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Detecting faults by tracing companion states in cloud computing systems

Jisuanji Xuebao/Chinese Journal of Computers 2012年第5期35卷 856-870页

作者： Rao, Xiang Wang, Huai-Min Chen, Zhen-Bang Zhou, Yang-Fan Cai, Hua Zhou, Qi Sun, Ting-Tao National Key Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha 410073 China Shenzhen Research Institute The Chinese University of Hong Kong Shenzhen China Department of Computing Platform Alibaba Cloud Computing Company Hangzhou 310011 China

A common way to construct a fault model is injecting the fault into the system and observing the subsequent symptoms, e. g. event logs. However, fault features would vary during the propagation period, and present different symptoms at different stage of the fault propagation process. The exiting detection window based feature extraction methods can only identify the early symptoms of a fault, but fail to detect the latter symptoms and cause false alarms. To solve the problem, we present a fault feature extraction method, called Companion State Tracer (CSTracer), which consists of 3 integrated steps: (1) pre-process logs to remove the unrelated logs;(2) construct a general identifier for the early symptoms of a fault;(3) construct a finite state machine model for the fault to trace the latter symptoms. CSTracer can persistently monitor a fault after the fault has been identified. We have justified the effectiveness of CSTracer in an enterprise cloud system. Compared with the existing, the results show that CSTracer has a better detection accuracy.

关键词： Fault detection

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Hierarchical diagnostic approach for performance problems in cloud computing platforms

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Tongxin Xuebao/Journal on Communications 2011年第7期32卷 114-124页

作者： Mi, Hai-Bo Wang, Huai-Min Cai, Hua Yin, Gang Zhou, Qi Sun, Ting-Tao Zhou, Yang-Fan National Laboratory for Parallel and Distributed Processing National University of Defense Technology Changsha 410073 China Computing Platform Alibaba Cloud Computing Company Hangzhou 310023 China Shenzhen Research Institute Chinese Univ. of Hong Kong Shenzhen 518057 China

A hierarchical diagnosis approach, namely Magnifier, was proposed, which models the execution path graph of a user request as component layer, module layer and function layer, and detects anomalies from higher layer to lower layer separately. Extensive experiments were conducted on the Alibaba cloud computing platform. The results indicate that, under the conditions of large volume of data and high complexity of execution paths, Magnifier can accurately and efficiently locate the prime causes of performance degradation.

关键词： Cloud computing

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A general and scalable solution for heterogeneous workflow invocation and nesting

A general and scalable solution for heterogeneous workflow i...

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Workshop on Workflows in Support of Large-Scale Science, WORKS

作者： Tamas Kukla Tamas Kiss Gabor Terstyanszky Peter Kacsuk Centre for Parallel Computing School of Informatics University of Westminster London UK Laboratory of the Parallel and Distributed Systems Computer and Automation Research Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

Several widely utilized, grid workflow management systems emerged in the last decade. These systems were developed by different scientific communities for various purposes. Enhancing these systems with the capability of invoking and nesting the workflows of other systems within their native workflows makes these communities to be able to carry out cross-organizational experiments and share non-native workflows. The novel solution described in this paper allows the integration of different workflow engines and makes them accessible for workflow systems in order to achieve this goal. The solution is based on an application repository and submitter, which exposes different workflow engines and executes them using the computational resources of the grid. In contrast with other approaches, our solution is scalable in terms of both number of workflows and amount of data, easily extendable in the sense that the integration of a new workflow engine does not require code re-engineering, and general, since it can be adopted by numerous workflow systems.

关键词： Engines Workflow management software Risk management Petri nets parallel processing Informatics Laboratories Concurrent computing Distributed computing Automation

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C++ and Interoperability between Libraries: The GraphBLAS C++ Specification

C++ and Interoperability between Libraries: The GraphBLAS C+...

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2023 IEEE International parallel and Distributed Processing Symposium Workshops, IPDPSW 2023

作者： Brock, Benjamin McMillan, Scott Buluc, Aydin Mattson, Timothy G. Moreira, Jose E. Parallel Computing Lab Intel United States Software Engineering Institute Carnegie Mellon University United States Lawrence Berkeley National Laboratory Computational Research Department United States University of California EECS Department Berkeley United States IBM Thomas J. Watson Research Center United States

ISBN: (纸本)9798350311990

Interoperability between libraries is often hindered by incompatible data formats, which can necessitate creating new copies of data when transferring data back and forth between different libraries. This additional data movement incurs additional runtime costs, particularly for sparse applications, where the costs of data movement often dwarf compute costs. In this paper, we investigate interoperability in the context of the C++ GraphBLAS Specification, where C++ concepts allow GraphBLAS algorithms to accept any matrix type as long as it follows the matrix interface defined in the GraphBLAS matrix concept. We first develop non-owning, lazily evaluated adapted views for a number of external data structures, including two categories of graphs defined in the Northwest Graph Library (NWGraph) and traditional pointer-based CSR data structures. These adapted views fulfill the C++ GraphBLAS matrix concept, allowing them to be used inside GraphBLAS algorithms. We then evaluate the performance of these adapted views across two kernels, matrix reduction and sparse times dense matrix multiplication (SpMM), where the performance achieved using a single generic implementation with these views largely matches the performance achieved operating directly on the original data structures, with a slight performance loss in one case. We then propose a mechanism for automatically discovering the availability of these views, allowing algorithms to directly accept external data structures. We also discuss potential extensions to the C++ GraphBLAS specification that might eliminate the small performance dip observed for one of the views. © 2023 IEEE.

关键词： Data structures

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Exploring the potential of using multiple e-science infrastructures with emerging open standards-based e-health research tools 10

Exploring the potential of using multiple e-science infrastr...

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10th IEEE/ACM International Symposium on Cluster, Cloud, and Grid computing, CCGrid 2010

作者： Riedel, M. Schuller, B. Rambadt, M. Memon, M.S. Memon, A.S. Streit, A. Lippert, Th. Zasada, S.J. Manos, S. Coveney, P.V. Wolf, Felix Kranzlmüller, Dieter Jülich Supercomputing Centre Forschungszentrum Jülich Jülich Germany Department of Chemistry University College London London United Kingdom Laboratory of Parallel Computing German Research School for Simulation Sciences Aachen Germany Ludwig Maximilians University Munich Munich Germany

ISBN: (纸本)9781424469871

E-health makes use of information and communication methods and the latest e-research tools to support the understanding of body functions. E-scientists in this field take already advantage of one single infrastructure to perform computationally-intensive investigations of the human body that tend to consider each of the constituent parts separately without taking into account the multiple important interactions between them. But these important interactions imply an increasing complexity of applications that embrace multiple physical models (i.e. multi-physics) and consider a larger range of scales (i.e. multi-scale) thus creating a steadily growing demand for interoperable infrastructures that allow for new innovative application types of jointly using different infrastructures for one application. But interoperable infrastructures are still not seamlessly provided and we argue that this is due to the absence of a realistically implementable infrastructure interoperability reference model that is based on lessons learned from e-science usage. Therefore, the goal of this paper is to explore the potential of using multiple infrastructures for one scientific goal with a particular focus on e-health. Since e-scientists gain more interest in using multiple infrastructures there is a clear demand for interoperability between them to enable a use with one e-research tool. The paper highlights work in the context of an e-Health bloodflow application while the reference model is applicable to other e-science applications as well. © 2010 IEEE.

关键词： Interoperability

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Extreme scale de novo metagenome assembly

arXiv

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arXiv 2018年

作者： Georganas, Evangelos Egan, Rob Hofmeyr, Steven Goltsman, Eugene Arndt, Bill Tritt, Andrew Buluç, Aydın Oliker, Leonid Yelick, Katherine Parallel Computing Lab Intel Corp Computational Research Division Joint Genome Institute Lawrence Berkeley National Laboratory United States National Energy Research Scientific Computing Center United States

Metagenome assembly is the process of transforming a set of short, overlapping, and potentially erroneous DNA segments from environmental samples into the accurate representation of the underlying microbiomes's genomes. State-of-the-art tools require big shared memory machines and cannot handle contemporary metagenome datasets that exceed Terabytes in size. In this paper, we introduce the MetaHipMer pipeline, a high-quality and high-performance metagenome assembler that employs an iterative de Bruijn graph approach. MetaHipMer leverages a specialized scaffolding algorithm that produces long scaffolds and accommodates the idiosyncrasies of metagenomes. MetaHipMer is end-to-end parallelized using the Unified parallel C language and therefore can run seamlessly on shared and distributed-memory systems. Experimental results show that MetaHipMer matches or outperforms the state-of-the-art tools in terms of accuracy. Moreover, MetaHipMer scales efficiently to large concurrencies and is able to assemble previously intractable grand challenge metagenomes. We demonstrate the unprecedented capability of MetaHipMer by computing the first full assembly of the Twitchell Wetlands dataset, consisting of 7.5 billion reads - size 2.6 TBytes. Copyright © 2018, The Authors. All rights reserved.

关键词： Scaffolds

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High Performance Non-uniform FFT on Modern X86-based Multi-core Systems

High Performance Non-uniform FFT on Modern X86-based Multi-c...

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International Symposium on parallel and Distributed Processing (IPDPS)

作者： Dhiraj D. Kalamkar Joshua D. Trzaskoz Srinivas Sridharan Mikhail Smelyanskiy Daehyun Kim Armando Manduca Yunhong Shu Matt A. Bernstein Bharat Kaul Pradeep Dubey Parallel Computing Lab Intel Labs Bangalore KA India Mayo Clinic Minnesota Rochester MN US Parallel Computing Laboratory INTEL Research Laboratory Santa Clara CA USA Department of Physiology and Biomedical Engineering Mayo Clinic Rochester MN USA Parallel Computing Lab Intel Labs Santa Clara CA USA Department of Radiology Mayo Clinic Rochester MN USA

The Non-Uniform Fast Fourier Transform (NUFFT) is a generalization of FFT to non-equidistant samples. It has many applications which vary from medical imaging to radio astronomy to the numerical solution of partial differential equations. Despite recent advances in speeding up NUFFT on various platforms, its practical applications are still limited, due to its high computational cost, which is significantly dominated by the convolution of a signal between a non-uniform and uniform grids. The computational cost of the NUFFT is particularly detrimental in cases which require fast reconstruction times, such as iterative 3D non-Cartesian MRI reconstruction. We propose novel and highly scalable parallel algorithm for performing NUFFT on x86-based multi-core CPUs. The high performance of our algorithm relies on good SIMD utilization and high parallel efficiency. On convolution, we demonstrate on average 90% SIMD efficiency using SSE, as well up to linear scalability using a quad-socket 40-core Intel(R) Xeon(R) E7-4870 Processors based system. As a result, on dual socket Intel(R) Xeon(R) X5670 based server, our NUFFT implementation is more than 4x faster compared to the best available NUFFT3D implementation, when run on the same hardware. On Intel(R) Xeon(R) E5-2670 processor based server, our NUFFT implementation is 1.5X faster than any published NUFFT implementation today. Such speed improvement opens new usages for NUFFT. For example, iterative multi channel reconstruction of a 240×240×240 image could execute in just over 3 minutes, which is on the same order as contemporary non-iterative (and thus less-accurate) 3D NUFFT-based MRI reconstructions.

关键词： Convolution Kernel Interpolation Magnetic resonance imaging Image reconstruction Hardware Transforms

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Optimal Multi-hop Cellular Architecture for Wireless Communications

Optimal Multi-hop Cellular Architecture for Wireless Communi...

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Conference on Local Computer Networks (LCN)

作者： Y. Hung Tam Hossam S. Hassanein Selim G. Akl Robert Benkoczi Telecommunications Research Laboratory School of Computing Queen''s University Kingston ONT Canada Parallel Computation Group School of Computing Queen''s University Kingston ONT Canada

Multi-hop relaying is an important concept in future generation wireless networks. It can address the inherent problems of limited capacity and coverage in cellular networks. However, most multi-hop relaying architectures are designed based on a small fixed-cell-size and a dense network. In a sparse network, the throughput and call acceptance ratio degrades because distant mobile nodes cannot reach the base station to use the available capacity. In addition, a fixed-cell-size cannot adapt to the dynamic changes of traffic pattern and network topology. In this paper, we propose a novel multi-hop relaying architecture called the adaptive multi-hop cellular architecture (AMC). AMC adapts the cell size to an optimal value that maximizes throughput by taking into account the dynamic changes of network density, traffic patterns, and network topology. To the best of our knowledge, this is the first time that adaptive (or optimal) cell size is accounted for in a multi-hop cellular environment. AMC also achieves the design goals of a good multi-hop relaying architecture. Simulation results show that AMC outperforms a fixed-cell-size multi-hop cellular architecture and a single-hop case in terms of data throughput, and call acceptance ratio

关键词： Wireless communication Relays Throughput Spread spectrum communication Telecommunication traffic Network topology Wireless networks Land mobile radio cellular systems Degradation Base stations

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Frequency-Domain Learning for Volumetric-Based 3d Data Perception

SSRN

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SSRN 2023年

作者： Yu, Zifan You, Suya Ren, Fengbo Parallel Systems and Computing Laboratory Arizona State University Tempe85281 United States U.S. DEVCOM Army Research Laboratory Adelphi20782 United States

Frequency-domain learning draws attention due to its superior tradeoff between inference accuracy and the required size of input data. Frequency-domain learning in 2D computer vision tasks has shown that 2D convolutional neural networks (CNN) have a stationary spectral bias towards low-frequency channels so that high-frequency channels can be pruned with no or little accuracy degradation. However, frequency-domain learning has not been studied in the context of 3D CNNs with 3D volumetric data. In this paper, we study frequency-domain learning for volumetric-based 3D data perception tasks, i.e., shape classification and scene semantic segmentation, to reveal the spectral bias and the tradeoff between inference accuracy and the required size of 3D volumetric data for 3D CNNs. Our study finds that 3D CNNs are sensitive to a limited number of critical frequency channels, especially low-frequency channels. Experiment results show that frequency-domain learning can significantly reduce the size of volumetric-based 3D inputs (based on spectral bias) while achieving comparable accuracy with conventional spatial-domain learning approaches. Specifically, frequency-domain learning is able to reduce the input data size by 98% in 3D shape classification while limiting the average accuracy drop within 2%, and by 98% in the 3D point cloud semantic segmentation with a 1.48% mean-class accuracy improvement while limiting the mean-class IoU loss within 1.55%. Moreover, by learning from higher-resolution 3D data (i.e., 2x of the original image in the spatial domain), frequency-domain learning improves the mean-class accuracy and mean-class IoU by 3.04% and 0.63%, respectively, while achieving an 87.5% input data size reduction in 3D point cloud semantic segmentation. © 2023, The Authors. All rights reserved.

关键词： Semantics

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An efficient local address generation for the block-cyclic distribution

An efficient local address generation for the block-cyclic d...

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IEEE International Conference on Algorithms and Architectures for parallel Processing (ICAP)

作者： Oh-Young Kwon Tae-Geun Kim Tack-Don Han Sung-Bong Yang Shin-Dug Kim Distributed Computing Laboratory Systems Engineering Research Institute Taejon South Korea Parallel Processing System Laboratory Department of Computer Science Yonsei University Seoul South Korea

ISBN: (纸本)0780342291

In order to generate local addresses for an array section A(l:h:s) with block-cyclic distribution, an efficient compiling method is required. In this paper, two local address generation methods for the block-cyclic distribution are presented. One is a simple local address generation method that is modified from the virtual-block scheme. The other is a linear-time /spl Delta/M table construction method. The array elements of A(l:h:s) to be accessed at run-time build up a family of lines. By using the equation of the lines, a /spl Delta/M table can be generated in O(k) time. Experimental results show that a simple local address generation method has poor performance but a linear-time /spl Delta/M table generation method is faster than other algorithms in /spl Delta/M table generation time and access time for 10,000 array elements.

关键词： Runtime Equations Distributed computing Systems engineering and theory parallel processing Laboratories Computer science parallel languages Upper bound Automata

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