The Experts below are selected from a list of 2373 Experts worldwide ranked by ideXlab platform

Yuan Wanlian - One of the best experts on this subject based on the ideXlab platform.

  • the use of Inline Function in c
    Journal of Suzhou College, 2006
    Co-Authors: Yuan Wanlian
    Abstract:

    This paper analyses the difference between Inline Function and Function, the difference between Inline Function and macro, and the limit to the use of Inline Function and macro. Moreover, this paper illuminates how to use Inline Function in class.

Amit Somani - One of the best experts on this subject based on the ideXlab platform.

  • A Study and Analysis of Function Inlining
    2007
    Co-Authors: Prasad Deshpande, Amit Somani
    Abstract:

    Function inlining is a widely known technique which has been used to improve program performance. Inlining replaces a Function call by the body of the Function. In this report, we study the effects of Inline Function expansion by observing the empirical behavior of a set of C and C++ programs. Our results indicate that for the average C program improvements in timings due to inlining are not much (2-3%). However, C++ programs benefit much more (up to 46%) from inlining due to smaller average Function size and a larger call stack depth. 1 Introduction Almost all programs are typically written as a collection of smaller computing units (procedures or Functions) to aid program development. However, Function invocation in a program has an associated overhead which might affect the execution time of the program. It also affects compile time optimizations like register allocation, dead code elimination, common subexpression elimination, constant propagation etc. Besides, conservative assump..

Prasad Deshpande - One of the best experts on this subject based on the ideXlab platform.

  • A Study and Analysis of Function Inlining
    2007
    Co-Authors: Prasad Deshpande, Amit Somani
    Abstract:

    Function inlining is a widely known technique which has been used to improve program performance. Inlining replaces a Function call by the body of the Function. In this report, we study the effects of Inline Function expansion by observing the empirical behavior of a set of C and C++ programs. Our results indicate that for the average C program improvements in timings due to inlining are not much (2-3%). However, C++ programs benefit much more (up to 46%) from inlining due to smaller average Function size and a larger call stack depth. 1 Introduction Almost all programs are typically written as a collection of smaller computing units (procedures or Functions) to aid program development. However, Function invocation in a program has an associated overhead which might affect the execution time of the program. It also affects compile time optimizations like register allocation, dead code elimination, common subexpression elimination, constant propagation etc. Besides, conservative assump..

Wang Deqing - One of the best experts on this subject based on the ideXlab platform.

  • design and exploitation for matrix class procedure in element stiffness calculation
    Forging and Stamping Technology, 2008
    Co-Authors: Wang Deqing
    Abstract:

    In finite element software exploitation,the reuse and the efficiency of program modules are two key issues which affect the software performance.In order to resolve reuse problems,object-oriented language can be used to develop finite element stiffness matrix calculation procedures.Using reference variable,dynamic memory allocation Function-calloc Function and Inline Function can increase the efficiency of element matrix calculation.Element stiffness matrix which was compiled by using C++ language was introduced.Compared with finite element program with traditional fortran language,the program with OOP has predominance of high speed in program running,convenience in maintenance and easily realizing coexisting of various kinds of elements.It is effective for large scale finite element program design.Finally,through the use of comparative examples,the efficiency of this kind of matrix was illustrated.

Ábel Vértesy - One of the best experts on this subject based on the ideXlab platform.

  • RoxygenReady: Create Roxygen skeletons for all of your Functions before compiling it into an R package.
    2018
    Co-Authors: Ábel Vértesy
    Abstract:

    Create Roxygen skeletons for all of your Functions before compiling it into an R package. Roxygen2 is an awesome tool to easily create a package from your Function library. RoxygenReady helps in creating the Function annotations needed to compile a proper package by Roxygen2. More precisely, RoxygenReady creates Roxygen skeletons, a certain format for Inline Function annotation (see below). By so, it spares you a lot of time documenting your Functions easily and precisely. The annotation skeleton it creates, can be automatically compiled into a package with a few lines of code. Packages are the standard way of distribution R code, as they integrate with other services, code sharing becomes much easier. See the installation section for an example. You can pass a whole file to RoxygenReady, and it will create Roxygen skeletons for all Functions defined in the file!   Installation and Usage Install directly from GitHub via devtools with one R command: devtools::install_github(repo = "vertesy/RoxygenReady/RoxygenReady") ...then simply load the package: require("RoxygenReady") and create Roxygen skeletons for your Functions RoxygenReady("Path/to/your/script.r")   Workflow Explained: a streamlined package creation 1. You start out with your .R file containing your favorite Functions. print11more