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检索条件"任意字段=Proceedings of the first international symposium on Databases in parallel and distributed systems"

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Fast and Efficient Graph Traversal Algorithm for CPUs: Maximizing Single-Node Efficiency

Fast and Efficient Graph Traversal Algorithm for CPUs: Maxim...

引用

26th IEEE international parallel and distributed Processing symposium (IPDPS) / Workshop on High Performance Data Intensive Computing

作者： Chhugani, Jatin Satish, Nadathur Kim, Changkyu Sewall, Jason Dubey, Pradeep Intel Corp Parallel Comp Lab Santa Clara CA 95051 USA

ISBN: (纸本)9780769546759

Graph-based structures are being increasingly used to model data and relations among data in a number of fields. Graph-based databases are becoming more popular as a means to better represent such data. Graph traversal is a key component in graph algorithms such as reachability and graph matching. Since the scale of data stored and queried in these databases is increasing, it is important to obtain high performing implementations of graph traversal that can efficiently utilize the processing power of modern processors. In this work, we present a scalable Breadth-first Search Traversal algorithm for modern multi-socket, multi-core CPUs. Our algorithm uses lock- and atomic-free operations on a cache-resident structure for arbitrary sized graphs to filter out expensive main memory accesses, and completely and efficiently utilizes all available bandwidth resources. We propose a work distribution approach for multi-socket platforms that ensures load-balancing while keeping cross-socket communication low. We provide a detailed analytical model that accurately projects the performance of our single- and multi-socket traversal algorithms to within 5-10% of obtained performance. Our analytical model serves as a useful tool to analyze performance bottlenecks on modern CPUs. When measured on various synthetic and real-world graphs with a wide range of graph sizes, vertex degrees and graph diameters, our implementation on a dual-socket Intel (R) Xeon (R) X5570 (Intel microarchitecture code name Nehalem) system achieves 1.5X-13.2X performance speedup over the best reported numbers. We achieve around 1 Billion traversed edges per second on a scale-free R-MAT graph with 64M vertices and 2 Billion edges on a dual-socket Nehalem system. Our optimized algorithm is useful as a building block for efficient multi-node implementations and future exascale systems, thereby allowing them to ride the trend of increasing per-node compute and bandwidth resources.

关键词： bandwidth efficient Graph traversal multi-socket single node

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distributed Ranking in Networks with Limited Memory and Communication

Distributed Ranking in Networks with Limited Memory and Comm...

引用

IEEE international symposium on Information Theory

作者： Jung, Kyomin Kim, Bo Young Vojnovic, Milan Korea Adv Inst Sci & Technol Taejon 305701 South Korea Microsoft Res Cambridge England

ISBN: (纸本)9781467325790

We study a basic information ranking problem in networks where each node holds an individual preference over a set of items and the goal for each node is to identify a sorted list of items with the largest aggregate preference. We would like to achieve this with a fully decentralized algorithm that uses a limited per-node memory and limited pair-wise communications. We show how this problem can be reduced to a plurality selection problem where the goal for each node is to identify an item with the largest aggregate ranking score, and show that solving the reduced problem solves the original ranking problem with high probability. Then we introduce a simple and natural plurality selection algorithm for the selection over m > 1 items that uses only log(2) (m) + 1 bits of per-node memory and per pair-wise communication. We prove correctness of the algorithm with high probability as the number of nodes grows large for the case when each node communicates with any other node, and establish tight convergence time bounds. The information ranking problem studied in this paper is a basic ranking problem that arises in various applications such as sorting elements in distributed computing systems, parallel databases, and may as well serve as a model of decentralized inference and opinion formation in distributed environments.

关键词： distributed computer systems

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ARCSM: A distributed feedback control mechanism for security-critical real-time system

ARCSM: A distributed feedback control mechanism for security...

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2012 10th IEEE international symposium on parallel and distributed Processing with Applications, ISPA 2012

作者： Ma, Yue Jiang, Wei Sang, Nan Zhang, Xia School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu 611731 China Informatics and Mathematical Modeling Department Technical University of Denmark DK-2800 Kongens Lyngby Denmark

ISBN: (纸本)9780769547015

Since the real-time systems are becoming increasingly networked, there are some growing critical challenges of security management and risk control. For the unpredicted and especially unsecured environments, such security-critical distributed real-time embedded systems need to enforce security on multiple nodes in order to against the potential threats as well as satisfying the real-time requirements. Unlike the traditional ad hoc static designing approaches, based on feedback theory, this paper proposes an Adaptive Risk Control and Security Management (ARCSM) mechanism for centralized distributed systems. ARCSM has the ability to guarantee the soft real-time and provide as strong security protection as possible. To meet this requirement, the host server is able to refuse to serve for the deadline missed tasks. In each node, a two-level scheduling framework is designed to implement the feedback control twice. In the first feedback, an appropriate initial security level is assigned for new task. At the runtime, the second feedback can dynamically adjust the ready tasks' security level based on runtime status. Considering features of embedded systems, we measured the energy and time costs of cryptographic algorithms and established a method to quantify the security risk. Moreover, the relationship between time and energy costs analyzed in this paper leaves its significance for the future researches. Experimental results demonstrate that our mechanism can be adaptive to the fluctuation of input workloads and has better performance than open-loop schemes. © 2012 IEEE.

关键词： Energy efficiency

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parallel real-time OLAP on multi-core processors 12

Parallel real-time OLAP on multi-core processors

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12th IEEE/ACM international symposium on Cluster, Cloud and Grid Computing, CCGrid 2012

作者： Dehne, Frank Zaboli, Hamdireza School of Computer Science Carleton University Ottawa ON Canada

ISBN: (纸本)9780769546919

One of the most powerful and prominent technologies for knowledge discovery in Decision Support systems is On-line Analytical Processing (OLAP). Most of the traditional OLAP research, and most of the commercial systems, follow the static data cube approach proposed by Gray etal. and materialize all or a subset of the cuboids of the data cube in order to ensure adequate query performance. Practitioners have called for some time for a real-time OLAP approach where the OLAP system gets updated instantaneously as new data arrives and always provides an up-to-date data warehouse for the decision support process. However, a major problem for real-time OLAP are significant performance issues with large scale data warehouses. The aim of our research is to address these problems through the use of efficient parallel computing methods. In this paper, we present a parallel real-time OLAP system for multi-core processors. To our knowledge, this is the first real-time OLAP system that has been parallelized and optimized for contemporary multi-core processors, providing the opportunity for real-time OLAP on large scale data warehouses. Our system allows for multiple insert and multiple query operations (transactions) to be executed in parallel and in real-time. We evaluated our method for a multitude of scenarios (different ratios of insert and query transactions, query transactions with different sizes of results, different system loads, etc.), using the TPC-DS "Decision Support" benchmark data set. The tests demonstrate that our parallel system achieves a significant speedup in transaction response time and a significant increase in transaction throughput. Since hardware performance improvements are currently achieved not by faster processors but by increasing the number of processor cores, our new parallel real-time OLAP method has the potential to enable OLAP systems that are real-time and efficient/feasible for large databases. © 2012 IEEE.

关键词： parallel processing systems

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Agent-based integration of rescue systems for first responders

Agent-based integration of rescue systems for first responde...

引用

10th IEEE Jubilee international symposium on Applied Machine Intelligence and Informatics, SAMI 2012

作者： Balogh, Z. Gatial, E. Habala, O. Hluchý, L. Institute of Informatics Slovak Academy of Sciences Department of Parallel and Distributed Computing Bratislava Slovakia

ISBN: (纸本)9781457701979

Routine operations of emergency first responders are usually well managed. The situation is different for mass casualty emergencies where more people and properties are threatened. In such situations there are no predefined plans in place and mitigation is solved mostly through crisis management. Teams managing such acute accidents are often working in information insufficiency. Timely information exchange between involved agencies, common understanding of data and fast provision of knowledge can save lives and protect properties. Useful information is heterogeneous and is distributed across many organizations in disparate information sources in many formats with different access policies and in varying quality. The information sources range from sensors deployed on incidence sites, publicly available data sources, corporate legacy systems, documents stored on remote locations to human end-users providing information using mobile devices. This article addresses operational challenges of first Responders and complementary challenges in accessing and analyzing information from multiple sources to provide advanced capabilities for command and control in emergency response. Herein we propose to use an agent-based infrastructure for supporting such interoperability. We propose to build the framework amplifying an agent infrastructure developed in scope of the SECRICOM EU integrated project. In this article we focus mainly on the conceptual architecture of such integration framework. © 2012 IEEE.

关键词： Legacy systems

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Big Data Processing in Cloud Computing Environments

Big Data Processing in Cloud Computing Environments

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12th international symposium on Pervasive systems, Algorithms, and Networks (I-SPAN)

作者： Ji, Changqing Li, Yu Qiu, Wenming Awada, Uchechukwu Li, Keqiu Dalian Maritime Univ Coll Informat Sci & Technol Dalian 116026 Peoples R China Dalian Maritime Univ Coll Phys Sci & Technol Dalian 116026 Peoples R China Dalian Univ Technol Sch Comp Sci & Technol Dalian 116024 Peoples R China

ISBN: (纸本)9780769549309

With the rapid growth of emerging applications like social network analysis, semantic Web analysis and bioinformatics network analysis, a variety of data to be processed continues to witness a quick increase. Effective management and analysis of large-scale data poses an interesting but critical challenge. Recently, big data has attracted a lot of attention from academia, industry as well as government. This paper introduces several big data processing technics from system and application aspects. first, from the view of cloud data management and big data processing mechanisms, we present the key issues of big data processing, including cloud computing platform, cloud architecture, cloud database and data storage scheme. Following the MapReduce parallel processing framework, we then introduce MapReduce optimization strategies and applications reported in the literature. Finally, we discuss the open issues and challenges, and deeply explore the research directions in the future on big data processing in cloud computing environments.

关键词： Big Data Cloud Computing Data Management distributed Computing

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An analysis of provisioning and allocation policies for infrastructure-as-a-service clouds 12

An analysis of provisioning and allocation policies for infr...

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12th IEEE/ACM international symposium on Cluster, Cloud and Grid Computing, CCGrid 2012

作者： Villegas, David Antoniou, Athanasios Sadjadi, Seyed Masoud Iosup, Alexandru School of Computing and Information Sciences Florida International University Miami FL United States Parallel and Distributed Systems Group Delft University of Technology Delft Netherlands

ISBN: (纸本)9780769546919

Today, many commercial and private cloud computing providers offer resources for leasing under the infrastructure as a service (IaaS) paradigm. Although an abundance of mechanisms already facilitate the lease and use of single infrastructure resources, to complete multi-job workloads IaaS users still need to select adequate provisioning and allocation policies to instantiate resources and map computational jobs to them. While such policies have been studied in the past, no experimental investigation in the context of clouds currently exists that considers them jointly. In this paper we present a comprehensive and empirical performance-cost analysis of provisioning and allocation policies in IaaS clouds. We first introduce a taxonomy of both types of policies, based on the type of information used in the decision process, and map to this taxonomy eight provisioning and four allocation policies. Then, we analyze the performance and cost of these policies through experimentation in three clouds, including Amazon EC2. We show that policies that dynamically provision and/or allocate resources can achieve better performance and cost. Finally, we also look at the interplay between provisioning and allocation, for which we show preliminary results. © 2012 IEEE.

关键词： Taxonomies

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distributed ranking in networks with limited memory and communication

Distributed ranking in networks with limited memory and comm...

引用

IEEE international symposium on Information Theory

作者： Kyomin Jung Bo Young Kim Milan Vojnovic KAIST Daejeon South Korea Microsoft Research Cambridge UK

ISBN: (纸本)9781467325790

We study a basic information ranking problem in networks where each node holds an individual preference over a set of items and the goal for each node is to identify a sorted list of items with the largest aggregate preference. We would like to achieve this with a fully decentralized algorithm that uses a limited per-node memory and limited pair-wise communications. We show how this problem can be reduced to a plurality selection problem where the goal for each node is to identify an item with the largest aggregate ranking score, and show that solving the reduced problem solves the original ranking problem with high probability. Then we introduce a simple and natural plurality selection algorithm for the selection over m >; 1 items that uses only log 2 (m) + 1 bits of per-node memory and per pair-wise communication. We prove correctness of the algorithm with high probability as the number of nodes grows large for the case when each node communicates with any other node, and establish tight convergence time bounds. The information ranking problem studied in this paper is a basic ranking problem that arises in various applications such as sorting elements in distributed computing systems, parallel databases, and may as well serve as a model of decentralized inference and opinion formation in distributed environments.

关键词： Convergence Aggregates Peer to peer computing Stochastic systems Heuristic algorithms Markov processes Information theory

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Hardware/Software Mechanisms for Protecting an IDS against Algorithmic Complexity Attacks

Hardware/Software Mechanisms for Protecting an IDS against A...

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IEEE international symposium on parallel and distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Govind Sreekar Shenoy Jordi Tubella Antonio Gonz'lez Department of Computer Architecture Universitat Politècnica de Catalunya Barcelona Spain Intel Barcelona Research Center Barcelona Spain

Intrusion Detection systems (IDS) have emerged as one of the most promising ways to secure systems in the network. An IDS like the popular Snort[17] detects attacks on the network using a database of previous attacks. So in order to detect these attack strings in the packet, Snort uses the Aho-Corasick algorithm. This algorithm first constructs a Finite State Machine (FSM) from the attack strings, and subsequently traverses the FSM using bytes from the packet. We observe that there are input bytes that result in a traversal of a series of FSM states (also viewed as pointers). This chain of pointer traversal significantly degrades (22X) the processing time of an input byte. Such a wide variance in the processing time of an input byte can be exploited by an adversary to throttle the IDS. If the IDS is unable to keep pace with the network traffic, the IDS gets disabled. So in the process the network becomes vulnerable. Attacks done in this manner are referred to as algorithmic complexity attacks, and arise due to weaknesses in IDS processing. In this work, we explore defense mechanisms to the above outlined algorithmic complexity attack. Our proposed mechanisms provide over 3X improvement in the worst-case performance.

关键词： Payloads Hardware databases Clocks Optimization Software Complexity theory

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Fast and Efficient Graph Traversal Algorithm for CPUs: Maximizing Single-Node Efficiency

Fast and Efficient Graph Traversal Algorithm for CPUs: Maxim...

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international symposium on parallel and distributed Processing (IPDPS)

作者： Jatin Chhugani Nadathur Satish Changkyu Kim Jason Sewall Pradeep Dubey Parallel Computing Laboratory Intel Corporation USA

Graph-based structures are being increasingly used to model data and relations among data in a number of fields. Graph-based databases are becoming more popular as a means to better represent such data. Graph traversal is a key component in graph algorithms such as reachability and graph matching. Since the scale of data stored and queried in these databases is increasing, it is important to obtain high performing implementations of graph traversal that can efficiently utilize the processing power of modern processors. In this work, we present a scalable Breadth-first Search Traversal algorithm for modern multi-socket, multi-core CPUs. Our algorithm uses lock- and atomic-free operations on a cache-resident structure for arbitrary sized graphs to filter out expensive main memory accesses, and completely and efficiently utilizes all available bandwidth resources. We propose a work distribution approach for multi-socket platforms that ensures load-balancing while keeping cross-socket communication low. We provide a detailed analytical model that accurately projects the performance of our single- and multi-socket traversal algorithms to within 5-10% of obtained performance. Our analytical model serves as a useful tool to analyze performance bottlenecks on modern CPUs. When measured on various synthetic and real-world graphs with a wide range of graph sizes, vertex degrees and graph diameters, our implementation on a dual-socket Intel ® Xeon ® X5570 (Intel microarchitecture code name Nehalem) system achieves 1.5X-13.2X performance speedup over the best reported numbers. We achieve around 1 Billion traversed edges per second on a scale-free R-MAT graph with 64M vertices and 2 Billion edges on a dual-socket Nehalem system. Our optimized algorithm is useful as a building block for efficient multi-node implementations and future exascale systems, thereby allowing them to ride the trend of increasing per-node compute and bandwidth resources.

关键词： Sockets Arrays Bandwidth Instruction sets Partitioning algorithms

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