High-Throughput Computing on High-Performance Platforms: A Case Study

The computing systems used by LHC experiments has historically consisted of the federation of hundreds to thousands of distributed resources, ranging from small to mid-size resource. In spite of the impressive scale of the existing distributed computing solutions, the federation of small to mid-size resources will be insufficient to meet projected future demands. This paper is a case study of how the ATLAS experiment has embraced Titan---a DOE leadership facility in conjunction with traditional distributed high- throughput computing to reach sustained production scales of approximately 52M core-hours a years. The three main contributions of this paper are: (i) a critical evaluation of design and operational considerations to support the sustained, scalable and production usage of Titan; (ii) a preliminary characterization of a next generation executor for PanDA to support new workloads and advanced execution modes; and (iii) early lessons for how current and future experimental and observational systems can be integrated with production supercomputers and other platforms in a general and extensible manner

XML Integrated Environment for Service-Oriented Data Management

The proliferation of XML as a family of related standards including a markup language (XML), formatting semantics (XSL style sheets), a linking syntax (XLINK), and appropriate data schema standards have emerged as a de facto standard for encoding and sharing data between various applications. XML is designed to be simple, easily parsed and self-describing. XML is based on and support the idea of separation of concerns: information content is separated from information rendering, and relationships between data elements are provided via simple nesting and references. As the XML content grows, the ability to handle schemaless XML documents becomes more critical as most XML documents do not have schema or Document Type Definitions (DTDs). In addition, XML content and XML tools are often required to be combined in effective ways for better performance and higher flexibility. In this research, we proposed XML Integrated Environment (XIE) which is a general-purpose service-oriented architecture for processing XML documents in a scalable and efficient fashion. The XIE supports a new software service model that provides a proper abstraction to describe a service and divide it into four components: structure, connection, interface and logic. We also proposed and implemented XIE Service Language (XIESL) that can capture the creation and maintenance of the XML processes and the data flow specified by the user and then orchestrates the interactions between different XIE services. Moreover, XIESL manages the complexity of XML processing by implementing an XML processing pipeline that enables better management, control, interpretation and presentation of the XML data even for non-professional users. The XML Integrated Environment is envisioned to revolutionize the way non-professional programmers see, work and manage their XML assets. It offers them powerful tools and constructs to fully utilize the XML processing power embedded in its unified framework and service-oriented architecture

Pervasive brain monitoring and data sharing based on multi-tier distributed computing and linked data technology

EEG-based Brain-computer interfaces (BCI) are facing grant challenges in their real-world applications. The technical difficulties in developing truly wearable multi-modal BCI systems that are capable of making reliable real-time prediction of users’ cognitive states under dynamic real-life situations may appear at times almost insurmountable. Fortunately, recent advances in miniature sensors, wireless communication and distributed computing technologies offered promising ways to bridge these chasms. In this paper, we report our attempt to develop a pervasive on-line BCI system by employing state-of-art technologies such as multi-tier fog and cloud computing, semantic Linked Data search and adaptive prediction/classification models. To verify our approach, we implement a pilot system using wireless dry-electrode EEG headsets and MEMS motion sensors as the front-end devices, Android mobile phones as the personal user interfaces, compact personal computers as the near-end fog servers and the computer clusters hosted by the Taiwan National Center for High-performance Computing (NCHC) as the far-end cloud servers. We succeeded in conducting synchronous multi-modal global data streaming in March and then running a multi-player on-line BCI game in September, 2013. We are currently working with the ARL Translational Neuroscience Branch and the UCSD Movement Disorder Center to use our system in real-life personal stress and in-home Parkinson’s disease patient monitoring experiments. We shall proceed to develop a necessary BCI ontology and add automatic semantic annotation and progressive model refinement capability to our system

Translation Of AADL To PNML To Ensure The Utilization Of Petri Nets

Architecture Analysis and Design Language (AADL), which is used to design and analyze software and hardware architectures of embedded and real-time systems, has proven to be a very efficient way of expressing the non-functional properties of safety-critical systems and architectural modeling. Petri nets are the graphical and mathematical modeling tools used to describe and study information processing systems characterized as concurrent and distributed. As AADL lacks the formal semantics needed to show the functional properties of such systems, the objective of this research was to extend AADL to enable other Petri nets to be incorporated into Petri Net Markup Language (PNML), an interchange language for Petri nets. PNML makes it possible to incorporate different types of analysis using different types of Petri net. To this end, the interchange format Extensible Markup Language (XML) was selected and AADL converted to AADL-XML (the XML format of AADL) and Petri nets to PNML, the XML-format of Petri nets, via XSLT script. PNML was chosen as the transfer format for Petri nets due to its universality, which enables designers to easily map PNML to many different types of Petri nets. Manual conversion of AADL to PNML is error-prone and tedious and thus requires automation, so XSLT script was utilized for the conversion of the two languages in their XML format. Mapping rules were defined for the conversion from AADL to PNML and the translation to XSLT automated. Finally, a PNML plug-in was designed and incorporated into the Open Source AADL Tool Environment (OSATE)

MORPH: A Reference Architecture for Configuration and Behaviour Self-Adaptation

An architectural approach to self-adaptive systems involves runtime change of system configuration (i.e., the system's components, their bindings and operational parameters) and behaviour update (i.e., component orchestration). Thus, dynamic reconfiguration and discrete event control theory are at the heart of architectural adaptation. Although controlling configuration and behaviour at runtime has been discussed and applied to architectural adaptation, architectures for self-adaptive systems often compound these two aspects reducing the potential for adaptability. In this paper we propose a reference architecture that allows for coordinated yet transparent and independent adaptation of system configuration and behaviour

Preparing sparse solvers for exascale computing.

Sparse solvers provide essential functionality for a wide variety of scientific applications. Highly parallel sparse solvers are essential for continuing advances in high-fidelity, multi-physics and multi-scale simulations, especially as we target exascale platforms. This paper describes the challenges, strategies and progress of the US Department of Energy Exascale Computing project towards providing sparse solvers for exascale computing platforms. We address the demands of systems with thousands of high-performance node devices where exposing concurrency, hiding latency and creating alternative algorithms become essential. The efforts described here are works in progress, highlighting current success and upcoming challenges. This article is part of a discussion meeting issue 'Numerical algorithms for high-performance computational science'