As HPC workloads evolve to resemble AI workloads, there is a growing need for next-generation data storage solutions that offer high-throughput and low-latency access to large volumes of unstructured data. These solutions must support the parallel and irregular I/O patterns typical of AI training and inference. By focusing on advanced metadata tagging and intelligent data management, faster iterations and improved time-to-insight can be achieved. DDN envisions the future of data platforms tailored for next-generation workloads.
