#Simply fortran themes how to#
#Simply fortran themes install#
#Simply fortran themes 64 Bit#
#Simply fortran themes code#
#Simply fortran themes Pc#

omp_get_thread_num() : returns the index of the specific thread you are in [0.I[.omp_set_num_threads(I): Sets the number of threads for the openMP parallel section to I.omp_get_num_threads() : returns the number of threads available in a specific section of the code.

#Simply fortran themes code#

omp_get_num_procs() : returns the number of processors your code sees (in hyper-threaded CPU’s this will be double of the actual number of processor cores).

OpenMP contains several functions which allow you to query and set several environment variables (check out these cheat-sheets for OpenMP v3.0 and v4.0). This can be achieved by a use statement: use omp_lib.

#Simply fortran themes 64 Bit#

W here you add the library (generally found in the folder of your compiler…in case of 64 bit compilers, make sure you get the 64 bit version)įinally, you may want to get access to OpenMP functions inside your code. In Code::Blocks go to Settings > Compiler > Linker Settings tab > Link Libraries: add. Secondly, you need to link in the OpenMP library. In Code::Blocks you will find this option under Settings > Compiler > Compiler Settings tab > Compiler Flags tab (If the option isn’t present try adding it to “other compiler options” and hope your compiler recognizes one of the flags). You only need to add a single compiler flag: -fopenmp (gcc/gfortran), -openmp (intel compiler), or -mp (P ortland Group).

#Simply fortran themes install#

Compiler-options and suchĪs most modern fortran compilers also are well aware of openMP (you can check which version of openMP is supported here), you generally will not need to install a new compiler to write parallel fortran code. (It is interesting to note that MPI and OpenMP are inteded for parallel programming in either C, C++ or fortran … a hint that what the important programming languages are.) OpenMP in Fortran: Basics A.

#Simply fortran themes how to#

The OpenMP framework consists of pragma’s (or directives) which can be added in an existing code as comment lines, and tell a compiler knowledgeable of OpenMP how to parallelize the code.

The two frameworks differ significantly in their complexity, fortunately for us, OpenMP is both the easier one, and the one most suited for a modern multi-core computer. The former mainly focuses on shared memory configurations (laptops, desktops, single nodes in a cluster), while the latter focuses of large distributed memory setups (multi-node clusters) and is thus well-suited for creating codes that need to run on hundreds or even thousands of CPU’s. Two commonly used frameworks for this task are OpenMP and MPI. But, there is always a but, even though you now have access to multiple times the processing power of 2005, this does not mean that your own code will be able to use it. Unfortunately there is no simple compiler switch which makes your code parallel (like the -m64 switch which makes your code 64-bit), you have to do this yourself ( the free lunch is over).

Most machines you can get these days have a minimum of 2 cores, with quad-core machines becoming more and more common. Where in 2005 you bought a single CPU with a high clock rate, you now get a machine with multiple cores. If anything, the average clock rate has even decreased to the range 2-3 GHz. As power-consumption grows quadratically with with the clock rate, this means that (1) there is much more heat produced, that needs to be transported away from your CPU (otherwise it get’s destroyed), (2) reducing the clock rate by a factor 2, allows you to power 4 CPU’s at half the clock rate, effectively doubling your calculation power. (There are even more tricks involved in modern CPU’s which crack up performance such that the clock rate isn’t a real measure for performance any longer, and sales people need to learn more new buzzword to sell your computer/laptop 👿 ) Since then, the clock rate has not increased a bit. The machine was advertised as state of the art with a clock rate of a whooping 233 MHz! During the decade that followed, the evolution of the clock rates kept going at a steady pace, until it saturated at about 3-4 GHz(15 times faster than the 233 MHz) around 2005. Even more, Google didn’t even exist before we got our computer, as the company was only founded in 1998 🙂 ). (Yup, I survived my entire high school career searching stuff in the library and the home encyclopedia. My dad got it, because I was going to university, and I would be able to do something “useful” with it.

#Simply fortran themes Pc#

The first PC we got at our home was a Pentium II.