Storage is the Key to HPC Revolution

The growth of AI/Deep learning and data analytics has created many of the most challenging HPC workloads in recent years. The latest HPC report by Hyperion Research states that iterative simulation workloads and new workloads such as AI and other Big Data jobs would drive the adoption of HPC storage. To keep up with the growing massive amount of data we are collecting, users need to enhance computation performance at the same time and hence HPC requires equally robust storage to maintain compute performance for faster data in and out as we are heading into the Big Data era now. Data-intensive HPC is driving new storage requirements and making a change. For the simulation process, it not only requires a large amount of computations running on HPC infrastructures built on a cluster of powerful servers linked together with networking and memory, but also adds in self-service concept data stores.