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tom Vol. 22. No 2
113--123
EN
In this paper after a short theoretical introduction about modern techniques used inparallel computing, we report a case study related to the design and development of the Caliban Linux High Performance Computing cluster, carried out by the author in the High Performance Computing Laboratory of the University of L’Aquila. Finally we report some performance evaluation tests related to the Caliban cluster performed using HPL (High-Performance Linpack) benchmarks.
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Content available remote Efficient Simulation of Reaction Systems on Graphics Processing Units
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EN
Reaction systems represent a theoretical framework based on the regulation mechanisms of facilitation and inhibition of biochemical reactions. The dynamic process defined by a reaction system is typically derived by hand, starting from the set of reactions and a given context sequence. However, this procedure may be error-prone and time-consuming, especially when the size of the reaction system increases. Here we present HERESY, a simulator of reaction systems accelerated on Graphics Processing Units (GPUs). HERESY is based on a fine-grained parallelization strategy, whereby all reactions are simultaneously executed on the GPU, therefore reducing the overall running time of the simulation. HERESY is particularly advantageous for the simulation of large-scale reaction systems, consisting of hundreds or thousands of reactions. By considering as test case some reaction systems with an increasing number of reactions and entities, as well as an increasing number of entities per reaction, we show that HERESY allows up to 29× speed-up with respect to a CPU-based simulator of reaction systems. Finally, we provide some directions for the optimization of HERESY, considering minimal reaction systems in normal form.
EN
The method for computing the latent heat in a system with many independently behaving components of the order parameter proposed previously is presented for a chosen point of the phase diagram of the 3D Ashkin-Teller (AH) model. Binder, Challa, and Lee-Kosterlitz cumulants are exploited and supplemented by the use of the energy distribution histogram. The proposed computer experiments using the Metropolis algorithm calculate the cumulants in question, the internal energy and its partial contributions as well as the energy distribution for the model Hamiltonian and its components. The important part of our paper is an attempt to validate the results obtained by several independent methods.
EN
In this paper we propose a new method of scheduling the distributed applications in cloud environment according to the High Performance Computing as a Service concept. We assume that applications, that are submitted for execution, are specified as task graphs. Our method dynamically schedules all the tasks using resource sharing by the applications. The goal of scheduling is to minimize the cost of resource hiring and the execution time of all incoming applications. Experimental results showed that our method gives significantly better utilization of computational resources than existing management methods for clouds.
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Content available remote High level Grid programming with ASSIST
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EN
The development of efficient Grid applications usually requires writing huge portions of code directly at the level of abstraction provided by the underlying Grid middleware. In this work we discuss an alternative approach, raising the level of abstraction used when programming Grid applications. Our approach requires programmers just to describe in a qualitative way the kind of parallelism they want to express. Then, compiler tools, loader tools and run time system take complete care of running the application on a Grid target architecture. This allows to move most of the cumbersome tasks related to Grid targeting and management from programmer responsibility to tools. This paper introduces the structured parallel programming environment ASSIST, whose design is aimed at raising the level of abstraction in Grid programming and discusses how it can support transparent Grid programming while implementing Grid adaptivity.
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