The rise of cloud computing has transformed the concept of computing power, with platforms like Azure, AWS, and Google Cloud essentially forming a global, scalable compute cluster. Originally developed for supercomputers, these technologies now enable users to build, deploy, and run high-performance computing (HPC) systems on-demand, leveraging the cloud’s vast resources to solve complex problems. Azure, in particular, offers specialized compute instances and collaborates with HPC vendors to provide HPC tools as services, making HPC accessible to a broader range of users.
Despite the cost-saving potential, building an HPC architecture in the cloud requires careful consideration of factors such as VM types, OS, scheduler, workload manager, and connectivity. Tools like Azure CycleCloud and Azure Batch further simplify HPC management and scalability, offering platform options for specific types of parallel workloads. While Azure provides powerful compute capabilities and supports familiar tools, the decision to switch from on-premises HPC to the cloud ultimately depends on the economic feasibility for each organization.
