Perspectives on Composable Systems and HPC/AI Architectures and How They May Fit in the HPC Market

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Traditional HPC architectures have typically been designed to address either homogenous workloads (such as physics-based modeling and simulation) with similar, and perhaps more important, fixed, compute, memory, and I/O requirements or, more recently, heterogenous workloads with a diverse range of compute, memory, and I/O requirements. Most HPC data center planners and operators, however, don’t have the luxury of focusing on one main type of workload; they typically must support many HPC users and their associated workloads sporting a wide range of compute, memory, and I/O profiles. Architectures have typically consisted of a fixed set of resources, resulting in an underutilized system with expensive elements often sitting idle for long periods of time. One approach being explored to increase system utilization by exposing resources that would otherwise sit idle to appropriately matched jobs waiting in a queue is via composable systems.