The performance of direct TCP streaming using analytical models was investigated. It was found that for both constrained and unconstrained streaming, the performance improves as the value of T/μ, where T/μ represent...
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The performance of direct TCP streaming using analytical models was investigated. It was found that for both constrained and unconstrained streaming, the performance improves as the value of T/μ, where T/μ represents how much the achievable TCP throughput is higher than the video playback rate, increases. The performance was found to be sensitive to the values of the various parameters in the models. It was observed that for both constrained and unconstrained streaming, the performance is generally good when the achievable TCP throughput is roughly twice the video bitrate, with only a few seconds of startup delay.
Practicing physical modeling leads to reconsider the relationship with the musical computer, at a conceptual and practical level. This calls for specific learning tools, which fully take into account the specificities...
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Small, portable, and low-cost millimeter wave imaging systems are desired in many nondestructive testing and imaging applications, as these system are capable of producing high-resolution images of interior of composi...
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Recently, research on scheduling for large-scale multiprocessor systems has begun to take into consideration the memory sizes of jobs. The approach used to ensure good performance without considering memory is to incr...
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Recently, research on scheduling for large-scale multiprocessor systems has begun to take into consideration the memory sizes of jobs. The approach used to ensure good performance without considering memory is to increase the multiprogramming level as the load increases. But if jobs require significant amounts of memory, then there will be a point at which the system can no longer fit additional jobs in memory. The scheduler will then have to carefully choose the way it allocates processors to jobs that are running in order to maximize performance. In this paper, we investigate the benefit of having speedup knowledge about individual jobs in making such a choice. We find that if memory sizes and speedup characteristics of jobs are uncorrelated, then there may be moderate benefits in having speedup information, but if large-sized jobs tend to have better speedup than small-sized ones, as might occur in real systems, then much more significant benefits can be obtained. We propose scheduling strategies that exploit speedup information to improve performance, and evaluate them under a variety of workloads.
This paper presents a comparative performance analysis of a wind power generation unit with and without the inclusion of a reactive compensator known as Saturated Core Reactor (SCR) to improve voltage variations resul...
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ISBN:
(纸本)0780387465
This paper presents a comparative performance analysis of a wind power generation unit with and without the inclusion of a reactive compensator known as Saturated Core Reactor (SCR) to improve voltage variations resulting from the wind power. Besides demonstrating the solution efficiency and adequacy for voltage control, the results can also be used to validate the established computational model. Field results, derived from a real system with and without the compensator insertion are given to enhance the overall system/compensator/generators behaviour.
Non-intrusive measures of mental workload signals are desirable, because they minimize artificially introduced noise, and can be more accurate. A new approach for non-intrusive personalized mental workload evaluation ...
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ISBN:
(纸本)9783642028083
Non-intrusive measures of mental workload signals are desirable, because they minimize artificially introduced noise, and can be more accurate. A new approach for non-intrusive personalized mental workload evaluation is presented. Our research results show that human mental workload is unique to each person, non-stationary, and not zero-state.
Numerical simulation of geothermal fields is a very time-consuming task that demands extensive experience. One of the crucial steps in numerical simulation is modeling the natural state of the field before any product...
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Deep embeddings answer one simple question: How similar are two images? Learning these embeddings is the bedrock of verification, zero-shot learning, and visual search. The most prominent approaches optimize a deep co...
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ISBN:
(纸本)9781538610329
Deep embeddings answer one simple question: How similar are two images? Learning these embeddings is the bedrock of verification, zero-shot learning, and visual search. The most prominent approaches optimize a deep convolutional network with a suitable loss function, such as contrastive loss or triplet loss. While a rich line of work focuses solely on the loss functions, we show in this paper that selecting training examples plays an equally important role. We propose distance weighted sampling, which selects more informative and stable examples than traditional approaches. In addition, we show that a simple margin based loss is sufficient to outperform all other loss functions. We evaluate our approach on the Stanford Online Products, CAR196, and the CUB200-2011 datasets for image retrieval and clustering, and on the LFW dataset for face verification. Our method achieves state-of-the-art performance on all of them.
In this study, we refute the popular belief [1,2] that packet processing does not benefit from data-caching. We show that a small data-cache of 8KB can bring down the packet processing time by much as 50-90%, while re...
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In this study, we refute the popular belief [1,2] that packet processing does not benefit from data-caching. We show that a small data-cache of 8KB can bring down the packet processing time by much as 50-90%, while reducing the off-chip memory bandwidth usage by about 60-95%. We also show that, unlike general-purpose computing, packet processing, due to its memory-intensive nature, cannot rely exclusively on data-caching to eliminate the memory bottleneck completely.
The behavioral simulation of large-scale analog circuits is very expensive. Instead of the circuit complex model, reduction of the computing effort implies using a macromodel capable to capture the behaviors of the or...
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ISBN:
(纸本)9781424470198
The behavioral simulation of large-scale analog circuits is very expensive. Instead of the circuit complex model, reduction of the computing effort implies using a macromodel capable to capture the behaviors of the original circuit while preserving its essential properties. Building such a model is based on a simplified and unitary description of the circuit, by establishing a simple relationship between the input/output variables. In this paper, the model order reduction techniques based on method projection in Krylov subspace are presented in two implementation: on state equations and on semi-sate equations of the analog circuits. Illustrative simulations are performed that allow a comparison of the standard methods based on Pack approximation with Krylov subspace methods, and some important conclusions.
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