Abstract
The need for an increasingly dynamic and more cost-efficient data-center infrastructure has led to the adoption of a software defined model that is characterized by: the creation of a federated control plane to judiciously allocate and control appropriate heterogeneous infrastructure resources in an automated fashion, the ability for applications to specify criteria, such as performance, capacity, and service levels, without detailed knowledge of the underlying infrastructure; and the migration of data-plane capabilities previously embodied as purpose-built devices or firmware into software running on a standard operating systems in commercial off-the-shelf servers. This last trend of hardware-based capabilities migrating to software is enabling yet another shift to hyperconvergence, which refers to merger of traditionally separate networking, compute, and storage capabilities in integrated system software. This paper examines the convergence of the software defined infrastructure stack, and introduces a hyperconverged compute and storage architecture, in which the IBM General Parallel File System (GPFS®) implements the software defined data plane that dynamically supports workloads ranging from high-I/O virtual desktop infrastructure applications to more compute-oriented analytics applications. The performance and scalability characteristics of this architecture are evaluated with a prototype implementation.
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