction from a PWEC moored in front of a pile-supported breakwater is investigated. The PWEC is simply supported at the edge. To evaluate the performance of the breakwater-attached PWEC, a hydroelastic model with the electro-mechanical and the hydrodynamic problems of the PWEC coupled together is developed based on linear potential flow theory and the eigenfunction matching method. Effects of the width and submergence of the PWEC, and also the width and draft of the breakwater, on wave power absorption of the breakwater integrated PWEC are examined with the employment of the present model. It is revealed that as the PWEC width increases, more peaks of the frequency response of wave power absorption efficiency can be excited in the computed range of wave conditions. As the PWEC submergence increases, the main peaks of the wave power absorption efficiency become lower and narrower, and slightly shift towards large wave frequencies. © European Wave and Tidal Energy Conference 2021.

关键词： Analytical model Breakwater Piezoelectricity Potential flow theory Wave power absorption

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Machine Learning Enhanced Electrochemical Simulations for Dendrites Nucleation in Li Metal Battery

arXiv

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arXiv 2024年

作者： Hu, Taiping Huang, Haichao Zhou, Guobing Wang, Xinyan Zhu, Jiaxin Cheng, Zheng Fu, Fangjia Wang, Xiaoxu Dai, Fuzhi Yu, Kuang Xu, Shenzhen Beijing Key Laboratory of Theory and Technology for Advanced Battery Materials School of Materials Science and Engineering Peking University Beijing100871 China AI for Science Institute Beijing100084 China Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen518055 China School of Chemical Engineering Jiangxi Normal University Nanchang330022 China DP Technology Beijing100080 China State Key Laboratory of Physical Chemistry of Solid Surfaces iChEM College of Chemistry and Chemical Engineering Xiamen University Xiamen361005 China School of Mathematical Sciences Peking University Beijing100871 China School of Materials Science and Engineering University of Science and Technology Beijing Beijing100083 China

Uncontrollable dendrites growth during electrochemical cycles leads to low Coulombic efficiency and critical safety issues in Li metal batteries. Hence, a comprehensive understanding of the dendrite formation mechanism is essential for further enhancing the performance of Li metal batteries. Machine learning accelerated molecular dynamics (MD) simulations can provide atomic-scale resolution for various key processes at an ab-initio level accuracy. However, traditional MD simulation tools hardly capture Li electrochemical depositions, due to lack of an electrochemical constant potential (ConstP) condition. In this work, we propose a ConstP approach that combines a machine learning force field with the charge equilibration method to reveal the dynamic process of dendrites nucleation at Li metal anode surfaces. Our simulations show that inhomogeneous Li depositions, following Li aggregations in amorphous inorganic components of solid electrolyte interphases, can initiate dendrites nucleation, accompanied by dead Li cluster formation. Our study provides microscopic insights for Li dendrites formations in Li metal anodes. More importantly, we present an efficient and accurate simulation method for modeling realistic ConstP conditions, which holds considerable potential for broader applications in modeling complex electrochemical interfaces. © 2024, CC BY.

关键词： Dendrites (metallography)

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Improved Method for Dynamic Heterogeneous Redundant Model Database

Improved Method for Dynamic Heterogeneous Redundant Model Da...

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IEEE Information Technology and Mechatronics engineering Conference (ITOEC)

作者： Yuan Tang Zheng Zhang YuFeng Zhao ZhenWu Liu State key laboratory of mathematics engineering and advanced computing Zhengzhou China

ISBN: (数字)9781728143231

ISBN: (纸本)9781728143248

The correctness and reliability of data is the most basic element of data storage system. It is primary for data security to ensure the correctness and reliability of data. The dynamic heterogeneous redundancy model has received more and more attention in recent years, and it has a good effect in defending known and unknown vulnerabilities. However, In the process of applying the model to database security, the researchers have found the inconsistent reads and writes of heterogeneous databases resulting in the difficulty of accurate data synchronization. To solve this problem, an improved method of heterogeneous database operation language decision merging is proposed, and the correctness, security and effectiveness of this means is tested. The experimental results show that this method can ensure the security of the system and reduce the false alarm.

关键词： Databases Data models Synchronization Memory Web servers Encryption

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Optimizing the Memory Hierarchy by Compositing Automatic Transformations on Computations and Data

Optimizing the Memory Hierarchy by Compositing Automatic Tra...

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IEEE/ACM International Symposium on Microarchitecture (MICRO)

作者： Jie Zhao Peng Di State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Huawei Technologies Co. Ltd Beijing China

ISBN: (数字)9781728173832

ISBN: (纸本)9781728173849

Optimizing compilers exploit the memory hierarchy using loop tiling and fusion, but these two transformations usually interfere with each other due to the oversight of transformations on data in memories. We present a novel composition of loop tiling and fusion in this paper. Unlike existing tiling-after-fusion algorithms that only transform computation spaces, our approach first applies rectangular/parallelogram tiling to live-out computation spaces for fitting the memory hierarchy, followed by the computation of the memory footprints required by each tile. The upwards exposed data extracted from the memory footprints are used to determine the tile shapes of intermediate computation spaces, allowing the construction of arbitrary tile shapes. Finally, our technique implements a post-tiling fusion strategy for maximizing data locality without losing tilability or parallelism of live-out computation spaces, thereby enabling storage reduction and reuse, and optimizing the memory hierarchy. We demonstrate that our approach can achieve superior performance on both CPU and GPU architectures over the state of the art by experimenting on 11 benchmarks extracted from numerous domains including neural networks, image processing, sparse matrix computation and linear algebra. Also, the results of the ResNet-50 model on an AI accelerator show that our approach can obtain 16% performance improvement.

关键词： Shape Tiles Memory management Transforms Benchmark testing Sparse matrices Optimization

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A CGAN-LSTM-Based Framework for Time-Varying Non-Stationary Channel Modeling

arXiv

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arXiv 2025年

作者： Guo, keying He, Ruisi Yang, Mi Zhang, Yuxin Ai, Bo Zhang, Haoxiang Han, Jiahui Chen, Ruifeng School of Electronics and Information Engineering Beijing Jiaotong University Beijing100044 China State Key Laboratory of Advanced Rail Autonomous Operation Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong University Beijing100044 China China Academy of Industrial Internet Ministry of Industry and Information Technology Beijing China Institute of Computing Technology China Academy of Railway Sciences Corporation Limited Beijing100081 China

Time-varying non-stationary channels, with complex dynamic variations and temporal evolution characteristics, have significant challenges in channel modeling and communication system performance evaluation. Most existing methods of time-varying channel modeling focus on predicting channel state at a given moment or simulating short-term channel fluctuations, which are unable to capture the long-term evolution of the channel. This paper emphasizes the generation of long-term dynamic channel to fully capture evolution of non-stationary channel properties. The generated channel not only reflects temporal dynamics but also ensures consistent stationarity. We propose a hybrid deep learning framework that combines conditional generative adversarial networks (CGAN) with long short-term memory (LSTM) networks. A stationarity-constrained approach is designed to ensure temporal correlation of the generated time-series channel. This method can generate channel with required temporal non-stationarity. The model is validated by comparing channel statistical features, and the results show that the generated channel is in good agreement with raw channel and provides good performance in terms of non-stationarity. Copyright © 2025, The Authors. All rights reserved.

关键词： Long Term Evolution (LTE)

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