Scalability has been used extensively as a de factor performance criterion for evaluating parallel algorithms and architectures. In this paper, the relation between scalability and execution time is carefully studied....
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Scalability has been used extensively as a de factor performance criterion for evaluating parallel algorithms and architectures. In this paper, the relation between scalability and execution time is carefully studied. Results show that isospeed scalability well characterizes the variation of execution time. Three algorithms from scientific computing are implemented on an Intel Paragon and an IBM SP2 parallel computer. Experimental and theoretical results show that scalability is an important, distinct metric for parallel and distributed systems, and may be as important as execution time in a scalable parallel and distributed environment.
The objective of this paper is the description of the implementation of the WAVE model and language for highly parallelprocessing in open computer networks as well as an application of the distributed WAVE interprete...
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The objective of this paper is the description of the implementation of the WAVE model and language for highly parallelprocessing in open computer networks as well as an application of the distributed WAVE interpreter for modelling complex systems within an object-oriented philosophy. WAVE represents a new distributed programming paradigm enabling the dynamic creation and processing of arbitrary network-structured knowledge. The model operates in a spatial pattern-matching, logic-flow, mode, without any centralized control.
One of the primary tasks in mining distributed textual data is feature extraction. The widespread digitization of information has created a wealth of data that requires novel approaches to feature extraction in a dist...
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ISBN:
(纸本)0769512968
One of the primary tasks in mining distributed textual data is feature extraction. The widespread digitization of information has created a wealth of data that requires novel approaches to feature extraction in a distributed environment. We propose a massively parallel model for feature extraction that employs unused cycles on networks of PCs/work-stations in a highly distributed environment. We have developed an analytical model of the time and communication complexity of the feature extraction process in this environment based on feature extraction algorithms developed in our textual data mining research with HDDI(TM) [1] [18] [20]. We show that speedups linear in the number of processors are achievable for applications involving reduction operations based on a novel, parallel pipelined model of execution. We are in the process of validating our analytical model with empirical observations based on the extraction of features from a large number of pages on the World Wide Web.
This paper presents an overview of the Scalable parallel Instrumentation (SPI) tool being developed at Honeywell. SPI provides a complete development and execution environment for developing real-time instrumentation ...
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This paper presents an overview of the Scalable parallel Instrumentation (SPI) tool being developed at Honeywell. SPI provides a complete development and execution environment for developing real-time instrumentation functions for heterogeneous parallel/distributed systems. This includes: C-extensions and development tools for the event-action programming model, run-time support for transparent event-action execution on a heterogeneous distributed platform, and a library of primitives (actions) ranging from real-time data collection, analysis to graphic display. Concurrent instrumentation functions can be flexibly parallelized/distributed over the heterogeneous platform to selectively analyze and display desired activity at the hardware, OS, IPC, and application levels. SPI is currently operational on a heterogeneous platform of SUN workstations and Intel Paragon.
This paper describes a number of different coarse-grain GA's, including various migration strategies and connectivity schemes to address the premature convergence problem. These approaches are evaluated on a graph...
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This paper describes a number of different coarse-grain GA's, including various migration strategies and connectivity schemes to address the premature convergence problem. These approaches are evaluated on a graph partitioning problem. Our experiments showed, first, that the sequential GA's used are not as effective as parallel GA's for this graph partition problem. Second, for coarse-grain GA's, the results indicate that using a large number of nodes and exchanging individuals asynchronously among them is very effective. third, GA's that exchange solutions based on population similarity instead of a fixed connection topology get better results without any degradation in speed. Finally, we propose a new coarse-grained GA architecture, the Injection Island GA (iiGA). The preliminary results of iiGA's show them to be a promising new approach to coarse-grain GA's.
An application programming interface (API) was developed for executing parallel jobs in distributed computer systems. The scheme was implemented through design of an interface which provided dynamic establishment of c...
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ISBN:
(纸本)0769512968
An application programming interface (API) was developed for executing parallel jobs in distributed computer systems. The scheme was implemented through design of an interface which provided dynamic establishment of communication links between processes. Synchronization of the parallel database access was achieved through the fence operation which also allowed scalable initialization of parallel jobs.
The paper is devoted to scalability analysis of a typical linear algebra algorithm on heterogeneous clusters. We proof that traditional scalability metrics proposed for analysis of linear algebra algorithms is applica...
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ISBN:
(纸本)0769522106
The paper is devoted to scalability analysis of a typical linear algebra algorithm on heterogeneous clusters. We proof that traditional scalability metrics proposed for analysis of linear algebra algorithms is applicable on heterogeneous platform and investigate influence of three heterogeneous strategies computation distribution to Scalable Universal Matrix Multiplication Algorithm (SUMMA) scalability.
A program's architecture-how it organizes the invocation of application-specific logic-influences important program characteristics including its scalability and security. Architecture details are usually expresse...
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ISBN:
(纸本)9798350311990
A program's architecture-how it organizes the invocation of application-specific logic-influences important program characteristics including its scalability and security. Architecture details are usually expressed in the same programming language as the rest of a program, and can be difficult to distinguish from non-architecture code. And once defined, architecture is difficult and risky to change because it couples tightly with application logic over time. We introduce C-Saw: an approach to express a software's architecture using a new embedded domain-specific language (EDSL) designed for that purpose. It decouples application-specific logic from architecture, making it easier to identify architectural details of software. C-Saw leverages three ideas: (i) introducing a new, formally-specified EDSL to separate an application's architecture description from its programming language;(ii) reducing architecture implementation to the definition and management of distributed key-value tables, and (iii) introducing an expressive state-management abstraction for distributed applications. We describe a prototype implementation of C-Saw for C programs and use it to build end-to-end examples of expressing and changing the architecture of widely-used, third-party software. We evaluate this on Redis, cURL, and Suricata and find that C-Saw provides expressiveness and reusability, requires fewer lines of code when compared to directly using C to express architectural patterns, and imposes low performance overhead on typical workloads.
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