与c#和Java相比,编译c++文件需要很长时间。编译一个c++文件比运行一个正常大小的Python脚本花费的时间要长得多。我目前使用vc++,但它与任何编译器是一样的。为什么会这样?
我能想到的两个原因是加载头文件和运行预处理器,但这似乎不能解释为什么需要这么长时间。
与c#和Java相比,编译c++文件需要很长时间。编译一个c++文件比运行一个正常大小的Python脚本花费的时间要长得多。我目前使用vc++,但它与任何编译器是一样的。为什么会这样?
我能想到的两个原因是加载头文件和运行预处理器,但这似乎不能解释为什么需要这么长时间。
当前回答
我能想到有两个问题可能会影响c++程序的编译速度。
POSSIBLE ISSUE #1 - COMPILING THE HEADER: (This may or may not have already been addressed by another answer or comment.) Microsoft Visual C++ (A.K.A. VC++) supports precompiled headers, which I highly recommend. When you create a new project and select the type of program you are making, a setup wizard window should appear on your screen. If you hit the “Next >” button at the bottom of it, the window will take you to a page that has several lists of features; make sure that the box next to the “Precompiled header” option is checked. (NOTE: This has been my experience with Win32 console applications in C++, but this may not be the case with all kinds of programs in C++.)
POSSIBLE ISSUE #2 - THE LOCATION BEING COMPILED TO: This summer, I took a programming course, and we had to store all of our projects on 8GB flash drives, as the computers in the lab we were using got wiped every night at midnight, which would have erased all of our work. If you are compiling to an external storage device for the sake of portability/security/etc., it can take a very long time (even with the precompiled headers that I mentioned above) for your program to compile, especially if it’s a fairly large program. My advice for you in this case would be to create and compile programs on the hard drive of the computer you’re using, and whenever you want/need to stop working on your project(s) for whatever reason, transfer them to your external storage device, and then click the “Safely Remove Hardware and Eject Media” icon, which should appear as a small flash drive behind a little green circle with a white check mark on it, to disconnect it.
我希望这对你有帮助;如果有,请告诉我!:)
其他回答
一些原因是:
1) c++语法比c#或Java更复杂,需要更多的时间来解析。
2)(更重要的是)c++编译器生成机器代码,并在编译期间进行所有优化。c#和Java只走了一半,将这些步骤留给JIT。
我能想到有两个问题可能会影响c++程序的编译速度。
POSSIBLE ISSUE #1 - COMPILING THE HEADER: (This may or may not have already been addressed by another answer or comment.) Microsoft Visual C++ (A.K.A. VC++) supports precompiled headers, which I highly recommend. When you create a new project and select the type of program you are making, a setup wizard window should appear on your screen. If you hit the “Next >” button at the bottom of it, the window will take you to a page that has several lists of features; make sure that the box next to the “Precompiled header” option is checked. (NOTE: This has been my experience with Win32 console applications in C++, but this may not be the case with all kinds of programs in C++.)
POSSIBLE ISSUE #2 - THE LOCATION BEING COMPILED TO: This summer, I took a programming course, and we had to store all of our projects on 8GB flash drives, as the computers in the lab we were using got wiped every night at midnight, which would have erased all of our work. If you are compiling to an external storage device for the sake of portability/security/etc., it can take a very long time (even with the precompiled headers that I mentioned above) for your program to compile, especially if it’s a fairly large program. My advice for you in this case would be to create and compile programs on the hard drive of the computer you’re using, and whenever you want/need to stop working on your project(s) for whatever reason, transfer them to your external storage device, and then click the “Safely Remove Hardware and Eject Media” icon, which should appear as a small flash drive behind a little green circle with a white check mark on it, to disconnect it.
我希望这对你有帮助;如果有,请告诉我!:)
c++被编译成机器代码。所以你有预处理器,编译器,优化器,最后是汇编器,所有这些都必须运行。
Java和c#被编译成字节码/IL, Java虚拟机/。NET框架执行(或JIT编译成机器代码)之前执行。
Python是一种解释型语言,它也被编译成字节码。
我相信还有其他原因,但总的来说,不需要编译为本机机器语言可以节省时间。
任何编译器的减速都不一定相同。
我没有使用过Delphi或Kylix,但在MS-DOS时代,Turbo Pascal程序几乎可以立即编译,而等效的Turbo c++程序只能爬行。
两个主要的区别是一个非常强大的模块系统和允许单次编译的语法。
编译速度当然可能不是c++编译器开发人员的优先考虑事项,但C/ c++语法中也有一些固有的复杂性,这使得处理起来更加困难。(我不是C方面的专家,但Walter Bright是,在构建了各种商业C/ c++编译器之后,他创建了D语言。他的改变之一是强制使用上下文无关的语法,使语言更容易解析。)
此外,您还会注意到,makefile通常设置为每个文件都单独用C编译,因此如果10个源文件都使用相同的包含文件,则该包含文件将被处理10次。
构建C/ c++:到底发生了什么,为什么要花这么长时间
相当大一部分软件开发时间不是花在编写、运行、调试甚至设计代码上,而是花在等待代码完成编译上。 为了让事情变得更快,我们首先必须理解编译C/ c++软件时发生了什么。步骤大致如下:
配置 构建工具启动 依赖项检查 编译 链接
现在,我们将更详细地查看每个步骤,重点关注如何使它们更快。
配置
这是开始构建的第一步。通常意味着运行配置脚本或CMake、Gyp、SCons或其他工具。对于非常大的基于autotools的配置脚本,这可能需要一秒钟到几分钟的时间。
这一步很少发生。它只需要在更改配置或更改构建配置时运行。如果不改变构建系统,就没有多少事情可以加快这一步。
构建工具启动
这是在IDE上运行make或单击构建图标(通常是make的别名)时发生的情况。构建工具二进制文件启动并读取其配置文件以及构建配置,这通常是同一件事。
根据构建的复杂性和大小,这可能需要几秒到几秒的时间。这本身并没有那么糟糕。不幸的是,大多数基于make的构建系统在每次构建时都会调用几十到几百次make。这通常是由递归使用make(这是不好的)引起的。
应该注意的是,Make如此缓慢的原因并不是实现错误。Makefiles的语法有一些怪癖,使得真正快速的实现几乎不可能。当与下一步结合使用时,这个问题会更加明显。
依赖项检查
Once the build tool has read its configuration, it has to determine what files have changed and which ones need to be recompiled. The configuration files contain a directed acyclic graph describing the build dependencies. This graph is usually built during the configure step. Build tool startup time and the dependency scanner are run on every single build. Their combined runtime determines the lower bound on the edit-compile-debug cycle. For small projects this time is usually a few seconds or so. This is tolerable. There are alternatives to Make. The fastest of them is Ninja, which was built by Google engineers for Chromium. If you are using CMake or Gyp to build, just switch to their Ninja backends. You don’t have to change anything in the build files themselves, just enjoy the speed boost. Ninja is not packaged on most distributions, though, so you might have to install it yourself.
编译
此时,我们最终调用编译器。省事起见,以下是大致采取的步骤。
合并包括 解析代码 代码生成和优化
与流行的观点相反,编译c++实际上并没有那么慢。STL很慢,大多数用于编译c++的构建工具都很慢。然而,有更快的工具和方法来减轻语言中缓慢的部分。
使用它们需要一些体力,但好处是不可否认的。更快的构建时间会让开发人员更快乐,更敏捷,并最终产生更好的代码。