High-Performance Computing (HPC) is a strategic pillar in sectors such as scientific research, engineering, artificial intelligence, and big data analysis. While AWS ParallelCluster has become a go-to solution for deploying and managing clusters on Amazon Web Services, it is not the only option available. There are both open source solutions and commercial platforms that enable the setup of HPC clusters in the public cloud, hybrid environments, or on private and bare-metal infrastructure.
Major alternatives to AWS ParallelCluster
1. Azure CycleCloud
Microsoft’s offering provides a mature platform for deploying, managing, and scaling HPC clusters on Azure. Its advantages:
- Integration with Active Directory and Microsoft’s corporate ecosystems.
- Support for multiple schedulers (Slurm, PBS Pro, Grid Engine).
- Dynamic autoscaling to adjust resources based on workload.
- Highly customizable for scientific and AI workflows.
Ideal for organizations already aligned with the Azure ecosystem.
2. TrinityX (open source)
TrinityX is an open-source platform focused on HPC and AI clusters, with a modular approach and easy deployment.
- Supports Slurm, Lustre, and CUDA natively.
- Includes integrated monitoring and centralized management tools.
- Designed to run on both bare metal and hybrid clouds.
This is a very attractive option for universities, research centers, and companies seeking full control over their infrastructure without depending on a specific cloud provider.
3. Qlustar
A complete (full-stack) Linux-based distribution for HPC and AI clusters, free of charge.
- Designed for bare metal deployment with centralized management via an intuitive interface.
- Includes support for HPC storage, high-speed networks (InfiniBand, Omni-Path), and scientific libraries.
- Widely used in Europe for academic and research environments.
4. Slurm
The most popular scheduler in supercomputing worldwide. While its primary role is resource and job management, it can also serve as a foundation for building clusters from scratch.
- Scalable to hundreds of thousands of nodes.
- Supports heterogeneous partitions (CPU, GPU, FPGA).
- Large community and integration with open-source projects like OpenHPC.
5. Bright Cluster Manager (NVIDIA)
A commercial solution aimed at companies seeking ease of deployment and official support.
- Installation and monitoring of heterogeneous clusters (CPU, GPU, AI).
- Deployment on both bare metal and public or private clouds.
- Centralized management with NVIDIA support for optimizing HPC/AI workloads.
Other relevant HPC ecosystems
- Amazon ECS/EKS + Batch: AWS alternatives for batch and containerized workloads, with auto-scaling and flexible orchestration.
- OpenHPC: An open-source stack providing libraries, schedulers, and pre-integrated configurations for HPC environments.
- Apache CloudStack: A private cloud orchestration platform supporting HPC workloads.
HPC in private and bare-metal infrastructures
Beyond public clouds, many organizations seek to deploy HPC in controlled environments, with greater cost predictability and data sovereignty. In this context, European providers of private cloud and bare-metal infrastructure like Stackscale come into play.
In such scenarios, you can:
- Build HPC clusters on dedicated bare-metal nodes, with low-latency connectivity and optimized storage.
- Integrate solutions like Slurm, Qlustar, or TrinityX directly on the infrastructure, achieving on-premise-like performance with the flexibility of the cloud.
- Design hybrid architectures where the core HPC runs on dedicated servers, supplemented with public cloud resources for demand peaks (cloud bursting).
This approach is ideal for regulated industries, sensitive research, or companies aiming to reduce dependency on hyperscalers and maintain greater control over costs and digital sovereignty.
Conclusion
AWS ParallelCluster is a powerful tool, but not the only one. Alternatives — from Azure CycleCloud to TrinityX, Qlustar, Slurm, or Bright Cluster Manager — enable deployment of HPC environments based on specific needs: open source for maximum flexibility, commercial solutions for ease of use, or integrated private cloud offerings like Stackscale in Spain.
The future of HPC lies in hybrid and multi-cloud models, where the key will be combining performance, scalability, and sovereignty over data and infrastructure.