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3rd International Conference on Applied Machine Learning, ICAML 2021

作者： Li, Yizhou Wang, Yijie Cheng, Li Xu, Hongzuo Science and Technology on Parallel and Distributed Processing Laboratory College of Computer National University of Defense Technology Changsha China

ISBN: (纸本)9781665421256

Payload anomaly detection can discover malicious beliaviors tiidden in network packets. It is liard to liandle payload due to its various possible characters and complex semantic context, and tlius identifying abnormal payload is also a non-trivial task. Prior art only uses the n-gram language model to extract features, which directly leads to ultra-high-dimensional feature space and also fails to capture the context semantics fully. Accordingly, this paper proposes a word embedding-based context-sensitive network flow payload anomaly detection method (termed WECAD). First, WECAD obtains the initial feature representation of the payload through the word embedding-based method. Then, we propose a corpus pruning algorithm, which appUes the cosine similarity clustering and frequency distribution to prune inconsequential characters. We only keep the essential characters to reduce the calculation space. Subsequently, we propose a context learning algorithm. It employs the co-occurrence matrix transformation technology and introduces the backward step size to consider the order relationship of essential characters. Comprehensive experiments on real-world intrusion detection datasets validate the effectiveness of our method. © 2021 IEEE

关键词： Embeddings

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Unsupervised feature learning for human activity recognition using smartphone sensors 2

Unsupervised feature learning for human activity recognition...

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2nd International Conference on Mining Intelligence and Knowledge Exploration, MIKE 2014

作者： Li, Yongmou Shi, Dianxi Ding, B. Liu, Dongbo National Key Laboratory for Parallel and Distributed Processing College of Computer National University of Defense Technology Changsha China

ISBN: (纸本)9783319138169

Feature representation has a significant impact on human activity recognition. While the common used hand-crafted features rely heavily on the specific domain knowledge and may suffer from nonadaptability to the particular dataset. To alleviate the problems of handcrafted features, we present a feature extraction framework which exploits different unsupervised feature learning techniques to learning useful feature representation from accelerometer and gyroscope sensor data for human activity recognition. The unsupervised learning techniques we investigate include sparse auto-encoder, denoising auto-encoder and *** evaluate the performance on a public human activity recognition dataset and also compare our method with traditional features and another way of unsupervised feature learning. The results show that the learned features of our framework outperform the other two methods. The sparse auto-encoder achieves better results than other two techniques within our framework. © Springer International Publishing Switzerland 2014.

关键词： Signal encoding

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Research on online failure prediction model and status pretreatment method for exascale system

Research on online failure prediction model and status pretr...

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3rd International Conference on Cyber-Enabled distributed Computing and Knowledge Discovery, CyberC 2011

作者： Zhou, Hao Jiang, Yanhuang National Laboratory for Parallel and Distributed Processing College of Computer Science National University of Defense Technology Changsha China

ISBN: (纸本)9780769545578

The reliability issue of Exascale system is extremely serious. Traditional passive fault-tolerant methods, such as rollback-recovery, can not fully guarantee system reliability any more because of their large executing overhead and long recovering duration. Active fault tolerance is expected to become another important fault-tolerant approach for Exascale system. Focusing on system failure prediction, which is one key step of active fault tolerance, we construct online failure prediction model and research on the effective method of system status pretreatment. In order to improve the accuracy and real-time feature of current methods, the proposed Improved Adaptive Semantic Filter (IASF) method processes the latest system logs regularly, filtering useless information out of them according to their semantics. Adopting the main idea of Vector Space Model (VSM), IASF method creates Event Vector corresponding to each log record. By calculating the cosine of vectorial angle, it evaluates the semantics correlation between different log records, and then executes temporal and spatial redundant filter considering the burst feature of log records. IASF method is insensitive to the type of system log and does not introduce any expert system or domain knowledge. The experiment result shows that system can eliminate about 99.6% of useless log records after executing IASF method. © 2011 IEEE.

关键词： Fault tolerance

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Data dependence-based optimistic data consistency maintenance method

Data dependence-based optimistic data consistency maintenanc...

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6th IEEE International Conference on Computer and Information Technology, CIT 2006

作者： Zhou, Jing Wang, Yijie Li, Sikun National Key Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology China

ISBN: (纸本)076952687X

Data replication introduces well-known consistency issues. This paper puts forward the question about data dependence in data consistency, which embodies pseudo-conflict updates and update dependency. According to that, an optimistic data consistency method is proposed. In our method, data object is partitioned into data blocks by fixed size, as the basic unit of data management. Updates are compressed by Bloom filter technique and propagated in double-path. Negotiation algorithms detect and reconcile update conflicts, and dynamic data management algorithms accommodate dynamic data processing. The results of the performance evaluation show that our method is an efficient method to achieve consistency, good dynamic property, and strong robustness. © 2006 IEEE.

关键词： Information technology

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OHTMA:an optimized heuristic topology-aware mapping algorithm on the Tianhe-3 exascale supercomputer prototype

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Frontiers of Information Technology & Electronic Engineering 2020年第6期21卷 939-949页

作者： Yi-shui LI Xin-hai CHEN Jie LIU Bo YANG Chun-ye GONG Xin-biao GAN Sheng-guo LI Han XU Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense TechnologyChangsha 410073China

With the rapid increase of the size of applications and the complexity of the supercomputer architecture,topology-aware process mapping becomes increasingly *** communication cost has become a dominant constraint of the performance of applications running on the *** avoid a bad mapping strategy which can lead to terrible communication performance,we propose an optimized heuristic topology-aware mapping algorithm(OHTMA).The algorithm attempts to minimize the hop-byte metric that we use to measure the mapping *** incorporates a new greedy heuristic method and pair-exchange-based *** reduces the number of long-distance communications and effectively enhances the locality of the *** results on the Tianhe-3 exascale supercomputer prototype indicate that OHTMA can significantly reduce the communication costs.

关键词： High-performance computing Topology mapping Heuristic algorithm

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Error detection by redundant transaction in transactional memory system

Error detection by redundant transaction in transactional me...

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IEEE International Conference on Networking, Architecture and Storage

作者： Song, Wei Jia, Jia Peng, Yu-Xing National Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology Changsha 410073 China

ISBN: (纸本)9780769545097

This paper addresses the issue of error detection in transactional memory, and proposes a new method of error detection based on redundant transaction (EDRT). This method creates a transaction copy for every transaction, and executes both original transactions and transaction copies on adequate processor cores, and achieves error detection by comparing the execution results. EDRT utilizes the data-versioning mechanism of transactional memory to achieve the acquisition of an approximate minimum error detection comparing data set, and the acquisition is transparent and online. At last, this paper validates the EDRT through 5 test programs, including 4 SPLASH-2 benchmarks. The experimental results show that, the average error detecting cost is about 3.68% relative to the whole program, and it's only about 12.07% relative to the transaction parts of the program. © 2011 IEEE.

关键词： Fault tolerance

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Program optimization of array-intensive SPEC2k benchmarks on multithreaded GPU using CUDA and brook+

Program optimization of array-intensive SPEC2k benchmarks on...

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15th International Conference on parallel and distributed Systems, ICPADS '09

作者： Wang, Guibin Tang, Tao Fang, Xudong Ren, Xiaoguang National Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology Changsha Hunan China

ISBN: (纸本)9780769539003

Graphic processing Unit (GPU), with many lightweight data-parallel cores, can provide substantial parallel computing power to accelerate several general purpose applications. Both the AMD and NVIDIA corps provide their specific high performance GPUs and software platforms. As the floating-point computing capacity increases continually, the problem of "memory-wall" becomes more serious, especially for array-intensive applications. In this paper, we optimize and implement two SPEC2k benchmarks mgrid and swim on multithreaded GPU using CUDA and Brook+. In order to reduce the pressure on off-hip memory, we make use of data locality in multi-level memory hierarchies and hide long memory access latency via double-buffers. To balance inter-thread parallelism and intra-hread locality, we further tune thread granularity for each kernel and empirically study the best equilibrium point for this problem. Flow control instruction can significantly impact the effective instruction throughput. Oriented to this problem, we introduce a diverge elimination technology to convert condition expression into computing operation. Through all the optimizations, we gain the speedup of 10x-34x to the CPU implementation on the GPUs of AMD and NVIDIA respectively. Finally, we summarize and compares the GPUs from AMD and NVIDIA in hardware and software. © 2009 IEEE.

关键词： Graphics processing unit

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CANSE: A churn adaptive approach to network size estimation

CANSE: A churn adaptive approach to network size estimation

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16th IEEE International Conference on parallel and distributed Systems, ICPADS 2010

作者： Ma, Xing-Kong Wang, Yi-Jie Zheng, Zhong National Key Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology Changsha China

ISBN: (纸本)9780769543079

Network size is one of the fundamental information of distributed applications. The approach to estimate network size must feature both high accuracy and robustness in order to adapt to the dynamic environment in different topologies. However, existing approaches fail to guarantee accuracy and robustness simultaneously in dynamic topologies due to the randomness of nodes sampled. In this paper, we propose a churn adaptive approach to network size estimation - CANSE, which collects closest nodes in identification to each node's identification by sampling nodes periodically. Each node collects closest identifications by two schemes. One scheme is sampling random nodes from random walks along the topology. The other one is exchanging the closest identifications with other nodes. Finally, each node calculates the average spacing of the closest identifications collected to estimate network size. Compared with existing approaches, extensive experiments show that CANSE provides accurate estimation values quickly in various dynamic topologies. © 2010 IEEE.

关键词： Topology

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Power analysis and optimizations for GPU architecture using a power simulator

Power analysis and optimizations for GPU architecture using ...

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2010 3rd International Conference on Advanced Computer Theory and Engineering, ICACTE 2010

作者： Wang, Guibin National Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology Changsha Hunan China

ISBN: (纸本)9781424465408

As one of the most popular many-core architecture, GPUs have illustrated power in many non-graphic applications. Traditional general purpose computing systems tend to integrate GPU as the co-processor to accelerate parallel computing tasks. Meanwhile, GPUs also result in high power consumption, which accounts for a large proportion of the total system power consumption. In this paper, we mainly focus on the power analysis and optimizations for GPU architecture. The main contributions of this paper are: firstly, we establish a GPU power reserach platform, which is extended from an existing GPU simulator with several power models;secondly, we validate that, as the gap between shader core and memory speed becomes larger and larger, integrating more shader cores or enhancing running frequencies may not bring better performance, but results in higher energy consumption;thirdly, we show that traditional power optimization methods for CPUs, such as dynamic frequency scaling and concurrencythrottling, could be effectively applied on GPU architectures for better power efficiency, especially for memory-intensive applications. © 2010 IEEE.

关键词： Simulators

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Invalid pointer dereferences detection for CPS software based on extended pointer structures

Invalid pointer dereferences detection for CPS software base...

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2012 IEEE 6th International Conference on Software Security and Reliability Companion, SERE-C 2012

作者： Dong, Longming Dong, Wei Chen, Liqian National Laboratory for Parallel and Distributed Processing School of Computer National University of Defense Technology Changsha 410073 China

ISBN: (纸本)9780769547435

Invalid pointer dereferences, such as null pointer dereferences, dangling pointer dereferences and double frees, are a prevalent source of software bugs in CPS software, due to flexible dereferencing pointers along various pointer fields. Existing tools have high overhead or are incomplete, thereby limiting their efficiency in checking the kind of CPS software with shared and mutable memory. In this paper, we present a novel extended pointer structure for detecting all invalid pointer dereferences in this kind of CPS software. We propose an invalid pointer dereferences detection algorithm based on the uniform transformation of abstract heap states. Experimental evaluation about a set of large C benchmark programs shows that the proposed approach is sufficiently efficient in detecting invalid pointer dereferences of CPS software with shared and mutable memory. © 2012 IEEE.

关键词： Program debugging

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