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Adaptive Code Collage: A Framework to Transparently Modify scientific Codes

COMPUTING IN SCIENCE & ENGINEERING 2012年第1期14卷 52-63页

作者： Kang, Pilsung Ramakrishnan, Naren Ribbens, Calvin J. Varadarajan, Srinidhi Heffner, Michael A. Virginia Tech Dept Comp Sci Blacksburg VA 24061 USA Virginia Tech Ctr High End Comp Syst Blacksburg VA 24061 USA

Legacy scientific codes are often repurposed to fit adaptive needs, but making such code adaptive without changing the original source programs can be challenging. Adaptive Code Collage (ACC) meets this challenge using function-call interception in a language-neutral way at link time, transparently "catching" and redirecting function calls.

关键词： Adaptation model Encoding Heuristic algorithms scientific computing scientific software adaptation Software algorithms function-call interception program modification scientific programming

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Pythran: Crossing the Python Frontier

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COMPUTING IN SCIENCE & ENGINEERING 2018年第2期20卷 83-89页

作者： Guelton, Serge Inst Mines Telecom Bretagne Plouzane France

Use of the Python language in scientific computing has always been characterized by the coexistence of interpreted Python code and compiled native code, written in languages like C or Fortran. This column takes a fresh look at the problem and introduces Pythran, a new optimization tool designed to efficiently handle unmodified Python code.

关键词： FORTRAN Object Oriented programming Program Compilers Program Interpreters Pythran Unmodified Python Code Python Language scientific Computing Interpreted Python Code Compiled Native Code Optimization C Languages programming scientific Computing Program Processors scientific programming scientific Computing Pythran Python Coding

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Grid-based state space exploration for molecular binding

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CANADIAN JOURNAL OF CHEMISTRY 2023年第9期101卷 710-724页

作者： Zupan, Hana Heinz, Frederick Keller, Bettina G. Free Univ Berlin Dept Biol Pharm Chem Arnimallee 22 D-14195 Berlin Germany

Binding processes are difficult to sample with molecular dynamics (MD) simulations. In particular, the state space exploration is often incomplete. Evaluating the molecular interaction energy on a grid circumvents this problem but is heavily limited by state space dimensionality. Here, we make the first steps towards a low-dimensional grid-based model of molecular binding. We discretize the state space of relative positions and orientations of the two molecules under the rigid body assumption. The corresponding program is published as the Python package molgri. For the rotational component of the grids, we test algorithms based on Euler angles, polyhedra and quaternions, of which the polyhedra-based are the most uniform. The program outputs a sequence of molecular structures that can be easily processed by standard MD programs to calculate grid point energies. We demonstrate the grid-based approach on two molecular systems: a water dimer and a coiled-coil protein interacting with a chloride anion. For the second system we relax the rigid-body assumption and improve the accuracy of the grid point energies by an energy minimization. In both cases, oriented bonding patterns and energies confirm expectations from chemical intuition and MD simulations. We also demonstrate how analysis of energy contributions on a grid can be performed and demonstrate that electrostatically driven association is sufficiently resolved by point-energy calculations. Overall, grid-based models of molecular binding are potentially a powerful complement to molecular sampling approaches, and we see the potential to expand the method to quantum chemistry and flexible docking applications.

关键词： molecular association state space discretization rotation grids scientific programming coiled-coils

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GENERAL-RELATIVISTIC VISUALIZATION

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COMPUTING IN SCIENCE & ENGINEERING 2011年第6期13卷 64-71页

作者： Mueller, Thomas Weiskopf, Daniel Univ Stuttgart D-7000 Stuttgart Germany

General-relativistic visualization helps us understand what we could see when massive objects curve spacetime.

关键词： Data visualization General relativity Mathematical model Visualization data visualisation diagrams general-relativistic visualization general-relativistic visualization graphics software massive object scientific programming spacetime visualization

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PUTTING A SLUG TO WORK

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COMPUTING IN SCIENCE & ENGINEERING 2009年第2期11卷 62-68页

作者： Laeufer, Konstantin Thiruvathukal, George K. Nishimura, Ryohei Martinez-Eiroa, Carlos Ramirez Loyola Univ Chicago IL 60611 USA

Although novel architectures such as cell processors, graphics processors, and FPGAs are growing in popularity, conventional microprocessor designs pack a punch in a small footprint and are widely supported by commodi... 详细信息

关键词： scientific programming Slug NSLU 2 Embedded Systems Distributed Systems

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MATLAB-like scripting of Java scientific libraries in ScalaLab

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scientific programming 2014年第3期22卷 187-199页

作者： Papadimitriou, Stergios Mavroudi, Seferina Theofilatos, Kostas Likothanasis, Spiridon Technol Educ Inst Eastern Macedonia & Thrace Dept Comp & Informat Engn Kavala 65404 Greece Univ Patras Dept Comp Engn & Informat GR-26110 Patras Greece Greece Technol Educ Inst Patras Technol Educ Inst Patras Sch Sci Hlth & Care Dept Social Work Patras Greece

Although there are a lot of robust and effective scientific libraries in Java, the utilization of these libraries in pure Java is difficult and cumbersome, especially for the average scientist that does not expertise in software development. We illustrate that ScalaLab presents an easier and productive MATLAB like front end. Also, the main strengths and weaknesses of the core Java libraries of ScalaLab are elaborated. Since performance is of paramount importance for scientific computation, the article discusses extensively performance aspects of the ScalaLab environment. Also, Java bytecode performance is compared to native code.

关键词： Java Scala functional programming scripting interpreters MATLAB scientific programming

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Matplotlib: A 2D graphics environment

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COMPUTING IN SCIENCE & ENGINEERING 2007年第3期9卷 90-95页

作者： Hunter, John D. Tradelink

Matplotlib is a 2D graphics package used for Python for application development, interactive scripting, and publication-quality image generation across user interfaces and operating systems.

关键词： Python Scripting Languages Application Development scientific programming

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The software architecture for performing scientific computation with the JLAPACK libraries in ScalaLab

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scientific programming 2012年第4期20卷 379-391页

作者： Papadimitriou, Stergios Mavroudi, Seferina Theofilatos, Kostas Likothanasis, Spiridon Technol Educ Inst Kavala Dept Informat Management Kavala 65404 Greece Univ Patras Dept Comp Engn & Informat Patras Greece Technol Educ Inst Patras Sch Sci Hlth & Care Dept Social Work Patras Greece

Although LAPACK is a powerful library its utilization is difficult. JLAPACK, a Java translation obtained automatically from the Fortran LAPACK sources, retains exactly the same difficult to use interface of LAPACK routines. The MTJ library implements an object oriented Java interface to JLAPACK that hides many complicated details. ScalaLab exploits the flexibility of the Scala language to present an even more friendly and convenient interface to the powerful but complicated JLAPACK library. The article describes the interfacing of the low-level JLAPACK routines within the ScalaLab environment. This is performed rather easily by exploiting well suited features of the Scala language. Also, the paper demonstrates the convenience of using JLAPACK routines for linear algebra operations from within ScalaLab.

关键词： Java Scala functional languages scripting interpreters MATLAB scientific programming class loaders binding

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COMPOSABLE PARALLEL PATTERNS WITH INTEL CILK PLUS

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COMPUTING IN SCIENCE & ENGINEERING 2013年第2期15卷 66-+页

作者： Robison, Arch D. Univ Leicester Dept Engn Leicester LE1 7RH Leics England

Intel Cilk Plus extends C and C++ to enable writing composable deterministic parallel software that can exploit both the thread and vector parallelism commonly available in modern hardware.

关键词： Parallel Processing Vectors Message Systems Program Processors programming scientific Computing scientific programming Parallel programming Thread Parallelism Vector Parallelism Intel Cilk Plus Open MP

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The NumPy Array: A Structure for Efficient Numerical Computation

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COMPUTING IN SCIENCE & ENGINEERING 2011年第2期13卷 22-30页

作者： van der Walt, Stefan Colbert, S. Chris Varoquaux, Gael Univ Stellenbosch ZA-7600 Stellenbosch South Africa Enthought Inc Austin TX USA INRIA Le Chesnay France

In the Python world, NumPy arrays are the standard representation for numerical data and enable efficient implementation of numerical computations in a high-level language. As this effort shows, NumPy performance can be improved through three techniques: vectorizing calculations, avoiding copying data in memory, and minimizing operation counts.

关键词： Arrays Computational efficiency Finite element methods NumPy Numerical analysis Performance evaluation Python Python programming language Resource management Vector quantization data structures high level language high level languages mathematics computing numerical analysis numerical computation numerical computations numerical data numpy array programming libraries scientific programming

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