The exponentially increasing complexity of many scientific applications and the high cost of supercomputing force us to explore new, sustainable, and affordable high-performance computing platforms. Recent significant...
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ISBN:
(纸本)0769521320
The exponentially increasing complexity of many scientific applications and the high cost of supercomputing force us to explore new, sustainable, and affordable high-performance computing platforms. Recent significant advances in FPGA technology and the inherent advantages of configurable logic have brought about new research efforts in the configurable computing field: parallelprocessing on configurable chips. We explore here parallel LU factorization of large sparse block-diagonal-bordered (BDB) matrices on a configurable multiprocessor that we have designed and implemented. A dynamic load balancing strategy is proposed and analyzed. Performance results for ieee power test systems are provided. Our research provides evidence that configurable logic can be a viable alternative to high-performance scientific computing.
This article presents a method for evaluating the CPU power, independently from the system used, in heterogeneous networks of work stations. It is based on the use of Java language in order to ensure application porta...
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ISBN:
(纸本)0769522106
This article presents a method for evaluating the CPU power, independently from the system used, in heterogeneous networks of work stations. It is based on the use of Java language in order to ensure application portability and more particularly on the mechanism of thread CPU processing time measurement introduced in the version 1.5 of Sun Java. That tool will be integrated into the load balancing mechanism which is totally written in Java and that we developed in the LIFL project ADAJ. We show how to evaluate the potential power of the CPU with a software totally written in Java. Moreover, we will justify the results provided by our approach. We will also analyse the exploitation of the calibration tool in order to improve the execution time of parallel and distributed applications in the context of load balancing in a network of workstations.
Desk checking is known to be an effective reading technique for early detection of sequential program errors. This paper discusses how to extend desk checking for concurrent and distributed programs. In addition to un...
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ISBN:
(纸本)0769521320
Desk checking is known to be an effective reading technique for early detection of sequential program errors. This paper discusses how to extend desk checking for concurrent and distributed programs. In addition to unbounded possible schedules, concurrent and distributed programs have execution states that include more than one process. The new concurrent and distributed desk checking technique supports the selection of schedules and execution states to be reviewed. The cross-product technique assists in the selection process. Schedule selection guidelines that facilitate early detection and coverage are introduced. Industrial pilots show that concurrent and distributed desk checking is a promising review technique for early error detection.
This article presents an efficient method to calculate in parallel the values of the Smarandache function S(i), i = 1, 2, ..., n. The value S(i) can be sequentially found with a complexity of i/log i. The computation ...
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Nowadays, distributed computing over large networks is a popular and good alternative to dedicated parallel machines or clusters. Nevertheless, grid computing often suffers poor performances due to the heterogeneity o...
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ISBN:
(纸本)0769521320
Nowadays, distributed computing over large networks is a popular and good alternative to dedicated parallel machines or clusters. Nevertheless, grid computing often suffers poor performances due to the heterogeneity of the machines and bottlenecks on the network. This is especially true for iterative computations when a lot of iterations are needed to converge to the problem solution. This paper evaluates Jace, a Java environment we have developed to easily implement and execute asynchronous iterationsasynchronous communications algorithms on the grid. Our evaluation is based on a typical iterative algorithm: the Power Method.
We analyze the average-case performance of an online scheduling algorithm for independent parallel tasks. We develop a method to calculate an analytical asymptotic average-case performance bound for arbitrary probabil...
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ISBN:
(纸本)0769521320
We analyze the average-case performance of an online scheduling algorithm for independent parallel tasks. We develop a method to calculate an analytical asymptotic average-case performance bound for arbitrary probability distribution of task sizes. In particular, we show that when task sizes are uniformly distributed in the range [1..C], an asymptotic average-case performance bound of M/M-(3-(1+1/C)C+1)C-1 can be achieved, where M is the number of processors. We also present extensive numerical and simulation data to demonstrate the accuracy of our analytical bound.
This article gives a brief overview of theoretical advances, computing trends, applications and future perspectives in parallel genetic algorithms. The information is segregated into two periods before and after the y...
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ISBN:
(纸本)0769521320
This article gives a brief overview of theoretical advances, computing trends, applications and future perspectives in parallel genetic algorithms. The information is segregated into two periods before and after the year 2000 and in all chapters. The second period is more interesting and of higher importance, because it highlights recent research efforts and gives some hints about possible future trends. That is why we devote much space to the second period. As there is no such an overview of the recent period of parallel genetic algorithms, we find our investigation to be important in many aspects.
Data mining is an application that is commonly executed on massively parallel systems, often using clusters with hundreds of processors. With a disk-based data store, however, the data must first be delivered to the p...
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ISBN:
(纸本)0769521320
Data mining is an application that is commonly executed on massively parallel systems, often using clusters with hundreds of processors. With a disk-based data store, however, the data must first be delivered to the processors before effective mining can take place. Here, we describe the prototype of an experimental system that moves processing closer to where the data resides, on the disk, and exploits massive parallelism via reconfigurable hardware to perform the computation. The performance of the prototype is also reported.
The past few years have seen the emergence of application domains that need to process data elements arriving as a continuous stream. Recently, several architectures to process database queries over these data streams...
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ISBN:
(纸本)0769521320
The past few years have seen the emergence of application domains that need to process data elements arriving as a continuous stream. Recently, several architectures to process database queries over these data streams have been proposed in the literature. Although these architectures may be suitable for general purpose query processing in a centralized-setting, they have serious limitations when it comes to supporting data mining queries in a distributed-setting. Data mining is an interactive process and it is crucial that we provide the user with interactive response times. In addition, many data mining applications, such as network intrusion detection, need to process data streams arriving at distributed end-points. Centralized processing of data streams for network intrusion detection would be overwhelming. These are fundamental issues for data mining over data streams and have been addressed in this paper. Our schemes give controlled interactive response times when processing data streams in a distributed-setting.
Cluster computing has become a valid alternative for high performance computing. To fully exploit the computing power of these environments, one must utilize high performance network and protocol technologies, since p...
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