Intel Visual Fortran Compiler 11.1.067(Windows) & Fortran Compiler 11.1.073(Linux) Professional Edition

Intel Visual Fortran Compiler 11.1.067(Windows) & Fortran Compiler 11.1.073(Linux) Professional EditionГод выпуска: 2010

Платформа: Windows XP и старше(x86)/Linux(x86/x64)

Системные требования:1GB RAM, 2GB HDD

: Intel Fortran Compiler — оптимизирующий компилятор Фортрана, разрабатываемый компанией Intel для своих процессоров архитектур x86, x86-64, IA-64. Генерирует наиболее быстрый код для этих процессоров

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Каждая программа, включая Intel Visual Fortran Compiler 11.1.067(Windows) & Fortran Compiler 11.1.073(Linux) Professional Edition содержит в себе проверенный кейген (в народе кряк, патч) или серийник (ключ). Так же таблетка может быть уже «вшита» в софт.

Перед установкой любого взломаного софта вы должны понимать, что несете полную ответственность за свой ПК и возможный ущерб, который могут нанести крякнутые программы. Хоть мы стараемся удалять такие раздачи, но 100% гарантии нет.

Если вам понравилась программа или вы заработали на ней деньги, не поленитесь купить официальную версию. Это поможет сделать ее еще лучше + вы получите техническую поддержку и самые свежие обновления.

To x64 or not to x64: Installing a 64-bit fortran compiler

Current day computers generally have 64-bit processors, and most even have 64-bit operating systems. On such systems, 32-bit programs will run fine, but 64-bit programs can make more efficient use of the underlying system. When we installed a fortran compiler and the code::blocks IDE, the default fortran compiler generated 32-bit programs. This generally is not an issue, unless you need a large amount of memory, for example to store a temporary array with 400 3 double precision coordinates (as I did for a project I’m currently working on). You may first start to look for ways of increasing the stack-size of your program, but you will soon discover that the problem is more profound: a 32-bit program cannot access address spacing beyond 4Gb. (In practice, generally you will not even reach 4Gb before running into problems.) This is because the memory address of your data is stored as a 32-bit value (2 32 = 4 294 967 296 = 4Gb) so the only way out of this predicament is a “larger address” aka 64-bit. So you need to install a new compiler capable of providing 64-bit programs.

Legend : Menu-paths / Important / Errors

A. Installing MingW64 for code::blocks

i. Installing the compiler

A common suggestion for installing a 64bit version of gfortran is the use of the TDM-GCC MingW compiler-installer. It is true that the installation runs very smoothly (and I would suggest it for this reason alone). Unfortunately the most recent gcc version available (at the time of writing this blogpost) was gcc-5.1.0 which gives rather nasty segmentation faults when trying to compile and test Lapack under windows. Luckily, this problem is resolved for gcc-5.3.0, so we will be getting this one instead. (Once TDM catches up to gcc-5.3 I suggest getting that one instead.)

• Go to the Gfortran compiler website: https://gcc.gnu.org/wiki/GFortran
• Under Quick Links follow the link Binaries for windows
• Under Windows follow the link snapshots under MinGW64 for Win64
• And then I followed the path Toolchains targetting Win64 >Personal Builds >mingw-builds >5.3.0 >threads-posix >seh . Of course you could follow any of the other paths as well. My choice was mainly based on the large number of downloads of this version.
• Just unzip the folders in the location of your choice, et voilà, the compiler has been installed.

ii. Setting the PATH-variable (Win10)

Now you need to make sure your operating system can also find the installed compiler and tool-chain. As such you will need to add the location of the new compiler to the PATH environment variable. In Windows 10 open the control panel (do a search for “control panel”, it is easier than finding out the place it is hidden), follow System and Security > System > Advanced System Settings in the tab advanced click Environment Variables , and now you can modify the PATH variable by adding the location of the minGW bin folder (the one in which you find x86_64-w64-mingw32-gfortran.exe).

iii. Adding the compiler to Code::Blocks

In this third and final step, we need to setup the compiler in code::blocks. For this you follow Settings > Compiler . Select the compiler you usually use for your 32-bit fortran programs and press copy. Give the new compiler a suitable name. By performing this copy, you have also copied all your preferred compiler and linker settings, making it easier to setup the new compiler.

Now select Toolchain Executables , enter the path to the minGW64 installation and set the compilers and linker to x86_64-w64-mingw32-gfortran.exe. (Don’t use gfortran.exe as this might lead to confusion, both for yourself and the IDE.) In addition, set the ar-tool to x86_64-w64-mingw32-gcc-ar.exe, otherwise the compiler will not be able to link libraries made with this 64-bit compiler. Furthermore, under the tab compiler settings in the tab Other compiler options add the -m64 flag.

Finally, you may also want to update possible libraries in the linker settings tab (think for example of libgomp.dll.a if you use openmp for parallelisation).

At this point you can compile and run your fortran code using this compiler. The resulting 64-bit programs will now be able to access more than 2-4Gb of memory, and might turn out to run faster if you use much double precision arithmetic.

B. Upgrading Lapack to 64-bit

Installing Lapack on a Windows OS is a bit of a pickle, as this OS is generally not used for scientific computational work. As a result, the standard fortran compilation procedure is aimed at unix-based systems (i.e. makefiles to be run from the commandline). Luckily there exists a simple procedure for installing Lapack on a windows machine, which can be found here. [local copy of the procedure (50KB)][local copy of Lapack 3.4.0 source (6MB)]

The procedure consists of a pair of batch files streamlining the installation. The only thing you will have to do is tweak the make.inc file included with the procedure (cf. highlighted lines).

• -m64 : This compiler flag makes sure you get 64-bit code. Trying to link a 32-bit version of Lapack in your 64-bit code will give problems.
• x86_64-w64-mingw32-gfortran.exe : use the explicit name of the 64-bit compiler, not the generic “gfortran”. This will prevent the make-program of accidentally using the wrong version when multiple versions are installed. When they are all included in the windows PATH variable, the make-program will just use the first one it encounters. (Use gfortran -v in the Command Prompt to find out which version is your current default.) Not using the explicit name may result in the following error message: “ gfortran: error: CreateProcess: No such file or directory “ when running makelibs.bat.
• x86_64-w64-mingw32-gcc-ar.exe & x86_64-w64-mingw32-gcc-ranlib.exe : You also need to make sure that you are using the 64-bit versions of the ar-program and the ranlib-program which combine the compiled objects into an archive, i.e. dll-file. When you use the default “ar” and “ranlib” you may end up seeing the error message : ” could not read symbols: Archive has no index; run Ranlib to add one “ , when trying to run the library-tests through testlibs.bat.
• Use gcc-5.3 : While running the testlibs.bat script, I also ran into segmentation faults during the tests of level-2 and level-3 BLAS. This ended up probably being due to the use of gcc-5.1. After upgrading to minGW64 of gcc-5.3 this problem was resolved.

With everything fixed, and all problems circumvented, I now have the means to perform my calculations using the temporary 400 3 double precision coordinate grid on my sidekick.

Intel® Fortran Compiler

Build applications that can scale for the future with optimized code designed for Intel® architecture.

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The Intel® Fortran Compiler is built on a long history of generating optimized code that supports industry standards while taking advantage of built-in technology for Intel® Xeon® Scalable processors and Intel® Core™ processors. Staying aligned with Intel’s evolving and diverse architectures, the compiler now supports GPUs.

Standards: The Path Forward

There are two versions of this compiler.

Intel® Fortran Compiler(Beta): provides CPU and GPU offload support of GPUs

Intel® Fortran Compiler Classic: provides continuity with existing CPU-focused workflows

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• Leverages well-proven LLVM compiler technology † and Intel’s history of compiler leadership

†Initial support available in Intel® Fortran Compiler(Beta)

• Takes advantage of multicore, Single Instruction Multiple Data (SIMD) vectorization, and multiprocessor systems with OpenMP, automatic parallelism, and coarrays
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Benchmarks

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Use the Latest Intel® Hardware

• Intel® Xeon® Scalable processors
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Documentation & Code Samples

Specifications

Intel Fortran Compiler(Beta)

• Intel® Core™ processors
• Intel® Xeon® processor family
• Intel® Xeon Scalable processors

• Intel® Processor Graphics Gen9 and above
• X e architecture

• Intel® Programmable Acceleration Card with Intel® Arria® 10 GX FPGA

Host and target operating systems:

• Fortran – Full 77, 90, 95, and partial 2003

†† OpenMP host and offload support available only in Intel Fortran Compiler(Beta)

For more information, see the system requirements.

Intel Fortran Compiler Classic

• Intel® Core™ processors
• Intel® Xeon® processor family
• Intel® Xeon Scalable processors

Host and target operating systems:

• Fortran – Full 77, 90, 95, 2003, 2008, and 2018

†† OpenMP host support available only

For more information, see the system requirements.

Get the Single Component

A stand-alone version of this component is available.

Get Help

Your success is our success. Access these support resources when you need assistance.

For additional help, see our general oneAPI Support.

Related Products

The Intel® oneAPI DPC++/C++ Compiler is a standards-based, cross-architecture compiler that builds high-performance applications by generating optimized code for Intel® Xeon® Scalable processors, Intel® Core™ processors, and supported XPUs. It allows you to:

• Support open standards of C, C++, SYCL, and OpenMP*
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Customer Testimonials

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— José Alberto Morales de los Ríos Pappa, electronics and software developer for the infrared (IR) camera in the Extreme Universe Space Observatory Onboard Japanese Experiment Module (JEM-EUSO) mission, Math and Physics Department, University of Alcalá