During our research for characterizing individual computing nodes using Software Probes, one of the remaining issues for quickly probing them was that of the checkpoints' sizes. This article shows the different ap...
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During our research for characterizing individual computing nodes using Software Probes, one of the remaining issues for quickly probing them was that of the checkpoints' sizes. This article shows the different approaches we used in order to reduce the Probes' sizes. We demonstrate that in some cases it is possible to reduce the set of Probes of an application up to 95% of its original size, thus making our approach for machine characterization useful even through slow networks such as the Internet.
作者：
Cornwall, L.A.Heymann, E.STFC
Rutherford Appleton Laboratory Harwell Oxford DidcotOX11 OQX United Kingdom Universitat Autonoma de Barcelona
Computer Architecture and Operating System Department Campus de Bellaterra Bellaterra Barcelona08193 Spain
This provides an overview of the activities of the European Grid Infrastructure (EGI) Software Vulnerability Group (SVG) and progress made in addressing vulnerabilities in collaboration with the European Middleware In...
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Wind field calculation is a common problem in different environmental applications from design of wind farms to forest fire propagation prediction. Calculating the wind field is a complex problem that involves solving...
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Wind field calculation is a common problem in different environmental applications from design of wind farms to forest fire propagation prediction. Calculating the wind field is a complex problem that involves solving huge linear systems. Solving such systems requires the use of iterative methods, such as Preconditioned Conjugate Gradient (PCG) that in most cases take long execution time. The PCG solver with different preconditioners has been analyzed and the performance and scalability of this solver has been determined. The most time consuming operations have been identified and a new method has been developed to improve the parallelization reducing the execution time and increasing the scalability. The new method has been applied on a wind field simulator, called WindNinja, usually coupled to forest fire propagation models. The results are very promising and the new parallelization method appears as a key point to be integrated in other approaches.
Distributed video-on-demand servers (DVS) are proposed as a solution to the limited streaming capacity and null scalability of large-scale centralized systems. Server interconnection topology plays an important role i...
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Distributed video-on-demand servers (DVS) are proposed as a solution to the limited streaming capacity and null scalability of large-scale centralized systems. Server interconnection topology plays an important role in video-on-demand systems' performance. This paper presents an analysis of different topologies and their influence over storage management and distribution, delivery policies performance, refusing requests occurrence, network consumption and scalability. To accomplish the proposal study, we have designed a complete simulation framework for DVS systems. Experimental results obtained under different workload conditions allow us to draw two important conclusions: First, a better connectivity implies a lower mean request service distance and lesser network requirements, improving multicast policies efficiency. Second, topology regularity is essential, as it allows a greater traffic balancing and provides more alternative routing paths. The analysis of global results shows that hypercube presents the best trade-off among all the evaluated metrics, providing a gradual and unlimited scalability for the DVS system.
The performance modeling of a parallel application is crucial for the better use of the HPC resources. However, certain scientific applications exhibit irregular performance characteristics, posing challenges in accur...
The performance modeling of a parallel application is crucial for the better use of the HPC resources. However, certain scientific applications exhibit irregular performance characteristics, posing challenges in accurately modeling their behavior. This irregularity primarily arises from these applications’ non-deterministic computation and communication patterns. This article introduces a performance modeling methodology designed for irregular parallel applications based on the PAS2P methodology. The PAS2P tool generates an application signature and utilizes it to analyze and predict performance. Our approach is based on process-based data analysis to characterize these applications according to the behavior of individual processes, proposing a model to group processes at the time of signature construction. This model allowed us to obtain a reduced number of phases and weights in a limited time, allowing us to characterize the application.
Performance modeling of parallel applications is essential for optimizing resource usage in high-performance computing (HPC) systems. However, some scientific applications exhibit irregular performance behaviors, whic...
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ISBN:
(数字)9798331527891
ISBN:
(纸本)9798331527907
Performance modeling of parallel applications is essential for optimizing resource usage in high-performance computing (HPC) systems. However, some scientific applications exhibit irregular performance behaviors, which complicates cre-ating accurate characteristic models. This irregularity is mainly due to these applications' nondeterministic computational and communication patterns. Tools such as PAS2P (Parallel Application Signatures for Performance Prediction) are used to extract detailed information about parallel applications. PAS2P is based on the repetitive behavior of the application to analyze and predict the application's performance, using the same resources that the parallel application uses for its execution. This paper presents a characterization model based on the PAS2P methodology for irregular applications that groups the repeatability patterns of all the processes running the application into a single characteristic model. To achieve this, we consolidate the different characterizations performed by each process independently, using metrics such as the number of instructions, the execution time of relevant sections, and the topological characteristics of the application. By grouping these repeatability patterns of all processes, we can obtain a concise and accurate representation of the behavior of irregular applications, thus improving predictability and performance optimization in HPC systems.
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