The ATLAS detector at CERN's Large Hadron Collider presents data handling requirements on an unprecedented scale. From 2008 on the ATLAS distributed data management system, Don Quijote2 (DQ2), must manage tens of ...
The ATLAS detector at CERN's Large Hadron Collider presents data handling requirements on an unprecedented scale. From 2008 on the ATLAS distributed data management system, Don Quijote2 (DQ2), must manage tens of petabytes of experiment data per year, distributed globally via the LCG, OSG and NDGF computing grids, now commonly known as the WLCG. Since its inception in 2005 DQ2 has continuously managed all experiment data for the ATLAS collaboration, which now comprises over 3000 scientists participating from more than 150 universities and laboratories in 34 countries. Fulfilling its primary requirement of providing a highly distributed, fault-tolerant and scalable architecture DQ2 was successfully upgraded from managing data on a terabyte-scale to managing data on a petabyte-scale. We present improvements and enhancements to DQ2 based on the increasing demands for ATLAS data management. We describe performance issues, architectural changes and implementation decisions, the current state of deployment in test and production as well as anticipated future improvements. Test results presented here show that DQ2 is capable of handling data up to and beyond the requirements of full-scale data-taking.
We have achieved a sustained performance of 55 TFLOPS for molecular dynamics simulations of the amyloid fibril formation of peptides from the yeast Sup35 in an aqueous solution. For performing the calculations, we use...
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Although Statecharts has gained widespread use as a formalism for modeling reactive real-time systems, testing these systems still confronts some difficulties, of which a major one is the existence of numerous and com...
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Although statecharts has gained widespread use as a formalism for modeling reactive real-time systems, testing these systems still confronts some difficulties, of which a major one is the existence of numerous and com...
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Although statecharts has gained widespread use as a formalism for modeling reactive real-time systems, testing these systems still confronts some difficulties, of which a major one is the existence of numerous and complex system behaviors. It is extremely difficult to conduct comprehensive and in-depth testing of such real-time systems. This paper presents an approach to property-oriented real-time testing. Necessary real-time extensions are proposed such that the time-enriched statecharts can describe nontrivial timing constraints. The properties to be tested are characterized by a restricted real-time logic. Then the targeted test sequences are derived from the real-time models according to the user-specified properties. Using this approach, testing efforts can be focused on particular properties of the real-time systems and usually only a small portion of the total behaviors needs to be tested.
Cluster computers have become the vehicle of choice to build high performance computing environments. To fully exploit the computing power of these environments, one must utilize high performance network and protocol ...
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Cluster computers have become the vehicle of choice to build high performance computing environments. To fully exploit the computing power of these environments, one must utilize high performance network and protocol technologies, since the communication patterns of parallel applications running on clusters require low latency and high throughput, not achievable by using off-the-shell network technologies. We have developed a technology to build high performance network equipment, called MaestroS. This paper describes the novel techniques used by Maestro2 to extract maximum performance from the physical medium and studies the impact of software-level parameters. The results obtained clearly show that Maestro2 is a promising technology, presenting very good results both in terms of latency and throughput. The results also show the large impact of software overhead in the overall performance of the system and validate the need for optimized communication libraries for high performance computing.
Recently Tao Guo (1999) proposed a stochastic search algorithm in his PhD thesis for solving function optimization problems. He combined the subspace search method (a general multi-parent recombination strategy) with ...
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Recently Tao Guo (1999) proposed a stochastic search algorithm in his PhD thesis for solving function optimization problems. He combined the subspace search method (a general multi-parent recombination strategy) with the population hill-climbing method. The former keeps a global search for the overall situation, and the latter maintains the convergence of the algorithm. Guo's algorithm has many advantages, such as the simplicity of its structure, the high accuracy of its results, the wide range of its applications, and the robustness of its use. In this paper a preliminary theoretical analysis of the algorithm is given and some numerical experiments are performed using Guo's algorithm to demonstrate the theoretical results. Three asynchronous parallel algorithms with different granularities for MIMD machines are designed by parallelizing Guo's algorithm.
This paper gives denotational models for three logic programming languages of progressive complexity, adopting the "logic programming without logic" approach. The first language is the control flow kernel of...
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ISBN:
(纸本)1581132654
This paper gives denotational models for three logic programming languages of progressive complexity, adopting the "logic programming without logic" approach. The first language is the control flow kernel of sequential Prolog, featuring sequential composition and backtracking. A committed-choice concurrent logic language with parallel composition (parallel AND) and don't care nondeterminism is studied next. The third language is the core of Warren's basic Andorra model, combining parallel composition and don't care nondeterminism with two forms of don't know nondeterminism (interpreted as sequential and parallel OR) and favoring deterministic over nondeterministic computation. We show that continuations are a valuable tool in the analysis and design of semantic models for both sequential and parallel logic programming. Instead of using mathematical notation, we use the functional programming language Haskell as a metalanguage for our denotational semantics, and employ monads in order to facilitate the transition from one language under study to another.
This paper describes an approach to the evolutionary modeling problem of ordinary differential equations including systems of ordinary differential equations and higher-order differential equations. Hybrid evolutionar...
This paper describes an approach to the evolutionary modeling problem of ordinary differential equations including systems of ordinary differential equations and higher-order differential equations. Hybrid evolutionary modeling algorithms are presented to implement the automatic modeling of one- and multi-dimensional dynamic systems respectively. The main idea of the method is to embed a genetic algorithm in genetic programming where the latter is employed to discover and optimize the structure of a model, while the former is employed to optimize its parameters. A number of practical examples are used to demonstrate the effectiveness of the approach. Experimental results show that the algorithm has some advantages over most available modeling methods.
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