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Optimizing CDN Infrastructure for Live Streaming with Constrained Server Chaining

Optimizing CDN Infrastructure for Live Streaming with Constr...

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international symposium on parallel and distributed Processing with Applications, ISPA

作者： Zhenyun Zhuang Chun Guo College of Computing Georgia Institute of Technology Atlanta GA USA Ying-Da-Ji Technol. Shenzhen China

Content Delivery Networks (CDNs) are increasingly being used to deliver live streaming on today's Internet. The new application type of live streaming exposes unique characteristics and challenges that require more advanced design of CDN infrastructure. Unlike traditional web-object delivering, which allows CDN content servers to cache contents and thus typically only involves certain CDN servers (e.g. edge content servers) for delivering contents, live streaming requires a real-time full CDN streaming path that spans across the streaming source, the CDN ingest server, the CDN content server, and end-viewers. Though the ingest server is typically fixed for a particular live stream, appropriate content servers need to be selected for delivering the stream to end viewers. Though today's CDNs typically employ layered infrastructure for delivering live streaming, in this work, we propose a flat-layered design which is referred to as Constrained Server Chaining (CSC) for selecting optimal content servers to deliver live streams. Rather than employing a strictly layered infrastructure, CSC allows CDN streaming servers to dynamically choose upstream servers, thus saves transit cost for CDN providers.

关键词： Servers Engines Monitoring Measurement Media Prototypes

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A Software-Pipelined Approach to Multicore Execution of Timing Predictable Multi-threaded Hard Real-Time Tasks

A Software-Pipelined Approach to Multicore Execution of Timi...

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international symposium on Object-Oriented Real-Time distributed computing

作者： Marco Paolieri Eduardo Quiñones Francisco J. Cazorla Julian Wolf Theo Ungerer Sascha Uhrig Zlatko Petrov Universitat Politecnica de Catalunya Spain Barcelona Supercomputing Center (BSC) Spain Spanish National Research Council (IIIA-CSIC) Spain University of Augsburg Germany Germany Technical University Dortmund Germany Germany Honeywell International Inc. Czech Republic Honeywell International s.r.o. Czech Republic

Multicore processors can deliver higher performance than single-core processors by exploiting thread level parallelism (TLP): applications are split into independent threads, each of which is mapped into a different core, reducing the execution time and potentially its worst-case execution time (WCET). Unfortunately, inter-thread interferences generated by simultaneous accesses to shared resources from different threads may completely destroy the performance benefits brought by TLP. This paper proposes a software/hardware cache partitioning approach that reduces the inter-thread memory interferences generated in hard real-time software-pipelined parallel applications. Our results show that our approach effectively reduces memory interferences, while still guaranteeing a predictable timing behaviour, achieving a WCET estimation reduction of 28% for a software pipelined version of the LU decomposition application with respect to the single-threaded version.

关键词： Instruction sets Multicore processing Pipeline processing Estimation Real time systems

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Evaluating In-Clique and Topological parallelism Strategies for Junction Tree-Based Bayesian Network Inference Algorithm on the Cray XMT

Evaluating In-Clique and Topological Parallelism Strategies ...

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

作者： George Chin Jr. Sutanay Choudhury Lars Kangas Sally McFarlane Andres Marquez Pacific Northwest National Laboratory Richland Washington USA

Long viewed as a strong statistical inference technique, Bayesian networks have emerged as an important class of applications for high-performance computing. We have applied an architecture-conscious approach to parallelizing the Lauritzen-Spiegelhalter Junction Tree algorithm for exact inferencing of Bayesian networks. In optimizing the Junction Tree algorithm, we have implemented both in-clique and topological parallelism strategies to best leverage the fine-grained synchronization and massive-scale multithreading of the Cray XMT architecture. Two topological techniques were developed to parallelize the evidence propagation process through the Bayesian network. The first technique involves performing intelligent scheduling of junction tree nodes based on the tree's topology and the relative sizes of nodes. The second technique involves decomposing the junction tree into a finer state graph representation to offer many more opportunities for parallelism. We evaluate these optimizations on five different Bayesian networks and report our findings and observations. From this development and evaluation, we demonstrate the application of massive-scale multithreading for load balancing and use of implicit parallelism-based compiler optimizations for designing scalable inferencing algorithms.

关键词： Junctions parallel processing Inference algorithms Algorithm design and analysis Bayesian methods Instruction sets Particle separators

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Reducing Fragmentation on Torus-Connected Supercomputers

Reducing Fragmentation on Torus-Connected Supercomputers

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international symposium on parallel and distributed Processing (IPDPS)

作者： Wei Tang Zhiling Lan Narayan Desai Daniel Buettner Yongen Yu Department of Computer Science Illinois Institute of Technology Chicago IL USA Mathematics and Computer Science Division Argonne National Laboratory Argonne IL USA Argonne Leadership Computing Facility Argonne National Laboratory Argonne IL USA

Torus-based networks are prevalent on leadership-class petascale systems, providing a good balance between network cost and performance. The major disadvantage of this network architecture is its susceptibility to fragmentation. Many studies have attempted to reduce resource fragmentation in this architecture. Although the approaches suggested can make good allocation decisions reducing fragmentation at job start time, none of them considers a job's wall time, which can cause resource fragmentation when neighboring jobs do not complete closely. In this paper, we propose a wall time-aware job allocation strategy, which adjacently packs jobs that finish around the same time, in order to minimize resource fragmentation caused by job length, discrepancy. Event-driven simulations using real job traces from a production Blue Gene/P system at Argonne National Laboratory demonstrate that our wall time-aware strategy can effectively reduce system fragmentation and improve overall system performance.

关键词： Resource management Cobalt Scheduling Partitioning algorithms Laboratories Three dimensional displays Runtime

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A (Radical) Proposal Addressing the Non-scalability of the Irregular MPI Collective Interfaces

A (Radical) Proposal Addressing the Non-scalability of the I...

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

作者： Jesper Larsson Traff Department of Scientific Computing Faculty of Computer Science University of Technology Vienna Vienna Austria

In both the regular and the irregular MPI collectives there is a correspondence between the argument lists and certain MPI derived datatypes. As a means to address and alleviate well-known memory and performance scalability problems in the irregular (or vector) collective interface definitions of MPI we propose to push this correspondence to its natural limit, and replace the interfaces of the MPI collectives with a new set of interfaces that specify all data sizes and displacements solely by means of derived datatypes. This reduces the number of collective (communication and reduction) interfaces from 16 to 10 (in the extreme to only 7), significantly generalizes the operations, unifies regular and irregular collective interfaces, makes it possible to decouple certain algorithmic decisions from the collective operation, and moves the interface scalability issue from the collective interfaces to the MPI derived datatypes. To complete the proposal we discuss the memory scalability of the derived datatypes and suggest a number of new datatypes for MPI, some of which may be of independent interest. Finally, we introduce additional, new functionality for scalable construction of datatypes as needed for the new collective interfaces. We give examples throughout of the benefits of this alternative set of collective interfaces. It is argued that an implementation can straightforwardly be undertaken within any reasonable MPI implementation.

关键词： Scalability Proposals Layout Tiles Indexes Semantics Limiting

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Achieving Target MTTF by Duplicating Reliability-Critical Components in High Performance computing Systems

Achieving Target MTTF by Duplicating Reliability-Critical Co...

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

作者： Nithin Nakka Alok Choudhary Gary Grider John Bent James Nunez Satsangat Khalsa Coordinated Science Laboratory University of Illinois Urbana-Champaign Urbana IL USA Department of Electrical Engineering and Computer Science Northwestern University Evanston IL USA Los Alamos National Laboratories Albuquerque NM USA

Mean Time To failure, MTTF, is a commonly accepted metric for reliability. In this paper we present a novel approach to achieve the desired MTTF with minimum redundancy. We analyze the failure behavior of large scale systems using failure logs collected by Los Alamos National Laboratory. We analyze the root cause of failures and present a choice of specific hardware and software components to be made fault-tolerant, through duplication, to achieve target MTTF at minimum expense. Not all components show similar failure behavior in the systems. Our objective, therefore, was to arrive at an ordering of components to be incrementally selected for protection to achieve a target MTTF. We propose a model for MTTF for tolerating failures in a specific component, system-wide, and order components according to the coverage provided. Systems grouped based on hardware configuration showed similar improvements in MTTF when different components in them were targeted for fault-tolerance.

关键词： Fault tolerant systems Maintenance engineering Hardware Redundancy Software

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Accelerating DFA Construction by Hierarchical Merging

Accelerating DFA Construction by Hierarchical Merging

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international symposium on parallel and distributed Processing with Applications, ISPA

作者： Yanbing Liu Li Guo Muyi Guo Ping Liu Chinese Academy and Sciences Beijing China Institute of Computing Technology Chinese Academy and Sciences Beijing China Chinese Academy of Sciences Beijing Beijing CN

Regular expression matching is widely used in many network applications to analyze suspicious traffic against predefined signatures, and to discover anomalous events. Deterministic Finite Automaton (DFA), which recognizes a set of regular expressions, is the basic data structure to scan input traffic byte by byte. Though DFA meets the requirement of real-time processing of network traffic, constructing a combined DFA for a set of regular expression signatures is very time-consuming, especially when the signature set is large. To attack this problem, we propose new strategies to accelerate DFA construction. The basic idea of our method is to construct the combined DFA by hierarchical merging of the DFAs of each single regular expression. Our method runs in O(|Q||Σ| In n) time, which is substantially superior to the time complexity O(|Q||Σ|(Σ i=1 n |Qi|) 2 ) of classical subset construction algorithm. Experiment on real signatures from open-source systems, such as L7-filter, BRO and SNORT, demonstrates that our method performs 45 times faster than the subset construction algorithm on average.

关键词： Doped fiber amplifiers Complexity theory Merging Open source software Data structures Acceleration Automata

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A Framework for Elastic Execution of Existing MPI Programs

A Framework for Elastic Execution of Existing MPI Programs

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

作者： Aarthi Raveendran Tekin Bicer Gagan Agrawal Department of Computer Science and Engineering Ohio State Uinversity USA

There is a clear trend towards using cloud resources in the scientific or the HPC community, with a key attraction of cloud being the elasticity it offers. In executing HPC applications on a cloud environment, it will clearly be desirable to exploit elasticity of cloud environments, and increase or decrease the number of instances an application is executed on during the execution of the application, to meet time and/or cost constraints. Unfortunately, HPC applications have almost always been designed to use a fixed number of resources. This paper describes our initial work towards the goal of making existing MPI applications elastic for a cloud framework. Considering the limitations of the MPI implementations currently available, we support adaptation by terminating one execution and restarting a new program on a different number of instances. The components of our envisioned system include a decision layer which considers time and cost constraints, a framework for modifying MPI programs, and a cloud-based runtime support that can enable redistributing of saved data, and support automated resource allocation and application restart on a different number of nodes. Using two MPI applications, we demonstrate the feasibility of our approach, and show that outputting, redistributing, and reading back data can be a reasonable approach for making existing MPI applications elastic.

关键词： Monitoring Elasticity Runtime Resource management Arrays Cloud computing

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Leveraging Social Networks to Combat Collusion in Reputation Systems for Peer-to-Peer Networks

Leveraging Social Networks to Combat Collusion in Reputation...

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international symposium on parallel and distributed Processing (IPDPS)

作者： Ze Li Haiying Shen Karan Sapra Department of Electrical and Computer Engineering Clemson University Clemson SC USA

In peer-to-peer networks (P2Ps), many autonomous peers without preexisting trust relationships share resources with each other. Due to their open environment, the P2Ps usually employ reputation systems to provide guidance in selecting trustworthy resource providers for high reliability and security. However, node collusion impairs the effectiveness of reputation systems in trustworthy node selection. Although some reputation systems have certain mechanisms to counter collusion, the effectiveness of the mechanisms is not sufficiently high. In this paper, we leverage social networks to enhance the capability of reputation systems in combating collusion. We first analyzed real trace of the reputation system in the Overstock online auction platform which incorporates a social network. The analysis reveals the important impact of the social network on user purchasing and reputation rating patterns. We thus identified suspicious collusion behavior patterns and propose a social network based mechanism, namely Social Trust, to counter collusion. Social Trust adaptively adjusts the weight of ratings based on the social distance and interest relationship between peers. Experimental results show that Social Trust can significantly strengthen the capability of current reputation systems in combating collusion.

关键词： Peer to peer computing Social network services Business Reliability Servers Communities Silicon

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Automatic Library Generation for BLAS3 on GPUs

Automatic Library Generation for BLAS3 on GPUs

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international symposium on parallel and distributed Processing (IPDPS)

作者： Huimin Cui Lei Wang Jingling Xue Yang Yang Xiaobing Feng Chinese Academy and Sciences China Chinese Academy of Sciences Beijing Beijing CN School of Computer Science and Engineering University of New South Wales Australia Institute of Computing Technology Chinese Academy and Sciences China

High-performance libraries, the performance-critical building blocks for high-level applications, will assume greater importance on modern processors as they become more complex and diverse. However, automatic library generators are still immature, forcing library developers to manually tune library to meet their performance objectives. We are developing a new script-controlled compilation framework to help domain experts reduce much of the tedious and error-prone nature of manual tuning, by enabling them to leverage their expertise and reuse past optimization experiences. We focus on demonstrating improved performance and productivity obtained through using our framework to tune BLAS3 routines on three GPU platforms: up to 5.4x speedups over the CUBLAS achieved on NVIDIA GeForce 9800, 2.8x on GTX285, and 3.4x on Fermi Tesla C2050. Our results highlight the potential benefits of exploiting domain expertise and the relations between different routines (in terms of their algorithms and data structures).

关键词： Optimization Libraries Tuning Instruction sets Symmetric matrices Graphics processing unit Resource management

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