183 research outputs found
High-performance simulation and simulation methodologies
types: Editorial CommentThe realization of high performance simulation necessitates sophisticated simulation experimentation and optimization; this often requires non-trivial amounts of computing power. Distributed computing techniques and systems found in areas such as High Performance Computing (HPC), High Throughput Computing (HTC), e-infrastructures, grid and cloud computing can provide the required computing capacity for the execution of large and complex simulations. This extends the long tradition of adopting advances in distributed computing in simulation as evidenced by contributions from the parallel and distributed simulation community. There has arguably been a recent acceleration of innovation in distributed computing tools and techniques. This special issue presents the opportunity to showcase recent research that is assimilating these new advances in simulation. This special issue brings together a contemporary collection of work showcasing original research in the advancement of simulation theory and practice with distributed computing. This special issue has two parts. The first part (published in the preceding issue of the journal) included seven studies in high performance simulation that support applications including the study of epidemics, social networks, urban mobility and real-time embedded and cyber-physical systems. This second part focuses on original research in high performance simulation that supports a range of methods including DEVS, Petri nets and DES. Of the four papers for this issue, the manuscript by Bergero, et al. (2013), which was submitted, reviewed and accepted for the special issue, was published in an earlier issue of SIMULATION as the author requested early publication.Research Councils U
Towards Exascale Computing Architecture and Its Prototype: Services and Infrastructure
This paper presents the design and implementation of a scalable compute platform for processing large data sets in the scope of the EU H2020 project PROCESS. We are presenting requirements of the platform, related works, infrastructure with focus on the compute components and finally results of our work
Contributions to the efficient use of general purpose coprocessors: kernel density estimation as case study
142 p.The high performance computing landscape is shifting from assemblies of homogeneous nodes towards heterogeneous systems, in which nodes consist of a combination of traditional out-of-order execution cores and accelerator devices. Accelerators provide greater theoretical performance compared to traditional multi-core CPUs, but exploiting their computing power remains as a challenging task.This dissertation discusses the issues that arise when trying to efficiently use general purpose accelerators. As a contribution to aid in this task, we present a thorough survey of performance modeling techniques and tools for general purpose coprocessors. Then we use as case study the statistical technique Kernel Density Estimation (KDE). KDE is a memory bound application that poses several challenges for its adaptation to the accelerator-based model. We present a novel algorithm for the computation of KDE that reduces considerably its computational complexity, called S-KDE. Furthermore, we have carried out two parallel implementations of S-KDE, one for multi and many-core processors, and another one for accelerators. The latter has been implemented in OpenCL in order to make it portable across a wide range of devices. We have evaluated the performance of each implementation of S-KDE in a variety of architectures, trying to highlight the bottlenecks and the limits that the code reaches in each device. Finally, we present an application of our S-KDE algorithm in the field of climatology: a novel methodology for the evaluation of environmental models
CFD Vision 2030 Study: A Path to Revolutionary Computational Aerosciences
This report documents the results of a study to address the long range, strategic planning required by NASA's Revolutionary Computational Aerosciences (RCA) program in the area of computational fluid dynamics (CFD), including future software and hardware requirements for High Performance Computing (HPC). Specifically, the "Vision 2030" CFD study is to provide a knowledge-based forecast of the future computational capabilities required for turbulent, transitional, and reacting flow simulations across a broad Mach number regime, and to lay the foundation for the development of a future framework and/or environment where physics-based, accurate predictions of complex turbulent flows, including flow separation, can be accomplished routinely and efficiently in cooperation with other physics-based simulations to enable multi-physics analysis and design. Specific technical requirements from the aerospace industrial and scientific communities were obtained to determine critical capability gaps, anticipated technical challenges, and impediments to achieving the target CFD capability in 2030. A preliminary development plan and roadmap were created to help focus investments in technology development to help achieve the CFD vision in 2030
Design and Evaluation of Low-Latency Communication Middleware on High Performance Computing Systems
[Resumen]El interés en Java para computación paralela está motivado por sus interesantes
características, tales como su soporte multithread, portabilidad, facilidad de aprendizaje,alta productividad y el aumento significativo en su rendimiento omputacional.
No obstante, las aplicaciones paralelas en Java carecen generalmente de mecanismos
de comunicación eficientes, los cuales utilizan a menudo protocolos basados
en sockets incapaces de obtener el máximo provecho de las redes de baja latencia,
obstaculizando la adopción de Java en computación de altas prestaciones (High Per-
formance Computing, HPC). Esta Tesis Doctoral presenta el diseño, implementación
y evaluación de soluciones de comunicación en Java que superan esta limitación. En
consecuencia, se desarrollaron múltiples dispositivos de comunicación a bajo nivel
para paso de mensajes en Java (Message-Passing in Java, MPJ) que aprovechan al
máximo el hardware de red subyacente mediante operaciones de acceso directo a memoria remota que proporcionan comunicaciones de baja latencia. También se incluye una biblioteca de paso de mensajes en Java totalmente funcional, FastMPJ, en la
cual se integraron los dispositivos de comunicación. La evaluación experimental ha
mostrado que las primitivas de comunicación de FastMPJ son competitivas en comparación con bibliotecas nativas, aumentando significativamente la escalabilidad de
aplicaciones MPJ. Por otro lado, esta Tesis analiza el potencial de la computación en
la nube (cloud computing) para HPC, donde el modelo de distribución de infraestructura
como servicio (Infrastructure as a Service, IaaS) emerge como una alternativa
viable a los sistemas HPC tradicionales. La evaluación del rendimiento de recursos
cloud específicos para HPC del proveedor líder, Amazon EC2, ha puesto de manifiesto el impacto significativo que la virtualización impone en la red, impidiendo
mover las aplicaciones intensivas en comunicaciones a la nube. La clave reside en un soporte de virtualización apropiado, como el acceso directo al hardware de red, junto
con las directrices para la optimización del rendimiento sugeridas en esta Tesis.[Resumo]O interese en Java para computación paralela está motivado polas súas interesantes características, tales como o seu apoio multithread, portabilidade, facilidade de aprendizaxe, alta produtividade e o aumento signi cativo no seu rendemento computacional. No entanto, as aplicacións paralelas en Java carecen xeralmente de mecanismos de comunicación e cientes, os cales adoitan usar protocolos baseados en sockets que son incapaces de obter o máximo proveito das redes de baixa latencia, obstaculizando a adopción de Java na computación de altas prestacións (High
Performance Computing, HPC). Esta Tese de Doutoramento presenta o deseño, implementaci
ón e avaliación de solucións de comunicación en Java que superan esta limitación. En consecuencia, desenvolvéronse múltiples dispositivos de comunicación a baixo nivel para paso de mensaxes en Java (Message-Passing in Java, MPJ) que aproveitan ao máaximo o hardware de rede subxacente mediante operacións de acceso
directo a memoria remota que proporcionan comunicacións de baixa latencia.
Tamén se inclúe unha biblioteca de paso de mensaxes en Java totalmente funcional,
FastMPJ, na cal foron integrados os dispositivos de comunicación. A avaliación experimental amosou que as primitivas de comunicación de FastMPJ son competitivas
en comparación con bibliotecas nativas, aumentando signi cativamente a escalabilidade
de aplicacións MPJ. Por outra banda, esta Tese analiza o potencial da computación na nube (cloud computing) para HPC, onde o modelo de distribución de infraestrutura como servizo (Infrastructure as a Service, IaaS) xorde como unha alternativa viable aos sistemas HPC tradicionais. A ampla avaliación do rendemento de recursos cloud específi cos para HPC do proveedor líder, Amazon EC2, puxo de manifesto o impacto signi ficativo que a virtualización impón na rede, impedindo mover as aplicacións intensivas en comunicacións á nube. A clave atópase no soporte de virtualización apropiado, como o acceso directo ao hardware de rede, xunto coas directrices para a optimización do rendemento suxeridas nesta Tese.[Abstract]The use of Java for parallel computing is becoming more promising owing to
its appealing features, particularly its multithreading support, portability, easy-tolearn properties, high programming productivity and the noticeable improvement in its computational performance. However, parallel Java applications generally su er
from inefficient communication middleware, most of which use socket-based protocols
that are unable to take full advantage of high-speed networks, hindering the
adoption of Java in the High Performance Computing (HPC) area. This PhD Thesis
presents the design, development and evaluation of scalable Java communication
solutions that overcome these constraints. Hence, we have implemented several lowlevel
message-passing devices that fully exploit the underlying network hardware while taking advantage of Remote Direct Memory Access (RDMA) operations to provide low-latency communications. Moreover, we have developed a productionquality Java message-passing middleware, FastMPJ, in which the devices have been integrated seamlessly, thus allowing the productive development of Message-Passing in Java (MPJ) applications. The performance evaluation has shown that FastMPJ communication primitives are competitive with native message-passing libraries, improving signi cantly the scalability of MPJ applications. Furthermore, this Thesis
has analyzed the potential of cloud computing towards spreading the outreach of
HPC, where Infrastructure as a Service (IaaS) o erings have emerged as a feasible
alternative to traditional HPC systems. Several cloud resources from the leading
IaaS provider, Amazon EC2, which speci cally target HPC workloads, have been
thoroughly assessed. The experimental results have shown the signi cant impact
that virtualized environments still have on network performance, which hampers
porting communication-intensive codes to the cloud. The key is the availability of
the proper virtualization support, such as the direct access to the network hardware,
along with the guidelines for performance optimization suggested in this Thesis
Intelligent Computing: The Latest Advances, Challenges and Future
Computing is a critical driving force in the development of human
civilization. In recent years, we have witnessed the emergence of intelligent
computing, a new computing paradigm that is reshaping traditional computing and
promoting digital revolution in the era of big data, artificial intelligence
and internet-of-things with new computing theories, architectures, methods,
systems, and applications. Intelligent computing has greatly broadened the
scope of computing, extending it from traditional computing on data to
increasingly diverse computing paradigms such as perceptual intelligence,
cognitive intelligence, autonomous intelligence, and human-computer fusion
intelligence. Intelligence and computing have undergone paths of different
evolution and development for a long time but have become increasingly
intertwined in recent years: intelligent computing is not only
intelligence-oriented but also intelligence-driven. Such cross-fertilization
has prompted the emergence and rapid advancement of intelligent computing.
Intelligent computing is still in its infancy and an abundance of innovations
in the theories, systems, and applications of intelligent computing are
expected to occur soon. We present the first comprehensive survey of literature
on intelligent computing, covering its theory fundamentals, the technological
fusion of intelligence and computing, important applications, challenges, and
future perspectives. We believe that this survey is highly timely and will
provide a comprehensive reference and cast valuable insights into intelligent
computing for academic and industrial researchers and practitioners
Virtual Organization Clusters: Self-Provisioned Clouds on the Grid
Virtual Organization Clusters (VOCs) provide a novel architecture for overlaying dedicated cluster systems on existing grid infrastructures. VOCs provide customized, homogeneous execution environments on a per-Virtual Organization basis, without the cost of physical cluster construction or the overhead of per-job containers. Administrative access and overlay network capabilities are granted to Virtual Organizations (VOs) that choose to implement VOC technology, while the system remains completely transparent to end users and non-participating VOs. Unlike alternative systems that require explicit leases, VOCs are autonomically self-provisioned according to configurable usage policies. As a grid computing architecture, VOCs are designed to be technology agnostic and are implementable by any combination of software and services that follows the Virtual Organization Cluster Model. As demonstrated through simulation testing and evaluation of an implemented prototype, VOCs are a viable mechanism for increasing end-user job compatibility on grid sites. On existing production grids, where jobs are frequently submitted to a small subset of sites and thus experience high queuing delays relative to average job length, the grid-wide addition of VOCs does not adversely affect mean job sojourn time. By load-balancing jobs among grid sites, VOCs can reduce the total amount of queuing on a grid to a level sufficient to counteract the performance overhead introduced by virtualization
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