Current workloads at data centers are changing at a blistering pace and fast becoming data-centric. Modern cloud-native applications are written as microservices distributed across network connected servers and many of these applications need to process large amounts of data quickly—data that cannot fit in a single server and therefore needs to be “sharded” or spread across many servers.

Computational storage is paramount for truly composable infrastructure. While there isn't yet broad adoption, computational storage is ready to move beyond test benches into widespread deployment. This presentation explore today’s cloud data center requirements using real-world use cases to show how to move compute to the data, instead of the data to the compute. Computational systems seek to address the limitations of hyper-converged infrastructure systems, in which users can only scale compute and storage by purchasing additional nodes.

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The SNIA Technical Council believes that it is important for storage developers to learn about the emerging technology of Data Processing Units (DPUs).  We have gathered a panel of leading DPU vendors to provide an overview and answer the following questions.

DPUs (data processing units) are an exciting new category of processor that complement CPUs and GPUs inside data centers. DPUs are fast at data-centric tasks, while they retain the full programmability of CPUs. DPUs have typically been used to offload networking and security functions from compute servers, but have not been used to build storage systems until recently. In this talk, we will briefly introduce DPUs, then highlight the use of DPUs to build storage systems. This is an emerging new use case for DPUs.