The diversity of computers and networks within a distributed system makes these systems highly heterogeneous. System heterogeneity complicates the design of static applications that must meet quality-of-service (QoS) ...
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This paper presents language features for High Performance Fortran (HPF) to specify non-local access patterns of distributed arrays, called halos, and to control the communication associated with these non-local acces...
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This paper presents the PuRE/EPOS approach to deal with the high complexity of adaptable operating systems and also to diminish the distance between application and operating system. A system designed according to the...
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We present our experience of building a prototype system based on the Utility Model for adaptive multimedia. The Utility Model is proposed to capture the issues and dynamics in multi-session multimedia systems where t...
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Our study of a large set of scientific applications over the past three years indicates that the processing for multi-dimensional datasets is often highly stylized. The basic processing step usually consists of mappin...
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Our study of a large set of scientific applications over the past three years indicates that the processing for multi-dimensional datasets is often highly stylized. The basic processing step usually consists of mapping the individual input items to the output grid and computing output items by aggregating, in some way, all the input items mapped to the corresponding grid point. In this paper, we discuss the design and performance of T2, an infrastructure for building parallel database systems that integrates storage, retrieval andprocessing of multi-dimensional datasets. It achieves its primary advantage from the ability to integrate data retrieval andprocessing for a wide variety of applications and from the ability to maintain and jointly process multiple datasets with different underlying grids. We present preliminary performance results comparing the implementation of two applications using the T2 services with custom-built integrated implementations.
Our study of a large set of scientific applications over the past three years indicates that the processing for multidimensional datasets is often highly stylized. The basic processing step usually consists of mapping...
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Our study of a large set of scientific applications over the past three years indicates that the processing for multidimensional datasets is often highly stylized. The basic processing step usually consists of mapping the individual input items to the output grid and computing output items by aggregating, in some way, all the input items mapped to the corresponding grid point. In this paper we discuss the design and performance of T2, an infrastructure for building parallel database systems that integrates storage, retrieval andprocessing of multi-dimensional datasets. It achieves its primary advantage from the ability to integrate data retrieval andprocessing for a wide variety of applications and from the ability to maintain and jointly process multiple datasets with different underlying grids. We present preliminary performance results comparing the implementation of two applications using the T2 services with custom-built integrated implementations.
This paper explains how efficient support for semi-regular distributions can be incorporated in a uniform compilation framework for hybrid applications. The key focus of this work is in showing how, unlike other exist...
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This paper explains how efficient support for semi-regular distributions can be incorporated in a uniform compilation framework for hybrid applications. The key focus of this work is in showing how, unlike other existing schemes, our scheme is able to minimize preprocessing overheads and maintain sophisticated communication optimizations (such as reduction of inter-processor communication during schedule generation and sharing of communicated information between regular and irregular accesses) even in the presence of semi-regular distributions. It is only natural that preprocessing overheads associated with semi-regular distributions be intermediate between those involved for regular and irregular distributions. This paper shows how various properties can be inferred for semi-regular distributions. These allow the use of the interval representation which in turn reduces the preprocessing overhead and makes possible compatible code generation for hybrid references. Experimental results on a 16-processor IBM SP-2 for a number of sparse applications using semi-regular distributions show that our scheme is feasible.
Classification is an important problem in the field of data mining. Construction of good classifiers is computationally intensive and offers plenty of scope for parallelization. Divide-and-conquer paradigm can be used...
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Classification is an important problem in the field of data mining. Construction of good classifiers is computationally intensive and offers plenty of scope for parallelization. Divide-and-conquer paradigm can be used to efficiently construct decision tree classifiers. We discuss in detail various techniques for parallel divide-and-conquer and extend these techniques to handle efficiently disk-resident data. Furthermore, a generic technique for parallel out-of-core divide-and-conquer problems is suggested. We present pCLOUDS, the parallel version of the decision tree classifier algorithm CLOUDS, capable of handling large out-of-core data sets. pCLOUDS exhibits excellent speedup, sizeup and scaleup properties which make it a competitive tool for data mining applications. We evaluate the performance of pCLOUDS for a range of synthetic data sets on the IBM-SP2.
This paper explains how efficient support for semi-regular distributions can be incorporated in a uniform compilation framework for hybrid applications. The key focus of this work is in showing how, unlike other exist...
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This paper explains how efficient support for semi-regular distributions can be incorporated in a uniform compilation framework for hybrid applications. The key focus of this work is in showing how, unlike other existing schemes, our scheme is able to minimize preprocessing overheads and maintain sophisticated communication optimizations (such as reduction of inter-processor communication during schedule generation and sharing of communicated information between regular and irregular accesses) even in the presence of semi-regular distributions. It is only natural that preprocessing overheads associated with semi-regular distributions be intermediate between those involved for regular and irregular distributions. This paper shows how various properties can be inferred for semi-regular distributions. These allow the use of the interval representation which in turn reduces the preprocessing overhead and makes possible compatible code generation for hybrid references. Experimental results on a 16-processor IBM SP-2 for a number of sparse applications using semi-regular distributions show that our scheme is feasible.
The ability to dynamically adapt an unstructured grid (or mesh) is a powerful tool for solving computational problems with evolving physical features;however, an efficient parallel implementation is rather difficult, ...
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The ability to dynamically adapt an unstructured grid (or mesh) is a powerful tool for solving computational problems with evolving physical features;however, an efficient parallel implementation is rather difficult, particularly from the viewpoint of portability on various multiprocessor platforms. We address this problem by developing PLUM, an automatic and architecture-independent framework for adaptive numerical computations in a message-passing environment. Portability is demonstrated by comparing performance on an SP2, an Origin2000, and a T3E, without any code modifications. We also present a general-purpose load balancer that utilizes symmetric broadcast networks (SBN) as the underlying communication pattern, with a goal to providing a global view of system loads across processors. Experiments on an SP2 and an Origin2000 demonstrate the portability of our approach which achieves superb load balance at the cost of minimal extra overhead.
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