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computing, Communication, Perception and quantum Technology (CCPQT), International Conference on

作者： Xiaofeng Zou Yuanxi Peng Tuo Li Lingjun Kong Zhaochun Pang Lu Zhang Institute for Quantum Information & State Key Laboratory of High Performance Computing National University of Defense Technology Changsha China Second Research Institute Cloud Computing Equipment Innovation Center Jinan China

This paper proposes a novel hardware design to accelerate the Blake3 hash algorithm, a cryptographic hash function, on RISC-V architecture, using both vector extension (V1.0) and a specially designed Blake3 instruction. The design leverages the parallelism and simplicity of BLAKE3 to achieve high throughput and low latency, implementing the core compression function using a custom instruction set architecture that supports vector operations and constant computing. The Blake3 compression function is speed up in architecture based on hardware/software co-design. The design achieves a speed-up of 10 times for the compression function compare with a single core of 2.7GHz Xeon 8280 and 10% faster than an AVX512 implementation.

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quantum transport in an environment parametrized by dispersive bosons

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Physical Review B 2024年第8期109卷 085125-085125页

作者： Monodeep Chakraborty Holger Fehske Centre for Quantum Science and Technology Chennai Institute of Technology Chennai-600069 India Institute of Physics University of Greifswald Felix-Hausdorff-Straße 6 17489 Greifswald Germany Erlangen National High Performance Computing Center 91058 Erlangen Germany

We generalize the two-channel (Edwards) fermion-boson model describing quantum transport in a background medium to the more realistic case of dispersive bosons. Using the variational exact diagonalization technique, we numerically solve the extended model in a one-dimensional setting, for both downward and upward curved boson dispersion, and show that going away from the previous Einstein-boson assumption has profound consequences for the particle transport. Specifically, we analyze the ground-state and spectral properties and demonstrate the renormalization of the particle's coherent band, effective mass, photoemission spectra, and fermion-boson correlation functions due to the interplay of fluctuations and correlations in a dispersive environment.

关键词： Electrical conductivity Electronic structure Phonons Polarons

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LprViT:An Efficient ViT for LiDAR-Based Place Recognition Using Range Image

LprViT:An Efficient ViT for LiDAR-Based Place Recognition Us...

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Communication, Image and Signal Processing (CCISP), International Conference on

作者： Rui He Yunzhe Xiao Shaowu Yang Quantum Information & State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha China

Place recognition is a crucial component in the realm of simultaneous localization and mapping (SLAM) and autonomous driving. It can also enhance the performance of loop closure detection and global localization. LiDAR-based place recognition usually relies on global feature descriptors to accurately express the similarity between LiDAR scans. However, it is time-consuming to extract and generate the global feature descriptors from the original LiDAR data. As a result, treating LiDAR-based point clouds place recognition as a 2D image problem using range projection is becoming an increasingly common and successful strategy. Vision Transformer (ViT) is a Transformer model based on self-attention mechanism for image classification. Through self-attention mechanism, ViT out-performs CNN at modeling the global information of images. We investigate that whether ViT can be transferred to LiDAR-based place recognition tasks. Firstly, we introduce a new convolutional stem to replace the original linear embedding layer in ViT. Secondly, we establish synergy by integrating low-level fine-grained features from new convolution layer with high-level coarse-grained features from ViT by skip connections. Thirdly, we aggregate these features to construct the global feature descriptor via the NetVLAD technique. The results of experiments on KITTI confirm that our method can operate online and achieve superior performance on par with existing approaches.

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Experimental demonstration of quantum transport enhancement using time-reversal symmetry breaking on a silicon photonic chip

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Science China(Physics,Mechanics & Astronomy) 2022年第10期65卷 2-9页

作者： Yang Wang Xinyao Yu Shichuan Xue Yizhi Wang Junwei Zhan Chao Wu Pingyu Zhu Qilin Zheng Miaomiao Yu Yingwen Liu Xiaogang Qiang Junjie Wu Xuejun Yang Ping Xu Institute for Quantum Information&State Key Laboratory of High Performance Computing College of Computer Science and TechnologyNational University of Defense TechnologyChangsha 410073China National Innovation Institute of Defense Technology Academy of Military SciencesBeijing 100071China National Laboratory of Solid State Microstructures and School of Physics Nanjing UniversityNanjing 210093China

The continuous-time quantum walk is a basic model for studying quantum transport and developing quantum-enhanced algorithms. Recent studies show that by introducing a phase into the standard continuous-time quantum walk model, the time-reversal symmetry can be broken without changing the Hermitian property of the Hamiltonian. The time-reversal symmetry breaking quantum walk shows advantages in quantum transport, such as perfect state transfer, directional control, transport speedup, and quantum transport efficiency enhancement. In this work, we implement the time-reversal symmetry breaking quantum walks on a reconfigurable silicon photonic chip and demonstrate the enhancement introduced by breaking time-reversal symmetry. Perfect state transfer on a three-site ring, a quantum switch implemented on a six-site graph, and transport speedup using a linear chain of triangles are demonstrated with high fidelity. Time-reversal asymmetry has also been used in a simplified light-harvesting model,implying the potential of time-reversal symmetry breaking in photosynthesis investigations.

关键词： quantum walk time-reversal asymmetry quantum transport

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Mining Top-k Frequent Patterns over Streaming Graphs 28th

Mining Top-k Frequent Patterns over Streaming Graphs

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28th International Conference on Database Systems for Advanced Applications, DASFAA 2023

作者： Wang, Xi Zhang, Qianzhen Guo, Deke Zhao, Xiang Institute for Quantum Information and State Key Laboratory of High Performance Computing National University of Defense Technology Changsha China Science and Technology on Information Systems Engineering Laboratory National University of Defense Technology Changsha China Laboratory for Big Data and Decision National University of Defense Technology Changsha China

ISBN: (纸本)9783031306747

Mining top-k frequent patterns is an important operation on graphs, which is defined as finding k interesting subgraphs with the highest frequency. Most existing work assumes a static graph. However, graphs are dynamic in nature, which is described as streaming graphs. Mining top-k frequent patterns in streaming graphs is challenging due to the streaming nature of the input and the exponential time complexity of the problem. A naive solution is to calculate approximations of the frequent patterns in the streaming graph and then find the top-k answers, which is a memory- and time-consuming method. In this paper, we design a novel auxiliary data structure, FPC, to detect valid subgraph patterns and their frequency in real-time. We first convert each newly produced subgraph into a sequence and then map it into corresponding tracks in FPC based on hash functions. We theoretically prove that FPC can provide unbiased estimation and then give an error bound of our algorithm. In addition, we propose a vertical hashing and candidate buckets sampling technique to further improve FPC with higher space utilization and higher accuracy. Extensive experiments confirm that our approach generates high-quality results compared to the baseline method. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Hash functions

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Memory Access Optimization of high-Order CFD Stencil Computations on GPU 1

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21st International Conference on Parallel and Distributed computing, Applications, and Technologies, PDCAT 2020

作者： Wang, Shengxiang Li, Zhuoqian Che, Yonggang Institute for Quantum Information and State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology Changsha China

ISBN: (数字)9783030692445

ISBN: (纸本)9783030692438

Stencils computations are a class of computations commonly found in scientific and engineering applications. They have relatively lower arithmetic intensity. Therefore, their performance is greatly affected by memory access. This paper studies the issue of memory access optimization for the key stencil computations of a high-order CFD program on the NVidia GPU. Two methods are used to optimize the performance. First, we use registers to cache the data used by the stencil computations in the kernel. We use the CUDA warp shuffle functions to exchange data between neighboring grid points, and adjust the thread computation granularity to increase the data reuse. Second, we use the shared memory to buffer the grid data used by the stencil computations in the kernel, and utilize loop tiling to reduce redundant accesses to the global memory. performance evaluation is done on an NVidia Tesla K80 GPU. The results show that compared to the original implementation that only uses the global memory, the optimized implementation that utilizes the registers achieves a maximum speedup of 2.59 and 2.79 relatively for 15M and 60M grids, and the optimized implementation that utilizes the shared memory achieves a maximum speedup of 3.51 and 3.36 relatively for 15M and 60M grids. © 2021, Springer Nature Switzerland AG.

关键词： Graphics processing unit

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Task2Morph: Differentiable Task-Inspired Framework for Contact-Aware Robot Design

Task2Morph: Differentiable Task-Inspired Framework for Conta...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Yishuai Cai Shaowu Yang Minglong Li Xinglin Chen Yunxin Mao Xiaodong Yi Wenjing Yang State Key Laboratory of High Performance Computing Institute for Quantum Information College of Computer Science and Technology National University of Defense Technology Changsha China

Optimizing the morphologies and the controllers that adapt to various tasks is a critical issue in the field of robot design, aka. embodied intelligence. Previous works typically model it as a joint optimization problem and use search-based methods to find the optimal solution in the morphology space. However, they ignore the implicit knowledge of task-to-morphology mapping which can directly inspire robot design. For example, flipping heavier boxes tends to require more muscular robot arms. This paper proposes a novel and general differentiable task-inspired framework for contact-aware robot design called Task2Morph. We abstract task features highly related to task performance and use them to build a task-to-morphology mapping. Further, we embed the mapping into a differentiable robot design process, where the gradient information is leveraged for both the mapping learning and the whole optimization. The experiments are conducted on three scenarios, and the results validate that Task2Morph outperforms DiffHand, which lacks a task-inspired morphology module, in terms of efficiency and effectiveness.

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Enhanced Dcf Tracker Regularized by Reliable Sample Construction

Enhanced Dcf Tracker Regularized by Reliable Sample Construc...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Kun Hu Mingyu Cao Mengzhu Wang Long Lan Wenjing Yang Huibin Tan Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha China

Discriminative correlation filter (DCF) is a highly efficient tracking technique using the circulant shifted samples of search images to update the template, so the reliability of input samples determines template quality. In this paper, we rethink the reliability problem of input samples in advance during template updating and propose an enhanced DCF tracking method regularized by a novel sparse representation based reliable sample construction term, called enhanced sparse correlation filter (ESCF). Specifically, the reconstructed reliable samples are the sparse representation of circulant shifted samples of unfiltered input samples, in which the target will approach the center to preserve target visual cues into the template when using the cosine window. Besides, we jointly perform template learning and reliable sample construction into a unified learning paradigm to benefit from each other, which further can be carried out in the frequency domain without incurring excessive time cost by skillful decomposition. Experiments on several popular visual tracking datasets verify the efficacy of ESCF and show that ESCF performs favorably against several well-established representative counterparts.

关键词： Training Visualization Correlation Costs Target tracking Frequency-domain analysis Signal processing

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Decomposition, Interaction, Reconstruction Meets Global Context Learning In Visual Tracking

Decomposition, Interaction, Reconstruction Meets Global Cont...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Huibin Tan Kun Hu Mingyu Cao Mengzhu Wang Liyang Xu Wenjing Yang Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha China

Tensor decomposition and reconstruction attention is a promising global context learning approach because it can remain efficient while avoiding feature compression. To exploit its potential even further in visual tracking, we redesign a 3D tensor modeling paradigm, namely tensor Decomposition, Interaction, Reconstruction attention (DIR), respectively corresponding to three function components, Tensor Decomposition Module (TDM), Tensor Interaction Module (TIM) and Context Reconstruction Module (CRM). Specifically, TDM decomposes a 3D tensor feature into rank-1 context fragments in different dimension views. The ingenuity here lies in the introduction of Circular Convolution for processing features at arbitrary scales and channel-sharing segments to enhance the interaction of the two branches in the Siamese network architecture. TIM obtains the tensor planes of each dimension by the Cross-Similarity operation of rank-1 tensors and fused cubic features, which brings more interactions between all feature dimensions. CRM reconstructs 3D context representations with the outputs of the above modules. In experiments, DIR is embedded into the tracker to verify its effectiveness.

关键词： Visualization Tensors Three-dimensional displays Target tracking Convolution Customer relationship management Time division multiplexing

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Memory-based Exploration-value Evaluation Model for Visual Navigation

Memory-based Exploration-value Evaluation Model for Visual N...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Yongquan Feng Liyang Xu Minglong Li Ruochun Jin Da Huang Shaowu Yang Wenjing Yang Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha China

We propose a hierarchical visual navigation solution, called Memory-based Exploration-value Evaluation Model (MEEM), to improve the agent's navigation performance. MEEM employs a hierarchical policy to tackle the challenge of sparse rewards, holds an episodic memory to store the historical information of the agent, and applies an Exploration-value Evaluation Model to calculate an exploration-value for action planning at each location in the observable area. We experimentally verify MEEM by navigation performance comparison on two datasets including the grid-map dataset and the 3D scenes Gibson dataset, where our approach achieves state-of-the-art performance on both. Specifically, the overall success rate of MEEM is 95% on the grid-map dataset while the best competitor reaches 68% only. As for the Gibson dataset, the success rate of ours and the best competitor SemExp are 69.8% and 54.4%, respectively. Ablation analysis on the tile-map dataset indicates that all three components of MEEM have positive effects.

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