Data center modernization has come to the top of the agenda for most enterprises due to the rise of 5G and AI. In the past, enterprises usually spent several years building their data centers, which were operated on proprietary enterprise-grade software and were expected to reach 100% utilization over another 3–5 years.However, because of rapid technological developments, what seemed to be reliable and visionary at their time of establishment have now become barriers to innovation. In the meantime, open source software products have become mature enough to replace parts of the commercial software stack. More and more companies are embracing open or hybrid data center architectures to increase flexibility and efficiency while reducing total cost of ownership. Such architectures allow customers to purchase on-premise systems step-by-step according to their business growth, accelerating the data center transformation journey in addition to offering high scalability and interoperability.
QCT offers its pre-configured pre-validated solution QCT Platform on Demand (QCT POD) to help enterprises address a broader range of HPC, Deep Learning, and Data Analytic demands. By integrating in-house hardware with best-practice software, this solution can be fine-tuned to fulfill specific workloads. Its architecture can be divided into the management building block, the compute building block, and the storage building block; each of which can be customized to fit user needs. For example, to prevent storage from becoming a bottleneck due to rapidly increasing AI & ML data feeds, QCT collaborated with industry-leading partners to solve these problems. We deployed BeeGFS and NVMesh on All-NVMe QCT Storage Servers to combine the power of the fastest parallel file system with the fastest block storage. This end-to-end, scale-out, high-performance storage solution brings impressive performance benefits for mission-critical workloads across industries.
For more information about QCT POD, download the insideHPC white paper below:Data-Center-Transformation_Why-a-Workload-Driven-and-Scalable-Architecture-Matters