Introduction to the special issue on high performance computing solutions for complex problems

[No abstract available

Risk-Based Optimal Scheduling for the Predictive Maintenance of Railway Infrastructure

In this thesis a risk-based decision support system to schedule the predictive maintenance activities, is proposed. The model deals with the maintenance planning of a railway infrastructure in which the due-dates are defined via failure risk analysis.The novelty of the approach consists of the risk concept introduction in railway maintenance scheduling, according to ISO 55000 guidelines, thus implying that the maintenance priorities are based on asset criticality, determined taking into account the relevant failure probability, related to asset degradation conditions, and the consequent damages

A high-performance computing framework for Monte Carlo ocean color simulations

This paper presents a high-performance computing (HPC) framework for Monte Carlo (MC) simulations in the ocean color (OC) application domain. The objective is to optimize a parallel MC radiative transfer code named MOX, developed by the authors to create a virtual marine environment for investigating the quality of OC data products derived from in situ measurements of in-water radiometric quantities. A consolidated set of solutions for performance modeling, prediction, and optimization is implemented to enhance the efficiency of MC OC simulations on HPC run-time infrastructures. HPC, machine learning, and adaptive computing techniques are applied taking into account a clear separation and systematic treatment of accuracy and precision requirements for large-scale MC OC simulations. The added value of the work is the integration of computational methods and tools for MC OC simulations in the form of an HPC-oriented problem-solving environment specifically tailored to investigate data acquisition and reduction methods for OC field measurements. Study results highlight the benefit of close collaboration between HPC and application domain researchers to improve the efficiency and flexibility of computer simulations in the marine optics application domain. (C) 2016 The Authors. Concurrency and Computation: Practice and Experience Published by John Wiley & Sons Ltd.Portuguese Foundation for Science and Technology (FCT/MEC) [PEst-OE/EEI/UI0527/2011]; ESA [22576/09/I-OL, ARG/003-025/1406/CIMA]; NOVA LINCS [UID/CEC/04516/2013]info:eu-repo/semantics/publishedVersio

Optimization for process planning and scheduling in parts manufacturing

Ph.DDOCTOR OF PHILOSOPH

Proceedings. 19. Workshop Computational Intelligence, Dortmund, 2. - 4. Dezember 2009

Dieser Tagungsband enthält die Beiträge des 19. Workshops „Computational Intelligence“ des Fachausschusses 5.14 der VDI/VDE-Gesellschaft für Mess- und Automatisierungstechnik (GMA) und der Fachgruppe „Fuzzy-Systeme und Soft-Computing“ der Gesellschaft für Informatik (GI), der vom 2.-4. Dezember 2009 im Haus Bommerholz bei Dortmund stattfindet

Proceedings of the 5th International Workshop on Reconfigurable Communication-centric Systems on Chip 2010 - ReCoSoC\u2710 - May 17-19, 2010 Karlsruhe, Germany. (KIT Scientific Reports ; 7551)

ReCoSoC is intended to be a periodic annual meeting to expose and discuss gathered expertise as well as state of the art research around SoC related topics through plenary invited papers and posters. The workshop aims to provide a prospective view of tomorrow\u27s challenges in the multibillion transistor era, taking into account the emerging techniques and architectures exploring the synergy between flexible on-chip communication and system reconfigurability

Agent-based resource management for grid computing

A computational grid is a hardware and software infrastructure that provides dependable, consistent, pervasive, and inexpensive access to high-end computational capability. An ideal grid environment should provide access to the available resources in a seamless manner. Resource management is an important infrastructural component of a grid computing environment. The overall aim of resource management is to efficiently schedule applications that need to utilise the available resources in the grid environment. Such goals within the high performance community will rely on accurate performance prediction capabilities. An existing toolkit, known as PACE (Performance Analysis and Characterisation Environment), is used to provide quantitative data concerning the performance of sophisticated applications running on high performance resources. In this thesis an ASCI (Accelerated Strategic Computing Initiative) kernel application, Sweep3D, is used to illustrate the PACE performance prediction capabilities. The validation results show that a reasonable accuracy can be obtained, cross-platform comparisons can be easily undertaken, and the process benefits from a rapid evaluation time. While extremely well-suited for managing a locally distributed multi-computer, the PACE functions do not map well onto a wide-area environment, where heterogeneity, multiple administrative domains, and communication irregularities dramatically complicate the job of resource management. Scalability and adaptability are two key challenges that must be addressed. In this thesis, an A4 (Agile Architecture and Autonomous Agents) methodology is introduced for the development of large-scale distributed software systems with highly dynamic behaviours. An agent is considered to be both a service provider and a service requestor. Agents are organised into a hierarchy with service advertisement and discovery capabilities. There are four main performance metrics for an A4 system: service discovery speed, agent system efficiency, workload balancing, and discovery success rate. Coupling the A4 methodology with PACE functions, results in an Agent-based Resource Management System (ARMS), which is implemented for grid computing. The PACE functions supply accurate performance information (e. g. execution time) as input to a local resource scheduler on the fly. At a meta-level, agents advertise their service information and cooperate with each other to discover available resources for grid-enabled applications. A Performance Monitor and Advisor (PMA) is also developed in ARMS to optimise the performance of the agent behaviours. The PMA is capable of performance modelling and simulation about the agents in ARMS and can be used to improve overall system performance. The PMA can monitor agent behaviours in ARMS and reconfigure them with optimised strategies, which include the use of ACTs (Agent Capability Tables), limited service lifetime, limited scope for service advertisement and discovery, agent mobility and service distribution, etc. The main contribution of this work is that it provides a methodology and prototype implementation of a grid Resource Management System (RMS). The system includes a number of original features that cannot be found in existing research solutions

A system’s approach to cache hierarchy-aware decomposition of data-parallel computations

Dissertação para obtenção do Grau de Mestre em Engenharia InformáticaThe architecture of nowadays’ processors is very complex, comprising several computational cores and an intricate hierarchy of cache memories. The latter, in particular, differ considerably between the many processors currently available in the market, resulting in a wide variety of configurations. Application development is typically oblivious of this complexity and diversity, taking only into consideration the number of available execution cores. This oblivion prevents such applications from fully harnessing the computing power available in these architectures. This problem has been recognized by the community, which has proposed languages and models to express and tune applications according to the underlying machine’s hierarchy. These, however, lack the desired abstraction level, forcing the programmer to have deep knowledge of computer architecture and parallel programming, in order to ensure performance portability across a wide range of architectures. Realizing these limitations, the goal of this thesis is to delegate these hierarchy-aware optimizations to the runtime system. Accordingly, the programmer’s responsibilities are confined to the definition of procedures for decomposing an application’s domain, into an arbitrary number of partitions. With this, the programmer has only to reason about the application’s data representation and manipulation. We prototyped our proposal on top of a Java parallel programming framework, and evaluated it from a performance perspective, against cache neglectful domain decompositions. The results demonstrate that our optimizations deliver significant speedups against decomposition strategies based solely on the number of execution cores, without requiring the programmer to reason about the machine’s hardware. These facts allow us to conclude that it is possible to obtain performance gains by transferring hierarchyaware optimizations concerns to the runtime system

The Guardian Council: Parallel programmable hardware security

Systems security is becoming more challenging in the face of untrusted programs and system users. Safeguards against attacks currently in use, such as buffer overflows, control-flow integrity, side channels and malware, are limited. Software protection schemes, while flexible, are often too expensive, and hardware schemes, while fast, are too constrained or out-of-date to be practical. We demonstrate the best of both worlds with the Guardian Council, a novel parallel architecture to enforce a wide range of highly customisable and diverse security policies. We leverage heterogeneity and parallelism in the design of our system to perform security enforcement for a large high-performance core on a set of small microcontroller-sized cores. These Guardian Processing Elements (GPEs) are many orders of magnitude more efficient than conventional out-of-order superscalar processors, bringing high-performance security at very low power and area overheads. Alongside these highly parallel cores we provide fixed-function logging and communication units, and a powerful programming model, as part of an architecture designed for security. Evaluation on a range of existing hardware and software protection mechanisms, reimplemented on the Guardian Council, across the SPEC CPU 2006 benchmarks demonstrates the flexibility of our approach with negligible overheads, out-performing prior work in the literature. For instance, 4 GPEs can provide forward control-flow integrity with 0% overhead, while 6 GPEs can provide a full shadow stack at only 2%.Arm Lt