How can I run GOLD in parallel?
For very large virtual-screening tasks, we provide the GOLD Cloud and GOLD Cluster tools. For smaller-scale parallelization, e.g. on a computational chemist's workstation or a local compute server, we do not have a specific product, but options are available.
This tool runs GOLD, inside a Docker container, on a Kubernetes cluster and is designed for use on commercial cloud platforms. Our experience is with Azure, but we are aware of customers who have used AWS and GCP. The GOLD Cloud tool and its User Guide are available to customers via our Downloads site under 'CSD-Discovery > GOLD'. A White Paper describing a practical application of the GOLD Cloud is also available.
This tool runs GOLD, inside a Singularity container, on an HPC compute cluster managed by Slurm. The GOLD Cluster tool and its User Guide are available to customers via our Downloads site under 'CSD-Discovery > GOLD'.
GOLD Cloud can be run locally using MiniKube or Docker Desktop and GOLD Cluster can be run on a Slurm cluster running in a Linux VM. Thus, in principle, these tools could be used to parallelize GOLD docking on a workstation. However, the setup involved isn't trivial and might not be straightforward on all platforms. A simpler solution for this use-case is thus required and a script is available which illustrates the use the CSD Docking API and the Python standard-library multiprocessing module to parallelize GOLD docking. This approach should be suitable for docking some hundreds or perhaps thousands of ligands, depending on the compute resource available and the docking protocol chosen. For further information, please contact email@example.com.
Platforms no longer supported
We no longer support using GOLD with Parallel Virtual Machine (PVM). We also do not currently provide tooling or support for running GOLD on Grid Engines, although there is nothing in principle that should prevent this being done.