Runtime Tuning

Besides the obvious tuning parameters exposed through the compile time options (see Compilation DEFINES, CUDA Compilation, and MPI Compilation), divERGe enables fine-grained CPU parallelization control using the following environment variables:

Environment Variable	Description
DIVERGE_OMP_NUM_THREADS=VAL	set the (maximum) number of OpenMP threads that execute parallel regions in the core components of divERGe to VAR. This specifically excludes parallelism in components like FFTW, OpenBLAS, etc. All loops within the source code are equipped with a num_threads() OpenMP clause. For user programs, a function that returns the number of threads is exported as diverge_omp_num_threads().
DIVERGE_FFTW_NUM_THREADS=VAL	set the number of FFTW threads to VAL.
DIVERGE_OMP_IMPLICIT_NUM_THREADS=VAL	set the number of OpenMP threads to VAL for all OpenMP regions that do not specify num_threads(). Especially useful if linking to, e.g., OpenBLAS, where thread control is not possible apart from this global, implicit OpenMP setting.
DIVERGE_SHARED_MALLOC_EXTRA_COLORS=VAL	boolean flag to control additional splitting of shared memory communicators. may be benificial for performance in some cases; and very useful for debugging.
DIVERGE_SYMCHECK_MPI	pass around the diverge symmetry maps among MPI ranks in round-robin fashion and then check whether they are equal. useful for debugging MPI related symmetry issues. MPI communication function called upon symmetry map creation.
DIVERGE_TU_SYMCHECK_MPI	same as DIVERGE_SYMCHECK_MPI but for TUFRG specific data structures.
DIVERGE_BATCHED_EIGEN3	enforce the batched eigensolver on CPU compiled with Eigen3 even if CUDA is compiled in