Results 1 - 10 of 128

The Distributed V Kernel and its Performance for Diskless Workstations

by David R. Cheriton, Willy Zwaenepoel - Proceedings of the 9th ACM Symposium on Operating Systems Principles , 1983
"... The distributed V kernel is a message-oriented kernel that provides uniform local and network interprocess communication. It is primarily being used in an environment of diskless workstations connected by a high-speed local network to a set of file servers. We describe a performance evaluation of th ..."
Abstract - Cited by 91 (14 self) - Add to MetaCart
The distributed V kernel is a message-oriented kernel that provides uniform local and network interprocess communication. It is primarily being used in an environment of diskless workstations connected by a high-speed local network to a set of file servers. We describe a performance evaluation

Long Term Distributed File Reference Tracing: Implementation and Experience

by L. Mummert, M. Satyanarayanan , 1994
"... DFSTrace is a system to collect and analyze long-term file reference data in a distributed UNIX workstation environment. The design of DFSTrace is unique in that it pays particular attention to efficiency, extensibility, and the logistics of long-term trace data collection in a distributed environme ..."
Abstract - Cited by 91 (3 self) - Add to MetaCart
DFSTrace is a system to collect and analyze long-term file reference data in a distributed UNIX workstation environment. The design of DFSTrace is unique in that it pays particular attention to efficiency, extensibility, and the logistics of long-term trace data collection in a distributed

Predictable Communication and Migration in the Quest-V Separation Kernel

by Ye Li , Richard West , Zhuoqun Cheng , Eric Missimer
"... Abstract-Quest-V is a separation kernel, which partitions a system into a collection of sandboxes. Each sandbox encapsulates one or more processing cores, a region of machine physical memory, and a subset of I/O devices. Quest-V behaves like a distributed system on a chip, using explicit communicat ..."
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Abstract-Quest-V is a separation kernel, which partitions a system into a collection of sandboxes. Each sandbox encapsulates one or more processing cores, a region of machine physical memory, and a subset of I/O devices. Quest-V behaves like a distributed system on a chip, using explicit

Distributed

by Waqaas Munawar, Olaf L, Muhammad Hamad Alizai, Klaus Wehrle, Rwth Aachen
"... Abstract—Wireless Sensor Networks (WSNs) are deployed for long periods of time, during which a need often arises to dynamically reprogram or retask them. An array of solutions has been proposed to this effect, ranging from full image replacement to virtual machines. However, the capabilities of Tiny ..."
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in the existing user interfaces, remaining transparent to the user. The evaluation shows that our approach imposes almost no performance overhead for loaded application while keeping a smaller memory footprint than other comparable solutions. I.

Parallel computation of RBF kernels for support vector classifiers

by Shibin Qiu, Terran Lane - Proc. 5th SIAM International Conference on Data Mining (SDM05 , 2005
"... While kernel support vector machines are powerful classification algorithms, their computational overhead can be significant, especially for large and high-dimensional data sets. A recent biomedical dataset, for instance, could take as long as 3 weeks to compute its RBF kernel matrix on a modern, si ..."
Abstract - Cited by 2 (1 self) - Add to MetaCart
, single-processor workstation. In this paper, we develop methods for high-performance parallel computation of kernel matrices. There are two key components to a parallel implementation: distribution of the computation across nodes and communication to combine the results. To address the first, we employ a

Parallel Computation of RBF Kernels for Support Vector Classifiers ∗

by unknown authors
"... While kernel support vector machines are powerful classification algorithms, their computational overhead can be significant, especially for large and high-dimensional data sets. A recent biomedical dataset, for instance, could take as long as 3 weeks to compute its RBF kernel matrix on a modern, si ..."
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, single-processor workstation. In this paper, we develop methods for high-performance parallel computation of kernel matrices. There are two key components to a parallel implementation: distribution of the computation across nodes and communication to combine the results. To address the first, we employ a

Distributed high performance computing in heterogeneous environments with DOTS

by Wolfgang Blochinger - In Proceedings of Intl. Parallel and Distributed Processing Symposium (IPDPS 2001 , 2001
"... This paper deals with high performance computing in heterogeneous clusters using the Distributed Object-Oriented Threads System (DOTS). DOTS is a paralleliza-tion platform that enables the programmer to build dis-tributed parallel applications using a high level and easy-to-use parallel programming ..."
Abstract - Cited by 6 (6 self) - Add to MetaCart
This paper deals with high performance computing in heterogeneous clusters using the Distributed Object-Oriented Threads System (DOTS). DOTS is a paralleliza-tion platform that enables the programmer to build dis-tributed parallel applications using a high level and easy-to-use parallel programming

A proposal for a heterogeneous cluster ScaLAPACK (dense linear solvers)

by Olivier Beaumont, Vincent Boudet, Antoine Petitet, Fabrice Rastello, Yves Robert , 2001
"... In this paper, we study the implementation of dense linear algebra kernels, such as matrix multiplication or linear system solvers, on heterogeneous networks of workstations. The uniform block-cyclic data distribution scheme commonly used for homogeneous collections of processors limits the perform ..."
Abstract - Cited by 59 (24 self) - Add to MetaCart
In this paper, we study the implementation of dense linear algebra kernels, such as matrix multiplication or linear system solvers, on heterogeneous networks of workstations. The uniform block-cyclic data distribution scheme commonly used for homogeneous collections of processors limits

port Vector Machines, Kernel Fisher Discriminant analysis

by Sebastian Mika, Koji Tsuda
"... Abstract | This review provides an introduction to Sup- ..."
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Abstract | This review provides an introduction to Sup-

Local Coding Based Matching Kernel Method for Image Classification

by Yan Song, Ian Vince Mcloughlin, Li-rong Dai , 2014
"... This paper mainly focuses on how to effectively and efficiently measure visual similarity for local feature based representation. Among existing methods, metrics based on Bag of Visual Word (BoV) techniques are efficient and conceptually simple, at the expense of effectiveness. By contrast, kernel b ..."
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or between features and their reconstruction. Generally, local kernels are defined using Euclidean distance or its derivatives, based either explicitly or implicitly on an assumption of Gaussian noise. However, local features such as SIFT and HoG often follow a heavy-tailed distribution which tends
Results 1 - 10 of 128