Global Settings

Time Ordered Astrophysics Scalable Tools (TOAST) is a software package designed to allow the processing of data from telescopes that acquire data as timestreams (rather than images).

Runtime behavior of this package can be controlled by setting some environment variables (before importing the package):

TOAST_LOGLEVEL= * Possible values are "VERBOSE", "DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL". Default is "INFO". * Controls logging of both C++ and Python code.

TOAST_FUNCTIME= * Values "1", "true", or "yes" will enable python function timers in many parts of the code.

TOAST_GPU_OPENMP= * Values "1", "true", or "yes" will enable runtime-support for OpenMP target offload. * Requires compile-time support for OpenMP 5.x features.

TOAST_GPU_MEM_GB= * Value in GB of memory to use for OpenMP on each GPU. * Conservative default is 2GB.

TOAST_GPU_JAX= * Values "1", "true", or "yes" will enable runtime support for jax. * Requires jax to be available / importable.

TOAST_GPU_HYBRID_PIPELINES= * Values "0", "false", or "no" will disable runtime support for hybrid GPU pipelines. * Requires TOAST_GPU_OPENMP or TOAST_GPU_JAX to be enabled.

OMP_NUM_THREADS= * Toast uses OpenMP threading in several places and the concurrency is set by the usual environment variable.

OMP_TARGET_OFFLOAD=[MANDATORY | DISABLED | DEFAULT] * If the TOAST_GPU_OPENMP environment variable is set, this standard OpenMP environment variable controls the offload behavior.

MPI_DISABLE= * Any non-empty value will disable a try block that looks for mpi4py. Needed on some systems where mpi4py is available but does not work. * The same variable also controls the pshmem package used by toast.

CUDA_MEMPOOL_FRACTION= * If compiled with CUDA support (-DUSE_CUDA), create a memory pool that pre-allocates this fraction of the device memory allocated to each process.