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# Looking into the future: The Next HPC at AWI
> [**Dr. Paul Gierz**](mailto:pgierz@awi.de)
> Chief Engineer
> High Performance Computing and Data Processing Group
> Scientific Computing
>
> Alfred Wegener Institute for Polar and Marine Research
> Bremerhaven, Germany
As AWI's HPC team, one of our primary goals is to provide strategic guidance on the optimal utilization of high-performance computing (HPC) resources. With AWI's commitment
to advancing polar and marine research, the demand for robust, scalable, and efficient computational capabilities is growing rapidly. While our current HPC infrastructure
is serving us well, we still need to plan for the future when the system inevitably reaches the end of its lifecycle. To ensure we meet the increasing computational and storage
needs of climate modeling and data analysis, it is therefore imperative to assess pathways for modernizing or replacing our HPC system.
We are currently evaluating three primary options for the future of our HPC infrastructure:
1. Upgrading to a new, on-premises HPC solution.
2. Leveraging a dedicated compute partition at DKRZ.
3. Transitioning to a cloud-based HPC system.
This report evaluates these options by weighing the benefits and challenges of on-premises systems, partner-hosted infrastructure, and cloud solutions to ensure our future
setup aligns with AWI's research priorities and long-term goals.
Cloud-based HPC offers attractive benefits, including virtually unlimited scalability, flexible resource allocation, and potential cost efficiencies tailored to fluctuating
computational demands. However, it comes with significant challenges, such as data transfer bottlenecks for our large datasets, stringent requirements for data security and
compliance, and potential performance variability compared to on-premises clusters. Additionally, integrating cloud resources into existing workflows may necessitate retraining
staff and adapting established processes.
On the other hand, upgrading to an on-premises HPC cluster allows for greater control over system performance, customized configurations tailored to our specific workloads, and
the retention of in-house expertise. However, this approach involves substantial upfront costs, ongoing maintenance efforts, and careful planning to future-proof against evolving
demands. This report examines these trade-offs across critical factors, including total cost of ownership, workload performance, operational flexibility, and long-term
sustainability, to identify the optimal solution for AWI's HPC future.
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