Analytical Performance Prediction on MulticomputersMark

Supercomputing ' 93 " Analytical Performance Prediction on MulticomputersMark

Multicomputers have the potential to deliver Gi-gaaop performance on many scientiic applications. Initial implementations of parallel programs on these machines, however, are often ineecient and require signiicant optimization before they can harness the potential power of the machine. Performance prediction tools can provide valuable information on which optimizations will result in increased ...

Performance of a Two-stages Gas Gun: Experimental, Analytical and Numerical Analysis

Two stages gas guns are used for various purposes, particularly for mechanical characterization of materials at high rate of deformations. The performance of a two stages gas gun is studied in this work using the theory of the two-stage gas gun proposed by Rajesh, numerical simulation using combined Eulerian/ Lagrangian elements in Autodyna commercial code and experiment using a two stage gas g...

A Review on Application of Soft Computing Techniques & Analytical Techniques in Machining Performance Prediction and Optimization under MQL

Prediction of Noise Transmission Loss and Acoustic Comfort Assessment of a Ventilated Window using Statistical Energy Analysis

In this paper, a novel analytical method was developed based on statistical energy analysis framework to evaluate sound transmission loss through ventilated windows. The proposed method was compared to numerical and analytical models available in the literature. Results showed the success and advantage of the proposed model in predicting the acoustic performance of the ventilated window and the...

Separating Well Log Data to Train Support Vector Machines for Lithology Prediction in a Heterogeneous Carbonate Reservoir

The prediction of lithology is necessary in all areas of petroleum engineering. This means that to design a project in any branch of petroleum engineering, the lithology must be well known. Support vector machines (SVM’s) use an analytical approach to classification based on statistical learning theory, the principles of structural risk minimization, and empirical risk minimization. In this res...