The substantiation is given of the need to develop the scientific works on the regular generalization of hydrological characteristics in the Russian Federation by means of the preparation of scientific and applied ref...
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The substantiation is given of the need to develop the scientific works on the regular generalization of hydrological characteristics in the Russian Federation by means of the preparation of scientific and applied reference books and/or Territorial Construction Standards on the Determination of Basic Design Hydrological Characteristics on the territory of responsibility of the Territorial Administrations for Hydrometeorological and Environmental Monitoring (TAHEMs) of Roshydromet. The methodology, technical support, and the need in the regular recomputation of maximum design water discharges for operating hydraulic structures are considered. The ways of solution of the major current problem in the field of engineering hydrological computations on the territorial generalization of hydrometeorological information in all TAHEMs and in the State Hydrological Institute are outlined.
computational methods are an integral part of most scientific disciplines and a rudimentary understanding of their potential and limitations is essential for any scientist or engineer. This textbook introduces computa...
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ISBN:
(数字)9781611976724
ISBN:
(纸本)9781611976717
computational methods are an integral part of most scientific disciplines and a rudimentary understanding of their potential and limitations is essential for any scientist or engineer. This textbook introduces computational science through a set of methods and algorithms with the aim of familiarizing the reader with the field's theoretical foundations and providing the practical skills to use and develop computational methods.
Methods in computational Science
extends the classical syllabus with new material, including high performance computing, adjoint methods, machine learning, randomized algorithms, and quantum computing;
is centered around a set of fundamental algorithms presented in the form of pseudocode;
presents theoretical material alongside several examples and exercises; and
provides Python implementations of many key algorithms.
With exascale-level computation on the horizon, the art of predicting the cost of computations has acquired a renewed focus. This task is especially challenging in the case of iterative methods, for which convergence ...
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With exascale-level computation on the horizon, the art of predicting the cost of computations has acquired a renewed focus. This task is especially challenging in the case of iterative methods, for which convergence behaviour often cannot be determined with certainty a priori (unless we are satisfied with potentially outrageous overestimates) and which typically suffer from performance bottlenecks at scale due to synchronization cost. Moreover, the amplification of rounding errors can substantially affect the practical performance, in particular for methods with short recurrences. In this article, we focus on what we consider to be key points which are crucial to understanding the cost of iteratively solving linear algebraic systems. This naturally leads us to questions on the place of numerical analysis in relation to mathematics, computer science and sciences, in general. This article is part of a discussion meeting issue 'Numerical algorithms for high-performance computational science'.
Recently some scientific computing users have discovered that they can replace 64-bit with 32-bit operations for carefully selected portions of the computation, and still retain acceptable accuracy in the final result...
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Recently some scientific computing users have discovered that they can replace 64-bit with 32-bit operations for carefully selected portions of the computation, and still retain acceptable accuracy in the final results. In addition, developers of some emerging applications such as machine learning have discovered that they can achieve acceptable results with only 16-bit precision in certain portions of the code. At the other end of the precision spectrum, some users have explored using 128-bit arithmetic in some particularly demanding applications, while others have done computations using much higher precision-hundreds or even thousands of digits. Such work has underscored the need to develop new mathematical and software frameworks to support a dynamically variable level of precision, and, more generally, to rethink what "reproducibility" means in a variable precision environment. This article summarizes some of the work being done in this arena, and lists research problems that need to be solved.
It is computationally advantageous to solve a finite-difference approximation to Poisson’s equation ∇⋅(σ∇P)<span class="mo" id="MathJax-Span-10" style="font-family: MathJax_Mai
In the present paper, a general class of linear functional equations is considered and a computer program is described, which determines the exact solutions of systems of equations belonging to this class.
In the present paper, a general class of linear functional equations is considered and a computer program is described, which determines the exact solutions of systems of equations belonging to this class.
Literate computing has emerged as an important tool for computational studies and open science, with growing folklore of best practices. In this work, we report two case studies-one in computational magnetism and anot...
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Literate computing has emerged as an important tool for computational studies and open science, with growing folklore of best practices. In this work, we report two case studies-one in computational magnetism and another in computational mathematics-where domain-specific software was exposed to the Jupyter environment. This enables high level control of simulations and computation, interactive exploration of computational results, batch processing on HPC resources, and reproducible workflow documentation in Jupyter notebooks. In the first study, Ubermag drives existing computational micromagnetics software through a domain-specific language embedded in Python. In the second study, a dedicated Jupyter kernel interfaces with the GAP system for computational discrete algebra and its dedicated programming language. In light of these case studies, we discuss the benefits of this approach, including progress toward more reproducible and reusable research results and outputs, notably through the use of infrastructure such as JupyterHub and Binder.
Abstract: A basic result of Haber and Levinson which describes the behavior of solutions of $\varepsilon y'' = f(t,y,y’)$,$a < t < b$,$y(a,\varepsilon )$,$y(b,\varepsilon )$, prescribed,...
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Abstract: A basic result of Haber and Levinson which describes the behavior of solutions of $\varepsilon y'' = f(t,y,y’)$,$a < t < b$,$y(a,\varepsilon )$,$y(b,\varepsilon )$, prescribed, in the presence of a reduced solution with corners is modified to treat related classes of problems. Under various stability assumptions, solutions are shown to remain, for small $\varepsilon > 0$, in a o(l)-neighborhood of an angular reduced solution with the possible exception of narrow layers near the boundaries in some cases. Each aspect of the theory developed here is illustrated by several examples.
Time series data in DEA often represent successive versions of the same unit (DMU). In order to assess efficiency of each DMU, several DEA techniques have been employed. One of the problems that conventional DEA model...
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Time series data in DEA often represent successive versions of the same unit (DMU). In order to assess efficiency of each DMU, several DEA techniques have been employed. One of the problems that conventional DEA models face is that the reference set, when dealing with time series data, is not constructed correctly. This is attributed to the fact that conventional DEA models examine the DMUs and extract their efficiency scores based only the spatial dimension. However, when dealing with time series data for DMUs in the DEA context, the temporal dimension should be also taken into account. This paper is based on Spatio-Temporal DEA (ST-DEA) model (Petridis et al. in Ann Oper Res 238(1-2):475-496, 2016) and extends the presented S-T DEA model by incorporating undesirable inputs/outputs. A GAMS representation of the model for the solution and explanation of ST-DEA model is shown through an illustrative example. The scope of the paper is to analyze the concept of ST-DEA model and demonstrate its applicability via an application explained in GAMS optimization software.
A lovely circle of ideas due primarily to Shub, Smale and Shamir says that if it is possible to divide quickly, then it is possible to factor quickly. Here, dividing quickly means modular division over a straight line...
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A lovely circle of ideas due primarily to Shub, Smale and Shamir says that if it is possible to divide quickly, then it is possible to factor quickly. Here, dividing quickly means modular division over a straight line program. In this context, quickly means actual computations done quickly. The point of this note is to advertise this lovely circle of ideas. The language of complexity theory sometimes clouds the underlying simplicity of the ideas. It is our hope to provide a straight forward explanation of these intrinsically simple ideas.
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