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Workload Characterization (IISWC), 2012 IEEE International Symposium on

Date 4-6 Nov. 2012

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Displaying Results 1 - 25 of 36
  • [Title pages]

    Publication Year: 2012 , Page(s): 1 - 2
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  • Table of contents

    Publication Year: 2012 , Page(s): 1 - 3
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  • Message from the general chair

    Publication Year: 2012 , Page(s): i
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  • Message from the program chair

    Publication Year: 2012 , Page(s): ii
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  • Committee

    Publication Year: 2012 , Page(s): iii
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  • Reviewers

    Publication Year: 2012 , Page(s): iv
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  • Keynote address: Moving a science workload to exascale computing

    Publication Year: 2012 , Page(s): 1
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (53 KB)  

    Summary form only given. With the huge amount of networked video cameras installed everywhere nowadays, there is an urgent need of embedded intelligence for automated tracking and event understanding of video objects. The scope of intelligent surveillance and analytics systems includes access control, crowd flux statistics analysis, intelligent transportation, abnormal event detection, and automat... View full abstract»

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  • Session 1: Best paper nominees

    Publication Year: 2012 , Page(s): 2
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  • Workload characterization on a production Hadoop cluster: A case study on Taobao

    Publication Year: 2012 , Page(s): 3 - 13
    Cited by:  Papers (11)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (672 KB) |  | HTML iconHTML  

    MapReduce is becoming the state-of-the-art computing paradigm for processing large-scale datasets on a large cluster with tens or thousands of nodes. It has been widely used in various fields such as e-commerce, Web search, social networks, and scientific computation. Understanding the characteristics of MapReduce workloads is the key to achieving better configuration decisions and improving the s... View full abstract»

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  • ECHO: Recreating network traffic maps for datacenters with tens of thousands of servers

    Publication Year: 2012 , Page(s): 14 - 24
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (8291 KB) |  | HTML iconHTML  

    Large-scale datacenters now host a large part of the world's data and computation, which makes their design a crucial architectural challenge. Datacenter (DC) applications, unlike traditional workloads, are dominated by user patterns that only emerge in the large-scale. This creates the need for concise, accurate and scalable analytical models that capture both their temporal and spatial features ... View full abstract»

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  • Wireless Body Area Networks: Where does energy go?

    Publication Year: 2012 , Page(s): 25 - 35
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1533 KB) |  | HTML iconHTML  

    Wireless Body Area Networks (WBANs) promise to revolutionize health care in the near future. By integrating bio-sensors with a mobile phone it is possible to monitor an individual's health and related behaviors. Monitoring is done by analyzing the sensor data either on a mobile phone or on a remote server by relaying this information over a wireless network. However, the “wireless” a... View full abstract»

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  • BenchNN: On the broad potential application scope of hardware neural network accelerators

    Publication Year: 2012 , Page(s): 36 - 45
    Cited by:  Papers (14)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (869 KB) |  | HTML iconHTML  

    Recent technology trends have indicated that, although device sizes will continue to scale as they have in the past, supply voltage scaling has ended. As a result, future chips can no longer rely on simply increasing the operational core count to improve performance without surpassing a reasonable power budget. Alternatively, allocating die area towards accelerators targeting an application, or an... View full abstract»

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  • Session 2: Parallelism

    Publication Year: 2012 , Page(s): 46
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  • Phase behavior in serial and parallel applications

    Publication Year: 2012 , Page(s): 47 - 58
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (497 KB) |  | HTML iconHTML  

    It is well known that most serial programs exhibit time varying behavior, for example, alternating between memory- and compute-bound phases. However, most research into program phase behavior has focused on the serial SPEC benchmark suite, with little investigations into large scale phase behavior in parallel applications. In this study we compare and examine the time-varying behavior of the SPEC2... View full abstract»

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  • Deconstructing the overhead in parallel applications

    Publication Year: 2012 , Page(s): 59 - 68
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (262 KB) |  | HTML iconHTML  

    Performance problems in parallel programs manifest as lack of scalability. These scalability issues are often very difficult to debug. They can stem from synchronization overhead, poor thread scheduling decisions, or contention for hardware resources, such as shared caches. Traditional profiling tools attribute program cycles to different functions, but do not generate immediate insight into issue... View full abstract»

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  • Whole program data dependence profiling to unveil parallel regions in the dynamic execution

    Publication Year: 2012 , Page(s): 69 - 80
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (378 KB) |  | HTML iconHTML  

    As application programs become large and complex year by year, mapping these programs into highly parallelized hardware resources by understanding all of the program structures across an application is becoming harder and harder for programmers. In this paper, we present an advanced technique that can extract dynamic memory dataflow across whole program execution to provide programmers with hints ... View full abstract»

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  • Session 3: Ongoing Research [breaker page]

    Publication Year: 2012 , Page(s): 81
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  • Automatic discovery of performance and energy pitfalls in HTML and CSS

    Publication Year: 2012 , Page(s): 82 - 83
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (93 KB) |  | HTML iconHTML  

    WebChar is a tool for analyzing browsers holistically to discover properties of HTML and CSS that lead to poor performance and high energy consumption. It analyzes a large collection of Web pages to mine a model for their performance based on static attributes of the content. An evaluation on two platforms, a netbook and a smartphone, demonstrates that WebChar can yield actionable conclusions for ... View full abstract»

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  • Characterizing global user download behavior on a large-scale satellite image distribution system

    Publication Year: 2012 , Page(s): 84 - 85
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (129 KB) |  | HTML iconHTML  

    Data explosion in the 21st century has seen the growth of massive online content distribution systems. These incredibly large-scale systems utilize vast datasets to provide a myriad of utilities to users. In order to keep up with the high volume of complex, diverse requests being generated by their users, efficient management of data is of critical importance. However, understanding and categorizi... View full abstract»

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  • Benchmarking ISA reliability to intermittent errors

    Publication Year: 2012 , Page(s): 86 - 87
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (83 KB) |  | HTML iconHTML  

    Silicon scaling has led to accelerated wearout, which results in increased number of intermittent errors. Of the various factors that can lead to intermittent errors, device utilization is a major contributor to wearout. Every device on a chip is activated in response to either control signals or data movement resulting from instruction execution. This research proposes a systematic methodology fo... View full abstract»

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  • Session 4: Workload analysis and benchmark development [breaker page]

    Publication Year: 2012 , Page(s): 88
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  • Using software architectural patterns for synthetic embedded multicore benchmark development

    Publication Year: 2012 , Page(s): 89 - 99
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (1440 KB) |  | HTML iconHTML  

    Benchmarks capture the essence of many important real-world applications and allow performance, and power analysis while developing new systems. Synthetic benchmarks are a miniaturized form of benchmarks that allow high simulation speeds and act as proxies to proprietary applications. Software architecture principles guide the development of new applications and benchmarks. We leverage software ar... View full abstract»

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  • A storage-centric analysis of MapReduce workloads: File popularity, temporal locality and arrival patterns

    Publication Year: 2012 , Page(s): 100 - 109
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (2244 KB) |  | HTML iconHTML  

    A huge increase in data storage and processing requirements has lead to Big Data, for which next generation storage systems are being designed and implemented. However, we have a limited understanding of the workloads of Big Data storage systems. We consider the case of one common type of Big Data storage cluster: a cluster dedicated to supporting a mix of MapReduce jobs. We analyze 6-month traces... View full abstract»

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  • Invited session: Hot workloads [breaker page]

    Publication Year: 2012 , Page(s): 110
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  • Analyzing the Facebook workload

    Publication Year: 2012 , Page(s): 111 - 112
    Save to Project icon | Request Permissions | Click to expandAbstract | PDF file iconPDF (119 KB) |  | HTML iconHTML  

    Understanding the performance of Facebook is challenging for several reasons: massive scale; unique characteristics of the application; a rapidly evolving domain; and complex interactions between a larger number of infrastructure components. This talk will explain these challenges along with our approach to analyze and optimize the overall system. View full abstract»

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