There is increasing interest in computing models that support extensibility of systems through code migration. Although appealing both from the system design and extensibility points of view, extensible systems are vu...
Modern software must evolve in response to changing condi- tions. In the most widely used programming environments, code is static and cannot change at runtime. This poses problems for applications that have limited d...
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Large-scale scientific applications present great challenges to computational scientists in terms of obtaining high performance and in managing large datasets. These applications (most of which are simulations) may em...
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In this paper, we present algorithms for efficiently implementing three collective communication operations on reflective memory network clusters: Broadcast, Barrier Synchronization and All-Reduce. These algorithms ha...
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An one-way hash chain generated by the iterative use of a one-way hash function on a secret value has recently been widely employed to develop many practical cryptographic solutions, especially electronic micropayment...
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There is increasing interest in computing models that support extensibility of systems through code migration. Although appealing both from the system design and extensibility points of view, extensible systems are vu...
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There is increasing interest in computing models that support extensibility of systems through code migration. Although appealing both from the system design and extensibility points of view, extensible systems are vulnerable to an external program's aberrant execution behaviors. We examine the problems of resource access control and resource consumption. We propose solutions for these problems and analyze their effectiveness.
Our results demonstrate that our novel application development environment provides both ease-of-use and high performance for large-scale, I/O-intensive scientific applications.
ISBN:
(纸本)9781581132700
Our results demonstrate that our novel application development environment provides both ease-of-use and high performance for large-scale, I/O-intensive scientific applications.
With the increasing number of scientific applications manipulating huge amounts of data, effective high-level data management is an increasingly important problem. Unfortunately, so far the solutions to the high‐leve...
With the increasing number of scientific applications manipulating huge amounts of data, effective high-level data management is an increasingly important problem. Unfortunately, so far the solutions to the high‐level data management problem either require deep understanding of specific storage architectures and file layouts (as in high-performance file storage systems) or produce unsatisfactory I/O performance in exchange for ease-of-use and portability (as in relational DBMSs). In this paper we present a novel application development environment which is built around an active meta-data management system (MDMS) to handle high-level data in an effective manner. The key components of our three-tiered architecture are user application, the MDMS, and a hierarchical storage system (HSS). Our environment overcomes the performance problems of pure database-oriented solutions, while maintaining their advantages in terms of ease-of-use and portability. The high levels of performance are achieved by the MDMS, with the aid of user-specified, performance-oriented directives. Our environment supports a simple, easy-to-use yet powerful user interface, leaving the task of choosing appropriate I/O techniques for the application at hand to the MDMS. We discuss the importance of an active MDMS and show how the three components of our environment, namely the application, the MDMS, and the HSS, fit together. We also report performance numbers from our ongoing implementation and illustrate that significant improvements are made possible without undue programming effort.
The issue of fairness has new prominence in multi-service networks where the diverse service characteristics can result in a very unfair resource allocation unless the issue is considered explicitly at the design stag...
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Via experimental study, we illustrate how TCP modulates application traffic in such a way as to adversely affect network performance in a heterogeneous computing system. Even when aggregate application traffic smooths...
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Via experimental study, we illustrate how TCP modulates application traffic in such a way as to adversely affect network performance in a heterogeneous computing system. Even when aggregate application traffic smooths out as more applications' traffic are multiplexed, TCP induces burstiness into the aggregate traffic load, and thus hurts network performance. This burstiness is particularly bad in TCP Reno, and even worse when RED gateways are employed. Based on the results of this experimental study, we then develop a stochastic model for TCP Reno to demonstrate how the burstiness in TCP Reno can be modeled.
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