2,203 research outputs found

    A web-based approach to engineering adaptive collaborative applications

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    Current methods employed to develop collaborative applications have to make decisions and speculate about the environment in which the application will operate within, the network infrastructure that will be used and the device type the application will operate on. These decisions and assumptions about the environment in which collaborative applications were designed to work are not ideal. These methods produce collaborative applications that are characterised as being inflexible, working on homogeneous networks and single platforms, requiring pre-existing knowledge of the data and information types they need to use and having a rigid choice of architecture. On the other hand, future collaborative applications are required to be flexible; to work in highly heterogeneous environments; be adaptable to work on different networks and on a range of device types. This research investigates the role that the Web and its various pervasive technologies along with a component-based Grid middleware can play to address these concerns. The aim is to develop an approach to building adaptive collaborative applications that can operate on heterogeneous and changing environments. This work proposes a four-layer model that developers can use to build adaptive collaborative applications. The four-layer model is populated with Web technologies such as Scalable Vector Graphics (SVG), the Resource Description Framework (RDF), Protocol and RDF Query Language (SPARQL) and Gridkit, a middleware infrastructure, based on the Open Overlays concept. The Middleware layer (the first layer of the four-layer model) addresses network and operating system heterogeneity, the Group Communication layer enables collaboration and data sharing, while the Knowledge Representation layer proposes an interoperable RDF data modelling language and a flexible storage facility with an adaptive architecture for heterogeneous data storage. And finally there is the Presentation and Interaction layer which proposes a framework (Oea) for scalable and adaptive user interfaces. The four layer model has been successfully used to build a collaborative application, called Wildfurt that overcomes challenges facing collaborative applications. This research has demonstrated new applications for cutting-edge Web technologies in the area of building collaborative applications. SVG has been used for developing superior adaptive and scalable user interfaces that can operate on different device types. RDF and RDFS, have also been used to design and model collaborative applications providing a mechanism to define classes and properties and the relationships between them. A flexible and adaptable storage facility that is able to change its architecture based on the surrounding environments and requirements has also been achieved by combining the RDF technology with the Open Overlays middleware, Gridkit

    Energy Measurements of High Performance Computing Systems: From Instrumentation to Analysis

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    Energy efficiency is a major criterion for computing in general and High Performance Computing in particular. When optimizing for energy efficiency, it is essential to measure the underlying metric: energy consumption. To fully leverage energy measurements, their quality needs to be well-understood. To that end, this thesis provides a rigorous evaluation of various energy measurement techniques. I demonstrate how the deliberate selection of instrumentation points, sensors, and analog processing schemes can enhance the temporal and spatial resolution while preserving a well-known accuracy. Further, I evaluate a scalable energy measurement solution for production HPC systems and address its shortcomings. Such high-resolution and large-scale measurements present challenges regarding the management of large volumes of generated metric data. I address these challenges with a scalable infrastructure for collecting, storing, and analyzing metric data. With this infrastructure, I also introduce a novel persistent storage scheme for metric time series data, which allows efficient queries for aggregate timelines. To ensure that it satisfies the demanding requirements for scalable power measurements, I conduct an extensive performance evaluation and describe a productive deployment of the infrastructure. Finally, I describe different approaches and practical examples of analyses based on energy measurement data. In particular, I focus on the combination of energy measurements and application performance traces. However, interweaving fine-grained power recordings and application events requires accurately synchronized timestamps on both sides. To overcome this obstacle, I develop a resilient and automated technique for time synchronization, which utilizes crosscorrelation of a specifically influenced power measurement signal. Ultimately, this careful combination of sophisticated energy measurements and application performance traces yields a detailed insight into application and system energy efficiency at full-scale HPC systems and down to millisecond-range regions.:1 Introduction 2 Background and Related Work 2.1 Basic Concepts of Energy Measurements 2.1.1 Basics of Metrology 2.1.2 Measuring Voltage, Current, and Power 2.1.3 Measurement Signal Conditioning and Analog-to-Digital Conversion 2.2 Power Measurements for Computing Systems 2.2.1 Measuring Compute Nodes using External Power Meters 2.2.2 Custom Solutions for Measuring Compute Node Power 2.2.3 Measurement Solutions of System Integrators 2.2.4 CPU Energy Counters 2.2.5 Using Models to Determine Energy Consumption 2.3 Processing of Power Measurement Data 2.3.1 Time Series Databases 2.3.2 Data Center Monitoring Systems 2.4 Influences on the Energy Consumption of Computing Systems 2.4.1 Processor Power Consumption Breakdown 2.4.2 Energy-Efficient Hardware Configuration 2.5 HPC Performance and Energy Analysis 2.5.1 Performance Analysis Techniques 2.5.2 HPC Performance Analysis Tools 2.5.3 Combining Application and Power Measurements 2.6 Conclusion 3 Evaluating and Improving Energy Measurements 3.1 Description of the Systems Under Test 3.2 Instrumentation Points and Measurement Sensors 3.2.1 Analog Measurement at Voltage Regulators 3.2.2 Instrumentation with Hall Effect Transducers 3.2.3 Modular Instrumentation of DC Consumers 3.2.4 Optimal Wiring for Shunt-Based Measurements 3.2.5 Node-Level Instrumentation for HPC Systems 3.3 Analog Signal Conditioning and Analog-to-Digital Conversion 3.3.1 Signal Amplification 3.3.2 Analog Filtering and Analog-To-Digital Conversion 3.3.3 Integrated Solutions for High-Resolution Measurement 3.4 Accuracy Evaluation and Calibration 3.4.1 Synthetic Workloads for Evaluating Power Measurements 3.4.2 Improving and Evaluating the Accuracy of a Single-Node Measuring System 3.4.3 Absolute Accuracy Evaluation of a Many-Node Measuring System 3.5 Evaluating Temporal Granularity and Energy Correctness 3.5.1 Measurement Signal Bandwidth at Different Instrumentation Points 3.5.2 Retaining Energy Correctness During Digital Processing 3.6 Evaluating CPU Energy Counters 3.6.1 Energy Readouts with RAPL 3.6.2 Methodology 3.6.3 RAPL on Intel Sandy Bridge-EP 3.6.4 RAPL on Intel Haswell-EP and Skylake-SP 3.7 Conclusion 4 A Scalable Infrastructure for Processing Power Measurement Data 4.1 Requirements for Power Measurement Data Processing 4.2 Concepts and Implementation of Measurement Data Management 4.2.1 Message-Based Communication between Agents 4.2.2 Protocols 4.2.3 Application Programming Interfaces 4.2.4 Efficient Metric Time Series Storage and Retrieval 4.2.5 Hierarchical Timeline Aggregation 4.3 Performance Evaluation 4.3.1 Benchmark Hardware Specifications 4.3.2 Throughput in Symmetric Configuration with Replication 4.3.3 Throughput with Many Data Sources and Single Consumers 4.3.4 Temporary Storage in Message Queues 4.3.5 Persistent Metric Time Series Request Performance 4.3.6 Performance Comparison with Contemporary Time Series Storage Solutions 4.3.7 Practical Usage of MetricQ 4.4 Conclusion 5 Energy Efficiency Analysis 5.1 General Energy Efficiency Analysis Scenarios 5.1.1 Live Visualization of Power Measurements 5.1.2 Visualization of Long-Term Measurements 5.1.3 Integration in Application Performance Traces 5.1.4 Graphical Analysis of Application Power Traces 5.2 Correlating Power Measurements with Application Events 5.2.1 Challenges for Time Synchronization of Power Measurements 5.2.2 Reliable Automatic Time Synchronization with Correlation Sequences 5.2.3 Creating a Correlation Signal on a Power Measurement Channel 5.2.4 Processing the Correlation Signal and Measured Power Values 5.2.5 Common Oversampling of the Correlation Signals at Different Rates 5.2.6 Evaluation of Correlation and Time Synchronization 5.3 Use Cases for Application Power Traces 5.3.1 Analyzing Complex Power Anomalies 5.3.2 Quantifying C-State Transitions 5.3.3 Measuring the Dynamic Power Consumption of HPC Applications 5.4 Conclusion 6 Summary and Outloo

    Classification of Dataflow Actors with Satisfiability and Abstract Interpretation

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    International audienceDataflow programming has been used to describe signal processing applications for many years, traditionally with cyclo-static dataflow (CSDF) or synchronous dataflow (SDF) models that restrict expressive power in favor of compile-time analysis and predictability. More recently, dynamic dataflow is being used for the description of multimedia video standards as promoted by the RVC standard (ISO/IEC 23001:4). Dynamic dataflow is not restricted with respect to expressive power, but it does require runtime scheduling in the general case, which may be costly to perform on software. The authors presented in a previous paper a method to automatically classify actors of a dynamic dataflow program within more restrictive dataflow models when possible, along with a method to transform the actors classified as static to improve execution speed by reducing the number of FIFO accesses (Wipliez & Raulet, 2010). This paper presents an extension of the classification method using satisfiability solving, and details the precise semantics used for the abstract interpretation of actors. The extended classification is able to classify more actors than what could previously be achieved

    The review of heterogeneous design frameworks/Platforms for digital systems embedded in FPGAs and SoCs

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    Systems-on-a-chip integrate specialized modules to provide well-defined functionality. In order to guarantee its efficiency, designersare careful to choose high-level electronic components. In particular,FPGAs (field-programmable gate array) have demonstrated theirability to meet the requirements of emerging technology. However,traditional design methods cannot keep up with the speed andefficiency imposed by the embedded systems industry, so severalframeworks have been developed to simplify the design process of anelectronic system, from its modeling to its physical implementation.This paper illustrates some of them and presents a comparative studybetween them. Indeed, we have selected design methods of SoC(ESP4ML and HLS4ML, OpenESP, LiteX, RubyRTL, PyMTL,SysPy, PyRTL, DSSoC) and NoC networks on OCN chip (PyOCN)and in general on FPGA (PRGA, OpenFPGA, AnyHLS, PYNQ, andPyLog).The objective of this article is to analyze each tool at several levelsand to discuss the benefit of each in the scientific community. Wewill analyze several aspects constituting the architecture and thestructure of the platforms to make a comparative study of thehardware and software design flows of digital systems.

    Collaborative Verification-Driven Engineering of Hybrid Systems

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    Hybrid systems with both discrete and continuous dynamics are an important model for real-world cyber-physical systems. The key challenge is to ensure their correct functioning w.r.t. safety requirements. Promising techniques to ensure safety seem to be model-driven engineering to develop hybrid systems in a well-defined and traceable manner, and formal verification to prove their correctness. Their combination forms the vision of verification-driven engineering. Often, hybrid systems are rather complex in that they require expertise from many domains (e.g., robotics, control systems, computer science, software engineering, and mechanical engineering). Moreover, despite the remarkable progress in automating formal verification of hybrid systems, the construction of proofs of complex systems often requires nontrivial human guidance, since hybrid systems verification tools solve undecidable problems. It is, thus, not uncommon for development and verification teams to consist of many players with diverse expertise. This paper introduces a verification-driven engineering toolset that extends our previous work on hybrid and arithmetic verification with tools for (i) graphical (UML) and textual modeling of hybrid systems, (ii) exchanging and comparing models and proofs, and (iii) managing verification tasks. This toolset makes it easier to tackle large-scale verification tasks

    SMART: A Single-Cycle Reconfigurable NoC for SoC Applications

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    As technology scales, SoCs are increasing in core counts, leading to the need for scalable NoCs to interconnect the multiple cores on the chip. Given aggressive SoC design targets, NoCs have to deliver low latency, high bandwidth, at low power and area overheads. In this paper, we propose Single-cycle Multi-hop Asynchronous Repeated Traversal (SMART) NoC, a NoC that reconfigures and tailors a generic mesh topology for SoC applications at runtime. The heart of our SMART NoC is a novel low-swing clockless repeated link circuit embedded within the router crossbars, that allows packets to potentially bypass all the way from source to destination core within a single clock cycle, without being latched at any intermediate router. Our clockless repeater link has been proven in silicon in 45nm SOI. Results show that at 2GHz, we can traverse 8mm within a single cycle, i.e. 8 hops with 1mm cores. We implement the SMART NoC to layout and show that SMART NoC gives 60% latency savings, and 2.2X power savings compared to a baseline mesh NoC.United States. Defense Advanced Research Projects Agency. The Ubiquitous High-Performance Computing Progra
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