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检索条件"任意字段=22nd ACM International Symposium on High-Performance Parallel and Distributed Computing, HPDC 2013"

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Efficient detection of dangling pointer error for C/C++ programs 2

Efficient detection of dangling pointer error for C/C++ prog...

引用

2nd Annual international Conference on Information System and Artificial Intelligence, ISAI 2017

作者： Zhang, Wenzhe Science and Technology on Parallel and Distributed Laboratory State Key Laboratory of High Performance Computing State Key Laboratory of High-end Server and Storage Technology College of Computer National University of Defense Technology Changsha China

Dangling pointer error is pervasive in C/C++ programs and it is very hard to detect. This paper introduces an efficient detector to detect dangling pointer error in C/C++ programs. By selectively leave some memory accesses unmonitored, our method could reduce the memory monitoring overhead and thus achieves better performance over previous methods. Experiments show that our method could achieve an average speed up of 9% over previous compiler instrumentation based method and more than 50% over previous page protection based method. © Published under licence by IOP Publishing Ltd.

关键词： Errors

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ACIC: automatic cloud I/O configurator for parallel applications 13

ACIC: automatic cloud I/O configurator for parallel applicat...

引用

Proceedings of the 22nd international symposium on high-performance parallel and distributed computing

作者： Mingliang Liu Ye Jin Jidong Zhai Yan Zhai Qianqian Shi Xiaosong Ma Wenguang Chen Tsinghua University Beijing China NCSU Raleigh NC USA UW-Madison Madison WI USA

ISBN: (纸本)9781450319102

To tackle the highlighted I/O bottleneck problem in cloud, we proposes ACIC, a system which automatically searches for optimized I/O system configurations from many candidates for each individual application running on a given cloud platform. The top ACIC-recommended configuration improves the applications? performance by a factor of up to 10.5 (3.0 on average), and cost saving of up to 89% (53% on average), compared with a commonly used baseline.

关键词： performance cloud computing storage modeling

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Orthrus: a framework for implementing high-performance collective I/O in the multicore clusters 13

Orthrus: a framework for implementing high-performance colle...

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Proceedings of the 22nd international symposium on high-performance parallel and distributed computing

作者： Xuechen Zhang Jianqiang Ou Kei Davis Song Jiang Georgia Institute of Technology Atlanta GA USA Wayne State University Detroit MI USA Los Alamos National Laboratory Los Alamos NM USA

ISBN: (纸本)9781450319102

This paper presents a framework, Orthrus, that can accommodate multiple collective-I/O implementations, each optimized for some performance aspects, and dynamically select the best performing one accordingly to current workload and system performance bottleneck. We have implemented Orthrus in the ROMIO library. Our experimental results with representative MPI-IO benchmarks show that Orthrus can significantly improve the performance of collective I/O under various workloads and system scenarios.

关键词： parallel I/O parallel file systems collective I/O

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IBIS: interposed big-data I/O scheduler 13

IBIS: interposed big-data I/O scheduler

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Proceedings of the 22nd international symposium on high-performance parallel and distributed computing

作者： Yiqi Xu Adrian Suarez Ming Zhao Florida International University Miami FL USA

ISBN: (纸本)9781450319102

Existing big-data systems (e.g., Hadoop/MapReduce) do not expose management of shared storage I/O resources. As such, application's performance may degrade in unpredictable ways under I/O contention, even with fair sharing of computing resources. This paper proposes \emph{IBIS}, a new Interposed Big-data I/O Scheduler, to provide performance differentiation for competing applications' I/Os in a shared MapReduce-type big-data system. IBIS is implemented in Hadoop by interposing HDFS I/Os and use an SFQ-based proportional-sharing algorithm. Experiments show that the IBIS provides strong performance isolation for one application against another highly I/O-intensive application. IBIS also enforces good proportional sharing of the global bandwidth among competing parallel applications, by coordinating distributed IBIS schedulers to deal with the uneven distribution of local services in big-data systems.

关键词： proportional sharing

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Supporting parallel soft real-time applications in virtualized environment 13

Supporting parallel soft real-time applications in virtualiz...

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Proceedings of the 22nd international symposium on high-performance parallel and distributed computing

作者： Like Zhou Song Wu Huahua Sun Hai Jin Xuanhua Shi Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781450319102

The prevalence of multicore processors and virtualization technology enables parallel soft real-time applications to run in virtualized environment. However, current hypervisors do not provide adequate support for them because of soft real-time constraints and synchronization problems, which result in frequent deadline misses and serious performance degradation. In this paper, we propose a novel parallel soft real-time scheduling algorithm which addresses them well, and implement a parallel soft real-time scheduler, named Poris, based on Xen. Our evaluation shows that Poris shortens the execution time of PARSEC benchmark by up to 44.12% compared to Credit scheduler.

关键词： virtualization soft real-time scheduling parallel

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Scalanytics: a declarative multi-core platform for scalable composable traffic analytics 13

Scalanytics: a declarative multi-core platform for scalable ...

引用

Proceedings of the 22nd international symposium on high-performance parallel and distributed computing

作者： Harjot Gill Dong Lin Xianglong Han Cam Nguyen Tanveer Gill Boon Thau Loo University of Pennsylvania Philadelphia PA USA

ISBN: (纸本)9781450319102

This paper presents SCALANYTICS, a declarative platform that supports high-performance application layer analysis of network traffic. SCALANYTICS uses (1) stateful network packet processing techniques for extracting application-layer data from network packets, (2) a declarative rule-based language called ANALOG for compactly specifying analysis pipelines from reusable modules, and (3) a task-stealing architecture for processing network packets at high throughput within these pipelines, by leveraging multi-core processing capabilities in a load-balanced manner without the need for explicit performance profiling. We have developed a prototype of SCALANYTICS that enhances a declarative networking engine with support for ANALOG and various stateful components, integrated with a parallel task-stealing execution model. We evaluate our SCALANYTICS prototype on a wide range of pipelines for analyzing SMTP and SIP traffic, and for detecting malicious traffic flows. Our evaluation on a 16-core machine demonstrate that SCALANYTICS achieves up to 11.4× improvement in throughput compared with the best uniprocessor implementation. Moreover, SCALANYTICS outperforms the Bro intrusion detection system by an order of magnitude when used for analyzing SMTP traffic.

关键词： programming languages and environments data-intensive computing applications of parallel and distributed computing

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Load balancing in large-scale epidemiological simulations 13

Load balancing in large-scale epidemiological simulations

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Proceedings of the 22nd international symposium on high-performance parallel and distributed computing

作者： Tariq Kamal Keith R. Bisset Ali R. Butt Youngyun Chungbaek Madhav Marathe Virginia Tech Blacksburg VA USA

ISBN: (纸本)9781450319102

Despite the recent advancements in graph partitioning techniques and algorithms, achieving static load balancing in agent-based epidemiological applications is challenging. Input to these simulations is a large agent-location bipartite graph that is highly complex and non-uniform. In this paper, we compare several static load distribution schemes, including our custom strategies, for partitioning a class of bipartite graphs. Computations over such graphs happen between classes of nodes in phases. Our performance evaluations on a 768 core system show that our lower-overhead custom load balancing strategy achieves a 2-fold increase in strong scaling performance compared to the default Round Robin data distribution.

关键词： distributed systems epidemiological simulations load balancing

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MTC envelope: defining the capability of large scale computers in the context of parallel scripting applications 13

MTC envelope: defining the capability of large scale compute...

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Proceedings of the 22nd international symposium on high-performance parallel and distributed computing

作者： Zhao Zhang Daniel S. Katz Michael Wilde Justin M. Wozniak Ian Foster University of Chicago Chicago IL USA University of Chicago & Argonne National Laboratory Chicago IL USA Argonne National Laboratory Argonne IL USA

ISBN: (纸本)9781450319102

Many scientific applications can be efficiently expressed with the parallel scripting (many-task computing, MTC) paradigm. These applications are typically composed of several stages of computation, with tasks in different stages coupled by a shared file system abstraction. However, we often see poor performance when running these applications on large scale computers due to the applications' frequency and volume of filesystem I/O and the absence of appropriate optimizations in the context of parallel scripting applications. In this paper, we show the capability of existing large scale computers to run parallel scripting applications by first defining the MTC envelope and then evaluating the envelope by benchmarking a suite of shared filesystem performance metrics. We also seek to determine the origin of the performance bottleneck by profiling the parallel scripting applications' I/O behavior and mapping the I/O operations to the MTC envelope. We show an example shared filesystem envelope and present a method to predict the I/O performance given the applications' level of I/O concurrency and I/O amount. This work is instrumental in guiding the development of parallel scripting applications to make efficient use of existing large scale computers, and to evaluate performance improvements in the hardware/software stack that will better facilitate parallel scripting applications.

关键词： parallel scripting application MTC distributed file system performance measurements

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ElastMan: autonomic elasticity manager for cloud-based key-value stores 13

ElastMan: autonomic elasticity manager for cloud-based key-v...

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Proceedings of the 22nd international symposium on high-performance parallel and distributed computing

作者： Ahmad Al-Shishtawy Vladimir Vlassov KTH Royal Institute of Technology Stockholm Sweden

ISBN: (纸本)9781450319102

The increasing spread of elastic Cloud services, together with the pay-as-you-go pricing model of Cloud computing, has led to the need of an elasticity controller. The controller automatically resizes an elastic service in response to changes in workload, in order to meet Service Level Objectives (SLOs) at a reduced cost. However, variable performance of Cloud virtual machines and nonlinearities in Cloud services complicates the controller design. We present the design and evaluation of ElastMan, an elasticity controller for Cloud-based elastic key-value stores. ElastMan combines feedforward and feedback control. Feedforward control is used to respond to spikes in the workload by quickly resizing the service to meet SLOs at a minimal cost. Feedback control is used to correct modeling errors and to handle diurnal workload. We have implemented and evaluated ElastMan using the Voldemort key-value store running in a Cloud environment based on OpenStack. Our evaluation shows the feasibility and effectiveness of our approach to automation of Cloud service elasticity.

关键词： key-value store elasticity controller cloud computing

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AI-Ckpt: leveraging memory access patterns for adaptive asynchronous incremental checkpointing 13

AI-Ckpt: leveraging memory access patterns for adaptive asyn...

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Proceedings of the 22nd international symposium on high-performance parallel and distributed computing

作者： Bogdan Nicolae Franck Cappello IBM Research Dublin Ireland INRIA Orsay France

ISBN: (纸本)9781450319102

With increasing scale and complexity of supercomputing and cloud computing architectures, faults are becoming a frequent occurrence, which makes reliability a difficult challenge. Although for some applications it is enough to restart failed tasks, there is a large class of applications where tasks run for a long time or are tightly coupled, thus making a restart from scratch unfeasible. Checkpoint-Restart (CR), the main method to survive failures for such applications faces additional challenges in this context: not only does it need to minimize the performance overhead on the application due to checkpointing, but it also needs to operate with scarce resources. Given the iterative nature of the targeted applications, we launch the assumption that first-time writes to memory during asynchronous checkpointing generate the same kind of interference as they did in past iterations. Based on this assumption, we propose novel asynchronous checkpointing approach that leverages both current and past access pattern trends in order to optimize the order in which memory pages are flushed to stable storage. Large scale experiments show up to 60% improvement when compared to state-of-art checkpointing approaches, all this achievable with an extra memory requirement of less than 5% of the total application memory.

关键词： cloud computing fault tolerance high performance computing reliability asynchronous checkpointing checkpoint restart access pattern adaptation scientific computing

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