This paper presents the new approach to parallel calculations with the use of mixed formats. Usually parallel computations are done in multibit Pulse Code Modulation (PCM). Using this format requires doing multibit mu...
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ISBN:
(纸本)9780889866560
This paper presents the new approach to parallel calculations with the use of mixed formats. Usually parallel computations are done in multibit Pulse Code Modulation (PCM). Using this format requires doing multibit multiplications what often decreases the speed of calculations. Mixed formats, which join differential modulation codes such as Delta Modulation (DM) with PCM, can lead to the decrease of code word length and speed-up operation in DSP (Digital Signal Processing). Some kinds of DM such as MDPCM-PCM (Modified Differential Pulse Code Modulation) and SDPCM-PCM (Synthetic DPCM) enable to replace the time-consuming multiplications with fast shift operations. The purpose of this work is working out the new processing methods for the fast-acting increase of DSP algorithms on the basis of parallel computations in mixed formats, especially with the use of MDPCM-PCM and SDPCM-PCM formats.
Heterogeneous computing (HC) is the coordinated use of different types of machines, networks, and interfaces to maximize the combined performance and/or cost effectiveness of the system. Heuristics for allocating reso...
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This paper presents a parallel and distributed approach to ensemble learning of Fuzzy ARTMAP classifiers based on the multi-agent platform. Neural networks have been used successfully in a broad range of non-linear pr...
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ISBN:
(纸本)9783540728290
This paper presents a parallel and distributed approach to ensemble learning of Fuzzy ARTMAP classifiers based on the multi-agent platform. Neural networks have been used successfully in a broad range of non-linear problems that are difficult to solve using traditional techniques. Training a neural network for practical applications is often time consuming thus extensive research work is being carried out to accelerate this process. Fuzzy ARTMAP (FAM) is one of the fastest neural network architectures given its ability to produce neurons on demand to represent new classification categories. FAM can adapt to the input data without having to specify an arbitrary structure. However, FAM is vulnerable to noisy data which can rapidly degrade network performance. Due to its fast learning features, FAM is sensitive to the sequence of input sample presentations. In this paper we propose a parallel and distributed approach to ensemble learning for FAM networks as a means to improve the over-all performance of the classifier and increase its resilience to noisy data. We use the multi-agent platform to distribute the computational load of the ensemble to several hosts. The multi-agent platform is a robust environment that can support large-scale neural network ensembles. Our approach also demonstrates the feasibility of large-scale ensembles. The experimental results show that ensemble learning substantially improved the performance of fuzzy ARTMAP classifiers.
We consider storage in an extremely large-scale distributed computer system designed for stream processing applications. In such systems, incoming data and intermediate results may need to be stored to enable future a...
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We consider storage in an extremely large-scale distributed computer system designed for stream processing applications. In such systems, incoming data and intermediate results may need to be stored to enable future analyses. The quantity of such data would dominate even the largest storage system. Thus, a mechanism is needed to keep the most useful data. One recently introduced approach is to employ retention value functions, which effectively assign each data object a value that changes over time. Storage space is then reclaimed automatically by deleting data of lowest current value. In such large systems, there can naturally be multiple file systems available, each with different properties. Choosing the right file system for a given incoming data stream presents a challenge. In this paper we provide a novel and effective scheme for optimizing the placement of data within a distributed storage subsystem employing retention value functions. The goal is to keep the data of highest overall value, while simultaneously balancing the read load to the file system.
The use of MANET's (or Mobile Ad hoc NETworks) is becoming very popular. Power efficiency is a key issue in this type of network, as mobile devices usually rely on limited power supplies. One essential service, th...
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ISBN:
(纸本)9783540747413
The use of MANET's (or Mobile Ad hoc NETworks) is becoming very popular. Power efficiency is a key issue in this type of network, as mobile devices usually rely on limited power supplies. One essential service, the routing protocol, employed to discover routes between nodes in the network, can greatly affect power consumption. Furthermore, many distributed applications require an additional membership service to keep track of the nodes that make up the system at any moment. In general, this information is not provided by routing services with the exception of the Optimised Link State Routing protocol (OLSR). The two services, routing and membership estimation, form a basic support to build other higher-level distributed services on ad hoc networks. To decrease the over-all power consumption these services should be optimized for the intended use of the network. In particular the degree of mobility can have an impact on the power consumption and performance of different approaches to routing and membership estimation. In this paper we present a study of two different approaches that combine a routing service with membership estimation. We compare the proactive OLSR with our own approach. Our approach consists of integrating a gossip-style failure detector with the reactive Dynamic Source Routing protocol (DSR). We present an analysis of the effects of mobility on the global performance and power consumption of the two approaches. We identify scenarios for which each approach is best suited.
The proceedings contain 32 papers. The topics discussed include: finite abstract models for deterministic transition systems: fair parallel composition and refinement-preserving logic;slicing abstractions;formalizing ...
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ISBN:
(纸本)9783540756972
The proceedings contain 32 papers. The topics discussed include: finite abstract models for deterministic transition systems: fair parallel composition and refinement-preserving logic;slicing abstractions;formalizing compatibility and substitutability in communication protocols using I/O-constraint automata;is your security protocol on time?;adapting the UPPAAL model of a distributed lift system;zone-based universality analysis for single-clock timed automata;compositional semantics of system-level designs written in SystemC;reusing requirements: the need for extended variability models;test selection criteria for quantifier-free first-order specifications;formal testing of systems presenting soft and hard deadlines;automatic composition of stateless components: a logical reasoning approach;and a model of component-based programming.
We examine the problem of detecting nested temporal predicates given the execution trace of a distributed program. We present a technique that allows efficient detection of a reasonably large class of predicates which...
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ISBN:
(纸本)9783540751410
We examine the problem of detecting nested temporal predicates given the execution trace of a distributed program. We present a technique that allows efficient detection of a reasonably large class of predicates which we call the Basic Temporal Logic or BTL. Examples of valid BTL predicates are nested temporal predicates based on local variables with arbitrary negations, disjunctions, conjunctions and the possibly (EF or lozenge) and invariant(AG or square) temporal operators. We introduce the concept of a basis, a compact representation of all global cuts which satisfy the predicate. We present an algorithm to compute a basis of a computation given any BTL predicate and prove that its time complexity is polynomial with respect to the number of processes and events in the trace although it is not polynomial in the size of the formula. We do not know of any other technique which detects a similar class of predicates with a time complexity that is polynomial in the number of processes and events in the system. We have implemented a predicate detection toolkit based on our algorithm that accepts offline traces from any distributed program.
Flow graphs provide an explicit description of the parallelization of an application by mapping vertices onto serial computations and edges onto message transfers. We present the design and implementation of a debugge...
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ISBN:
(纸本)159593748X
Flow graphs provide an explicit description of the parallelization of an application by mapping vertices onto serial computations and edges onto message transfers. We present the design and implementation of a debugger for the flow graph based Dynamic parallel Schedules (DPS) parallelization framework. We use the flow graph to provide both a high level and detailed picture of the current state of the application execution. We describe how reordering incoming messages enables testing for the presence of message races while debugging a parallel application. The knowledge about causal dependencies between messages enables tracking messages and computations along individual branches of the flow graph. In addition to common features such as restricting the analysis to a subset of threads or processes and attaching sequential debuggers to running processes, the proposed debugger also provides support for message alterations and for message content dependent breakpoints. Copyright 2007 ACM.
Scale-out approach, in contrast to scale-up approach (exploring increasing performance by utilizing more powerful shared-memory servers), refers to deployment of applications on a large number of small, inexpensive, b...
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Scale-out approach, in contrast to scale-up approach (exploring increasing performance by utilizing more powerful shared-memory servers), refers to deployment of applications on a large number of small, inexpensive, but tightly packaged and tightly interconnected servers. Recently, there has been an increasing interest in scale-out approach. The purpose of this study is to discover advantages or disadvantages of scale-out systems with a typical enterprise workload, IBM Trade Performance Benchmark Sample for Websphere application server (a.k.a. Trade6). In this work, through cross system performance comparison, we show that for such workload, scale-out approach has better performance/cost effect. In term of scalability, we show that Websphere application server packages for distributed environment scale well while the possible bottleneck of the application deployment is the database tier. We present preliminary results to show that both database partitioning feature (DPF) and federated database server approaches are not exactly suitable for providing scale-out solution for the database tier of workloads similar to Trade (small tables and short transactions). In addition, we discuss our on-going effort on further performance study: (1) studies of performance/scalability for larger deployments by adopting the IBM AMBIENCE queuing network modeling tool, (2) performance breakdowns utilizing IBM ACTC hardware counter library.
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