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## Available Compilers, Including GNU, INTEL, and UPC Compilers
Currently there are several compilers for different programming languages available on the Anselm cluster:
* C/C++
* Fortran 77/90/95
* Unified Parallel C
* Java
* NVIDIA CUDA
The C/C++ and Fortran compilers are divided into two main groups GNU and Intel.
For information about the usage of Intel Compilers and other Intel products, please read the [Intel Parallel studio](intel-suite/) page.
For compatibility reasons there are still available the original (old 4.4.6-4) versions of GNU compilers as part of the OS. These are accessible in the search path by default.
It is strongly recommended to use the up to date version (4.8.1) which comes with the module gcc:
With the module loaded two environment variables are predefined. One for maximum optimizations on the Anselm cluster architecture, and the other for debugging purposes:
$ echo $OPTFLAGS
-O3 -march=corei7-avx
$ echo $DEBUGFLAGS
-O0 -g
For more information about the possibilities of the compilers, please see the man pages.
* GNU - SMP/multi-threading support only
* Berkley - multi-node support as well as SMP/multi-threading support
To use the GNU UPC compiler and run the compiled binaries use the module gupc
if (MYTHREAD == 0) {
printf("Welcome to GNU UPC!!!n");
}
upc_barrier;
To use the Berkley UPC compiler and runtime environment to run the binaries use the module bupc
As default UPC network the "smp" is used. This is very quick and easy way for testing/debugging, but limited to one node only.
For production runs, it is recommended to use the native Infiband implementation of UPC network "ibv". For testing/debugging using multiple nodes, the "mpi" UPC network is recommended.
Selection of the network is done at the compile time and not at runtime (as expected)!
#include <upc.h>
#include <stdio.h>
int main() {
if (MYTHREAD == 0) {
printf("Welcome to Berkeley UPC!!!n");
}
upc_barrier;
To compile the example with the "ibv" UPC network use
```bash
$ upcc -network=ibv -o hello.upc.x hello.upc
```
To run the example on two compute nodes using all 32 cores, with 32 threads, issue
```bash
$ qsub -I -q qprod -A PROJECT_ID -l select=2:ncpus=16
For information how to use Java (runtime and/or compiler), please read the [Java page](java/).
For information on how to work with NVIDIA CUDA, please read the [NVIDIA CUDA page](nvidia-cuda/).