  Hyper-Kamiokande is a next-generation multi-purpose neutrino experiment with
a primary focus on constraining CP-violation in the lepton sector. It features
a diverse science programme that includes neutrino oscillation studies,
astrophysics, neutrino cross-section measurements, and searches for physics
beyond the standard model, such as proton decay. Building on its predecessor,
Super-Kamiokande, the Hyper-Kamiokande far detector has a total volume
approximately 5 times larger and is estimated to collect nearly 2PB of data per
year. The experiment will also include both on- and off-axis near detectors,
including an Intermediate Water Cherenkov Detector. To manage the significant
demands relating to the data from these detectors, and the associated Monte
Carlo simulations for a range of physics studies, an efficient and scalable
distributed computing model is essential. This model leverages Worldwide LHC
Grid computing infrastructure and utilises the GridPP DIRAC instance for both
workload management and for file cataloguing. In this report we forecast the
computing requirements for the Hyper-K experiment, estimated to reach around
35PB (per replica) and 8,700 CPU cores (~ 100,000 HS06) by 2036. We outline the
resources, tools, and workflow in place to satisfy this demand.
