UVA HPC offers multiple compiler bundles for C, C++, and Fortran. Different compilers have different strengths and weaknesses and different error messaging and debugging features, so users should be willing to try another one when appropriate. The modules system manages the compiler environment and ensures that only compatible libraries are available for loading.
Many users of compiled languages are working with codes that can employ MPI for multinode parallel runs. MPI users should first understand how their chosen compiler works, then see the MPI instructions at our parallel programming page.
Compiled languages can be more difficult to debug, and the assistance of a good debugger can be essential. Descriptions of debuggers available on the HPC system can be found at our debuggers and utilities page.
Available Compilers on The HPC System
| Module |
Category |
Description |
| aocc |
compiler |
AMD Optimized C/C++ & Fortran compilers (AOCC) based on LLVM |
| clang |
compiler |
C, C++, Objective-C compiler, based on LLVM. Does not
include C++ standard library -- use libstdc++ from GCC. |
| gcc |
compiler |
The GNU Compiler Collection includes front ends for C, C++, Objective-C, Fortran, Java, and Ada,
as well as libraries for these languages (libstdc++, libgcj,...). |
| ghc |
compiler |
The Glorious/Glasgow Haskell Compiler |
| intel-compilers |
compiler |
Intel C, C++ & Fortran compilers (classic and oneAPI) |
| llvm |
compiler |
The LLVM Core libraries provide a modern source- and target-independent
optimizer, along with code generation support for many popular CPUs
(as well as some less common ones!) These libraries are built around a well
specified code representation known as the LLVM intermediate representation
("LLVM IR"). The LLVM Core libraries are well documented, and it is
particularly easy to invent your own language (or port an existing compiler)
to use LLVM as an optimizer and code generator. |
| nvhpc |
compiler |
C, C++ and Fortran compilers included with the NVIDIA HPC SDK (previously: PGI) |
| ocaml |
compiler |
OCaml is an industrial-strength programming language supporting functional, imperative and object-oriented styles |
GNU Compiler
The GNU Compiler Collection compilers are free, open-source tools. Additional tools included are the gdb debugger and the gprof performance profiler. For detailed documentation, visit the GNU website.
The compilers are:
- Fixed-format Fortran: gfortran [options] filename.f
- Free-format Fortran: gfortran [options] filename.f90
- C: gcc [options] filename.c
- C++: g++ [options] filename.cpp or g++ [options] filename.cxx
A list of compiler options can be obtained by invoking the compiler with the -help option. For example: gfortran -help
More information is available from the manpage, e.g.:
man g++
The default GNU compilers on the HPC system are typically fairly old. Newer versions can be invoked through an appropriate module. For available versions, please run
module spider gcc
It is important to load the correct module if you want to use more advanced features available in newer standards, particularly for C++ and Fortran.
module load gcc
It may be necessary to use an older compiler for programs using GPGPUs.
Available GNU Compilers
| Module | Version |
Module Load Command |
|---|
| gcc | .11.4.0-intel |
module load gcc/.11.4.0-intel
|
| gcc | 11.4.0 |
module load gcc/11.4.0
|
| gcc | 12.4.0 |
module load gcc/12.4.0
|
| gcc | 13.3.0 |
module load gcc/13.3.0
|
Intel Compiler
The Intel Linux Fortran and C/C++ compilers are for x86-64 processor-based systems running Linux. These compilers have specific optimizations for Intel architectures. The University has floating network licenses for the Intel compiler suite as well as for the Math Kernel Libraries.
For detailed information, review the documentation on the Intel C/C++ and Fortran compiler website.
The Intel compilers are accessed on the cluster by using the modules software to dynamically set the appropriate environmental variables (e.g. PATH and LD_LIBRARY_PATH). To initialize your environment to use the Intel compilers, use the command:
module load intel
- Fortran fixed format: ifort [options] filename.f
- Fortran free format: ifort [options] filename.f90
- C: icc [options] filename.c
- C++: icpc [options] filename.cpp or: icpc [options] filename.cxx
A list of compiler options can be obtained by invoking the compiler with the -help option, e.g.:
ifort -help
or by accessing the manpage, e.g.
man ifort
To see the available versions, run
module spider intel
Then load the appropriate module, in this case the default version
module load intel
Available Intel Compilers
| Module | Version |
Module Load Command |
|---|
| intel | 18.0 |
module load intel/18.0
|
| intel | 2023.1 |
module load intel/2023.1
|
| intel | 2024.0 |
module load intel/2024.0
|
Important note for Fortran programmers: Nearly all Fortran code must be compiled with the flag -heap-arrays added or it will encounter a segmentation violation.
If you still experience segmentation violations, recompile with -g -CB (for debugging and bounds checking respectively) and run the program under the control of a debugger. Once the program is debugged, be sure to remove the -g and certainly the -CB flags and recompile with -O or -O -ipo. If that works, try -O3 or -O3 -ipo for a higher level of optimization.
If mathematical libraries are needed, we strongly recommend the Intel Math Kernel Libraries (MKL). They provide LAPACK, BLAS, and a number of other libraries. They are highly optimized, especially for Intel architecture, and they automatically work with the compiler. The Intel module for any version loads the MKL that is compatible with that compiler. The module script sets an environment variable MKL_DIR (with MKLROOT as a synonym). This variable can be used in scripts and makefiles. For example, in a [mM]akefile: LIBS=-L$(MKLROOT).
The MKL consists of a number of libraries, and which ones to link is not always obvious. In newer Intel compilers a flag -mkl can be added for both compiler and linker. However, that does not always suffice, so Intel provides a link line advisor at their site. Remember that default integers are 32 bits even on 64-bit systems. The MKL bundled with our compiler suite includes ScaLAPACK.
NVIDIA CUDA Compiler
The NVIDIA HPC SDK C, C++, and Fortran compilers support GPU acceleration of HPC modeling and simulation applications with standard C++ and Fortran, OpenACC directives, and CUDA.
NVIDIA CUDA compilers are accessed on the HPC cluster by using modules to dynamically set the appropriate environmental variables (e.g. PATH and LD_LIBRARY_PATH). To initialize your environment to use the CUDA compilers, use the command
module load cuda
or
module load nvhpc
Available NVIDIA CUDA Compilers
| Module | Version |
Module Load Command |
|---|
| cuda | 10.2.89 |
module load cuda/10.2.89
|
| cuda | 11.4.2 |
module load cuda/11.4.2
|
| cuda | 11.8.0 |
module load cuda/11.8.0
|
| cuda | 12.2.2 |
module load cuda/12.2.2
|
| cuda | 12.4.1 |
module load cuda/12.4.1
|
| Module | Version |
Module Load Command |
|---|
| nvhpc | 24.1 |
module load nvhpc/24.1
|
| nvhpc | 24.5 |
module load nvhpc/24.5
|
Please see here for details.
PGI Compiler
Please use the nvhpc module instead (see previous section).
Building on the HPC System
For more information about building your code on UVA HPC, please see our howto.
