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In order to build MPI applications, please us the compiler wrappers mpif77 / mpif90 / mpif08 / mpicc / mpicxx.

Please note that compilers do not use optimization flags by default at the moment. Hence, please refer to Compiler Options Quick Reference Guide and set the respective flags on your own (with znver1 for Naples and znver2 for Rome nodes). Compiler Usage Guidelines for AMD64 Platforms might also be a source of inspiration w.r.t. optimization flags.

Available compilers

We highly recommend to try as many different compilers as possible and compare the performance of the generated code! If you code according to language standards, this is almost for free but can give you a significant speedup! There is no such thing as an "ideal" compiler! One suites better to application A, one suites better to application B (cf. Best Practice Guide AMD EPYC (Naples)).

Default compiler flags for the GCC and AOCC compilers are currently:

-march=znver2 -mtune=znver2 -O3

Default compiler flags for the Intel compilers are currently:

-march=core-avx2 -mtune=core-avx2 -O3

Providing a different -OX value will override the -O3 value.


Make sure to load a more up to date version of the GNU Compiler Collection than the one preinstalled in the system

module load gcc/9.2.0

Then compile with



AOCC is the AMD Optimizing C/C++ Compiler based on LLVM. It contains a Fortran compiler (flang) as well.

Load aocc module

module load aocc/2.1.0

Compile with


AOCC comes with a couple of exclusive compiler flags that are not part of LLVM and allow more aggressive optimizations, they are documented in the C/C++ and Fortran compiler manual.


Load Intel compiler module

module load intel/19.1.0

Compile with


Do not use

<compiler> -xHOST
<compiler> -xCORE-AVX2

since it can crash the compiler in some cases or a resulting binary will refuse to start.

In some cases compiling with -check <arg> resulted in the compiler crashing as well. If you encounter this, try removing the option.

Compiler Options for High Performance Computing

This section shows compiler flags for GNU-compatible compilers (gnu, aocc, intel), other compilers may have other options for the described functionality.

Static Linking

Attention: Building of static binaries (usually compiled with the "-static" flag) are currently not supported on Hawk. This section describes how to link static libraries into a binary with dynamic linking (run-time linker).

Large jobs with thousands of processes can overload the file systems connected to the cluster during startup if the binary is linked to (many) shared libraries that are stored on these file systems.

To avoid this issue and to also improve the performance by reducing the overhead from potentially frequent function calls to shared libraries, compiling dependencies statically into the binary is recommended.

During link-time, you can set the compiler to look for static libraries instead of shared libraries in the library search path with

# Link libhdf5 + zlib statically, set back to look for shared libraries again after (default)
<compiler> ... -Wl,-Bstatic -lhdf5_fortran -lhdf5_f90cstub -lhdf5 -lz -Wl,-Bdynamic

You can also specify a static library filename in the library search path directly

# Statically link hdf5 + zlib
<compiler> ... -l:libhdf5_fortran.a -l:libhdf5_f90cstub.a -l:libhdf5.a -l:libz.a

Or provide the full path to the static library like with other object files

# Statically link hdf5 + zlib
<compiler> ... /path/to/static/lib/libhdf5_fortran.a /path/to/static/lib/libhdf5_f90cstub.a /path/to/static/lib/libhdf5.a /path/to/static/lib/libz.a

Keep in mind that all the symbols referenced in the static library need to be resolved during linking. Thus, linking to additional (static) libraries may be required. In some cases the order of the linked static libraries is important, as with the hdf5 example above.

Link-Time Optimization (LTO), Interprocedural Optimization (IPO), Whole Program Optimization (WPO)

These techniques allow the compiler to optimize the code at link time. During this, further rearrangement of the code from separate object files is performed.

An article about LTO performance comparison with GCC 10: https://www.phoronix.com/scan.php?page=article&item=gcc10-lto-tr

The option needs to be set at compile time and link time.


# Compile with LTO in mind (generate metadata in object files)
<compiler> -flto -o component1.o -c component1.c
<compiler> -flto -o component2.o -c component2.c

# Link with LTO
<compiler> -flto -o program component1.o component2.o

Hint: With GCC you can specify the amount of processes to do the actual link-time optimization with

# Link with LTO
gcc|g++|gfortran -flto=<n_procs> -o program component1.o component2.o

Keep in mind LLVM(AOCC) compiles LLVM bitcode files instead of ELF object files when using LTO. Using tools like objdump, readelf, strip, etc. on these files won't work. Neither will linking them with other compilers work.

More information here: https://www.llvm.org/docs/LinkTimeOptimization.html


# Compile with IPO in mind (generate metadata in object files)
<compiler> -ipo -o component1.o -c component1.c
<compiler> -ipo -o component2.o -c component2.c

# Link with IPO
<compiler> -ipo -o program component1.o component2.o


Linking with LTO/IPO takes a considerable amount of time longer than normal linking.

Profile Guided Optimization (PGO)

This optimization can lead to a 10-20% boost in performance in some cases. It basically collects information about how the program actually runs and improves the assumptions made about which code paths are more likely to be taken.

An article about PGO performance comparison with GCC 10: https://www.phoronix.com/scan.php?page=news_item&px=GCC-10-PGO-3960X-Xmas-Eve

This requires the code to be compiled twice and the program being run with a representative use-case in-between.

A good example for GCC can be found here:

PGO documentation for LLVM:

PGO documentation for the Intel Compiler:

Compiler Related Environment Variables

The compiler modules set implicit environment variables according to established coding practices that will be used in properly set up build tools (GNU Autotools, CMake, etc.) to choose the currently set compiler automatically from the environment variables


and base compiler/linker flags from the environment variables



In a manually set up build process, it is good practice to read from these environment variables, an example:

#!/usr/bin/env bash
# configure script


# Flags for the GCC compiler
if [[ ${CC} == *"gcc"* ]]; then
    CFLAGS="${CFLAGS} -flto"
    LDFLAGS="${LDFLAGS} -flto=16 -l:libamdlibm.a -lm"
# Flags for the AOCC compiler
elif [[ ${CC} == *"clang"* ]]; then
    CFLAGS="${CFLAGS} -flto -finline-aggressive -mllvm -vectorize-memory-aggressively"
    LDFLAGS="${LDFLAGS} -flto -finline-aggressive -l:libamdlibm.a -lm"


echo "CC = ${CC}" > make.cfg
echo "CFLAGS = ${CFLAGS}" >> make.cfg
echo "LDFLAGS = ${LDFLAGS}" >> make.cfg
# Makefile
include make.cfg


program: component1.o component2.o
    $(CC) -o $@ component1.o component2.o $(LDFLAGS)

%.o: %.c
    $(CC) -o $@ -c $(CFLAGS) $<


For large codebases the usage of build tools mentioned above is strongly recommended for maintainable and portable code.