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23rd IEEE International Symposium on On-Line Testing and Robust system Design, IOLTS 2017

作者： Ye, Jing Gong, Yue Hu, Yu Li, Xiaowei State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781538603512

Physical Unclonable Function {PUF) is severely threatened by modeling attacks. This paper proposes a novel Polymorphic PUF for CPU+FPGA SoC. We fully exploit the dynamic reconfigurability of the SoC to minimize the Challenge Response Pair (CRP) correlation so as to resist modeling attacks. An asymmetric RO pair is proposed to produce the response. Experiments on real CPU+FPGA SoCs show the high resistance of Polymorphic PUF against modeling attacks, with good uniformity and uniqueness. © 2017 IEEE.

关键词： system-on-chip

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Characterizing big data analytics workloads on POWER8 SMT processors

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High technology Letters 2017年第3期23卷 245-251页

作者：贾禛 Zhan Jianfeng Wang Lei Zhang Lixin State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 P. R. China University of Chinese Academy of Sciences Beijing 100049 P. R. China

Big data analytics is emerging as one kind of the most important workloads in modern data centers. Hence,it is of great interest to identify the method of achieving the best performance for big data analytics workloads running on state-of-the-art SMT( simultaneous multithreading) processors,which needs comprehensive understanding to workload characteristics. This paper chooses the Spark workloads as the representative big data analytics workloads and performs comprehensive measurements on the POWER8 platform,which supports a wide range of multithreading. The research finds that the thread assignment policy and cache contention have significant impacts on application performance. In order to identify the potential optimization method from the experiment results,this study performs micro-architecture level characterizations by means of hardware performance counters and gives implications accordingly.

关键词： simultaneous multithreading(SMT) workloads characterization POWER8 big data analytics

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A heuristic clustering algorithm based on high density-connected partitions

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High technology Letters 2018年第2期24卷 149-155页

作者： Yuan Lufeng Yao Erlin Tan Guangming State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 P. R. China University of Chinese Academy of Sciences Beijing 100049 P. R. China

Clustering data with varying densities and complicated structures is important,while many existing clustering algorithms face difficulties for this problem. The reason is that varying densities and complicated structure make single algorithms perform badly for different parts of data. More intensive parts are assumed to have more information probably,an algorithm clustering from high density part is proposed,which begins from a tiny distance to find the highest density-connected partition and form corresponding super cores,then distance is iteratively increased by a global heuristic method to cluster parts with different densities. Mean of silhouette coefficient indicates the cluster performance. Denoising function is implemented to eliminate influence of noise and outliers. Many challenging experiments indicate that the algorithm has good performance on data with widely varying densities and extremely complex structures. It decides the optimal number of clusters *** knowledge is not needed and parameters tuning is easy. It is robust against noise and outliers.

关键词： heuristic clustering density-based spatial clustering of applications with noise( DBSCAN) density-based clustering agglomerative clustering machine learning high density-connected partitions optimal clustering number

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Video Face Recognition system: RetinaFace-Mnet-Faster and Secondary Search

Video Face Recognition System: RetinaFace-Mnet-Faster and Se...

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Future of Information and Communication Conference, FICC 2021

作者： Li, Qian Guo, Nan Ye, Xiaochun Fan, Dongrui Tang, Zhimin State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783030731021

Face recognition is widely used in the scene. However, different visual environments require different methods, and face recognition has a difficulty in complex environments. Therefore, this paper mainly experiments complex faces in the video. First, we design an image pre-processing module for fuzzy scene or under-exposed faces to enhance images. Our experimental results demonstrate that effective images pre-processing improves the accuracy of 0.11%, 0.2% and 1.4% on LFW, WIDER FACE and our datasets, respectively. Second, we propose RetinacFace-mnet-faster for detection and a confidence threshold specification for face recognition, reducing the lost rate. Our experimental results show that our RetinaFace-mnet-faster for 640 × 480 resolution on the Tesla P40 and single-thread improve speed of 16.7% and 70.2%, respectively. Finally, we design secondary search mechanism with HNSW to improve performance. Ours is suitable for large-scale datasets, and experimental results show that our method is 82% faster than the violent retrieval for the single-frame detection. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Face recognition

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A case study of 3D RTM-TTI algorithm on multicore and many-core platforms

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High technology Letters 2017年第2期23卷 185-190页

作者：张秀霞 Tan Guangming Chen Mingyu Yao Erlin State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 P. R. China University of Chinese Academy of Sciences Beijing 100049 P. R. China

3D reverse time migration in tiled transversly isotropic(3D RTM-TTI) is the most precise model for complex seismic ***,vast computing time of 3D RTM-TTI prevents it from being widely used,which is addressed by providing parallel solutions for 3D RTM-TTI on multicores and *** data parallelism and memory optimization,the hot spot function of 3D RTMTTI gains 35.99 X speedup on two Intel Xeon CPUs,89.75 X speedup on one Intel Xeon Phi,89.92 X speedup on one NVIDIA K20 GPU compared with serial CPU *** study makes RTM-TTI practical in *** the computation pattern in RTM is stencil,the approaches also benefit a wide range of stencil-based applications.

关键词： 3D RTM-TTI Intel Xeon Phi NVIDIA K20 GPU stencil computing manycore multicore seismic imaging

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Degradation analysis and optimization of temperature effect on MEMRISTOR-based Neural Network Accelerators by electro-thermal simulation

Degradation analysis and optimization of temperature effect ...

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2020 International Conference on Electronics, Communications and Information technology, CECIT 2020

作者： Shang, Mengjun Yin, Longxiang Xu, Ning School of Information Engineering Wuhan University of Technology Wuhan China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China

Nowadays, memristor-based neural network accelerators have been widely studied due to their outstanding performance in massive parallel vector matrix multiplication. However, the memristor is sensitive to temperature and its on/off state operation window can be seriously degraded by the increasing temperature, which may lead to computation failures in memristor -based NN accelerators. In this work, we establish an electro-thermal simulation platform to evaluate the temperature impact on memristor -based NN accelerators. With this platform, we first investigate the impact on computation accuracy with the temperature increase in different NN layers in the accelerators. We then apply a temperature-aware NN weight mapping scheme to the most temperature-sensitive layer and achieve 28.89% improvement in computation accuracy, which only has 0.06% difference with the improvement achieved by applied the mapping scheme to the whole NN model. This finding can help to simplify the temperature-aware hardware optimization design in memristor-based neural network accelerators and reduce the power consumption. © Published under licence by IOP Publishing Ltd.

关键词： Memristors

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DU-DARTS: Decreasing the Uncertainty of Differentiable architecture Search 32

DU-DARTS: Decreasing the Uncertainty of Differentiable Archi...

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32nd British Machine Vision Conference, BMVC 2021

作者： Lu, Shun Hu, Yu Yang, Longxing Sun, Zihao Mei, Jilin Zeng, Yiming Li, Xiaowei Research Center for Intelligent Computing Systems Institute of Computing Technology Chinese Academy of Sciences China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China School of Computer Science and Technology University of Chinese Academy of Sciences China Tecent ADlab China

Differentiable Neural architecture Search (DARTS) recently attracts a lot of research attention because of its high efficiency. However, the competition of candidate operations in DARTS introduces high uncertainty for selecting the truly important operation, thus leading to serious performance collapse. In this work, we decrease the uncertainty of differentiable architecture search (DU-DARTS) by enforcing the distribution of architecture parameters to approach the one-hot categorical distribution and by replacing the zero operation with a gate switch. Without any extra search cost, our method achieves state-of-the-art performance with 2.32%, 16.74%, and 24.1% test error on CIFAR-10, CIFAR-100, and ImageNet datasets, respectively. Moreover, DU-DARTS can robustly find an excellent architecture on NAS-Bench-1Shot1 and NAS-Bench-201, which further demonstrates the effectiveness of our method. The source code is available at https://***/ShunLu91/DU-DARTS. © 2021. The copyright of this document resides with its authors.

关键词： computer vision

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Feedback-controlled security-aware and energy-efficient scheduling for real-time embedded systems

Feedback-controlled security-aware and energy-efficient sche...

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7th International Conference on Embedded and Multimedia computing, EMC 2012

作者： Ma, Yue Sang, Nan Jiang, Wei Zhang, Lei School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9789400750753

Security has become an important characteristic for many real-time systems. Due to the lack of enough and stable energy supply in battery-powered embedded systems, one of the foremost challenges is the mismatch between energy and performance requirements of security processing. In this paper, we propose a security-aware and energy-efficient scheduling algorithm that aims at reducing energy consumption while ensuring the real-time and security requirements. Based on the feedback control theory, we employ a feedback unit to keep track of the CPU utilization and manage the security level dynamically. Simulation results show the effectiveness and efficiency of the proposed algorithm. © 2012 Springer Science+Business Media.

关键词： Feedback control

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HDCat: Effectively identifying hot data in large-Scale I/O streams with enhanced temporal locality 15th

HDCat: Effectively identifying hot data in large-Scale I/O s...

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15th International Conference on Algorithms and architectures for Parallel Processing, ICA3PP 2015

作者： Chen, Jiahao Deng, Yuhui Huang, Zhan Department of Computer Science Jinan University Guangzhou510632 China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9783319271217

Hot data is very important for optimizing modern computer systems. For example, the identified hot data can be employed to extend the lifespan of flash memory. However, it is very challenging to effectively identify hot data with low memory consumption and low runtime overhead. This paper proposes a Hot Data Catcher (HDCat) which can effectively identify hot data in large-scale I/O streams by leveraging enhanced temporal locality. HDCat only maintains a hot data queue and a candidate hot data queue to record the data access pattern by tracking limited data set, thus effectively reducing the memory consumption. Furthermore, HDCat adopts a D-bit counter and a recency-bit to leverage both the frequency and recency contained in the data stream. Additionally, HDCat can significantly reduce the conversion between hot data and cold data. Real traces are used to evaluate the proposed approach. Experimental results demonstrate that HDCat significantly outperforms the state-of-the-art Multi-hash algorithm and the two-level LRU algorithm. © Springer International Publishing Switzerland 2015.

关键词： Hash functions

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Designing a power-aware replication strategy for storage clusters

Designing a power-aware replication strategy for storage clu...

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2013 IEEE International Conference on Green computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social computing, GreenCom-iThings-CPSCom 2013

作者： Zhang, Lingwei Deng, Yuhui Department of Computer Science Jinan University Guangzhou 510632 China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9780769550466

The exponential data growth is presenting challenges to traditional storage systems. Component-based cluster storage systems, due to their high scalability, are becoming the architecture of next generation storage systems. Cluster storage systems often use data replication to ensure high availability, fault tolerance, and load balance. However, this kind of data replication not only consumes a large amount of storage resources, but also generates more energy consumption. This paper presents a power-aware data replication strategy by leveraging data access behavior. This strategy uses 80/20 rule (80% of the data accesses often go to 20% of the storage space) to replicate only a small amount of frequently accessed data. Furthermore, the storage nodes are divided into a hot node set and a cold node set. Hot nodes, which store a small amount of hot data copies, are always in an active state to guarantee the QoS of the system. The cold nodes which store a large number of infrequently accessed cold data, are placed in a low power state, thus reducing the energy consumption of the cluster storage system. The experimental results show that the proposed strategy can effectively reduce the resource and energy consumption of the system, while ensuring the system performance. © 2013 IEEE.

关键词： Energy utilization

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