scholarly journals SST_GPU: An Execution -Driven CUDA Kernel Scheduler and Streaming-Multiprocessor Compute Model.

2019 ◽  
Author(s):  
Mahmoud Khairy ◽  
Mengchi Zhang ◽  
Roland Green ◽  
Simon David Hammond ◽  
Robert J. Hoekstra ◽  
...  
Keyword(s):  
Author(s):  
Jesper N. Wulff

Researchers who model fractional dependent variables often need to consider whether their data were generated by a two-part process. Two-part models are ideal for modeling two-part processes because they allow us to model the participation and magnitude decisions separately. While community-contributed commands currently facilitate estimation of two-part models, no specialized command exists for fitting two-part models with process dependency. In this article, I describe generalized two-part fractional regression, which allows for dependency between models’ parts. I show how this model can be fit using the community-contributed cmp command (Roodman, 2011, Stata Journal 11: 159–206). I use a data example on the financial leverage of firms to illustrate how cmp can be used to fit generalized two-part fractional regression. Furthermore, I show how to obtain predicted values of the fractional dependent variable and marginal effects that are useful for model interpretation. Finally, I show how to compute model fit statistics and perform the RESET test, which are useful for model evaluation.


2011 ◽  
Vol 48 (02) ◽  
pp. 389-403 ◽  
Author(s):  
Peter Tankov

Improved bounds on the copula of a bivariate random vector are computed when partial information is available, such as the values of the copula on a given subset of [0, 1]2, or the value of a functional of the copula, monotone with respect to the concordance order. These results are then used to compute model-free bounds on the prices of two-asset options which make use of extra information about the dependence structure, such as the price of another two-asset option.


Geophysics ◽  
2017 ◽  
Vol 82 (1) ◽  
pp. G1-G21 ◽  
Author(s):  
William J. Titus ◽  
Sarah J. Titus ◽  
Joshua R. Davis

We apply a Bayesian Markov chain Monte Carlo formalism to the gravity inversion of a single localized 2D subsurface object. The object is modeled as a polygon described by five parameters: the number of vertices, a density contrast, a shape-limiting factor, and the width and depth of an encompassing container. We first constrain these parameters with an interactive forward model and explicit geologic information. Then, we generate an approximate probability distribution of polygons for a given set of parameter values. From these, we determine statistical distributions such as the variance between the observed and model fields, the area, the center of area, and the occupancy probability (the probability that a spatial point lies within the subsurface object). We introduce replica exchange to mitigate trapping in local optima and to compute model probabilities and their uncertainties. We apply our techniques to synthetic data sets and a natural data set collected across the Rio Grande Gorge Bridge in New Mexico. On the basis of our examples, we find that the occupancy probability is useful in visualizing the results, giving a “hazy” cross section of the object. We also find that the role of the container is important in making predictions about the subsurface object.


2020 ◽  
Vol 21 (2) ◽  
pp. 373-380
Author(s):  
Jung Ah Yang ◽  
Taejung Park
Keyword(s):  

2020 ◽  
Vol 17 (8) ◽  
pp. 3581-3585
Author(s):  
M. S. Roobini ◽  
Selvasurya Sampathkumar ◽  
Shaik Khadar Basha ◽  
Anitha Ponraj

In the last decade cloud computing transformed the way in which we build applications. The boom in cloud computing helped to develop new software design and architecture. Helping the developers to focus more on the business logic than the infrastructure. FaaS (function as a service) compute model it gave developers to concentrate only on the application code and rest of the factors will be taken care by the cloud provider. Here we present a serverless architecture of a web application built using AWS services and provide detail analysis of lambda function and micro service software design implemented using these AWS services.


2008 ◽  
Vol 4 (S252) ◽  
pp. 419-420
Author(s):  
Hongwei. Ge ◽  
R. F. Webbink ◽  
Z. Han

AbstractWe describe our work on the development and application of a stellar structure code to compute model sequences representing donor stars in interacting binaries subject to rapid (adiabatic) mass-loss. The donor star is assumed to remain in hydrostatic equilibrium, but no heat flow is allowed. These sequences can be used to define bifurcation sequences in close binary evolution, and to circumscribe possible survivors of common envelope evolution.


2021 ◽  
Vol 6 (1) ◽  
pp. 36
Author(s):  
Deddy Kurniawansyah

The purpose of this study to examine (1) how the stages of the production process for “Sale Pisang Product’ that affects the determination of the selling price of Micro, Small, and Medium Enterprises in Banyuwangi? (2) How is the selling price computing model "Banana Sale Products" able to determine a competitive selling price for Micro, Small and Medium Enterprises in Banyuwangi?. This Study used survey, qualitative exploratory and action. The analysis data used triangulation method. The results obtained in this studi is the process of computing the production cost of “Sale Pisang Product” still uses a traditional method, so that the resulting product cost is distorted and the selling price becomes uncompetitive. In fact, the product cost compute model using Time Driven Activity Based Costing provides more accurate and informative information for Micro, Small and Medium Enterprises actors in making decisions such as determining the selling price. The Time Driven Activity Based Costing method is able to reduce costs and increase the net income of each “sale pisang” variant. The contribution of this study is expected to create competitive selling price of “Sale Pisang Product” and improve the economic competitiveness of Kab. Banyuwangi is more dynamic based on the potential of natural resources and local wisdom.


This paper presents the development of automatic control over batch type production in the paint industry. The automation technique for the manufacturing of paint industry is applied wit0068 the help of programmable Logic Controller. In this task, the analytical compute model for optimizing the functions of the volume processing plant is capable of handling all possible decision variables in the setup. The synthesized function is used in a dominant paint construct plant. This workconcentrate plant is a multi-product, batch processing plant, with a ample variety of products, challenge for various process apparatus at the manufacturing site. The plant under consideration working in accordance with the principle of "order-based" production. Therefore, this application can be classified as a short-term organize of a real case multi-product module alter plant


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