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The advantages of computational storage are well suited to improve storage system efficiency for HPC storage systems supporting simulation science. These benefits can be implemented transparently or include slight modifications to application behavior. Simulation science workloads have ever-growing requirements for bandwidth while single data set size is increasing towards petabyte scale. The organization of these datasets is currently file-based, but the structure of the data looks like common data analytics formats. It has become clear that integrating computational storage into HPC system designs will provide significant performance improvements over more traditional designs while also enabling a large and open ecosystem. Providing use-cases, requirements, and demonstrations for real world applications of computational storage can benefit the broader community and assist with standardization efforts. We will present these use-cases and demonstrations for integrating computation near storage in HPC storage systems. Presented by Dominic Manno, Los Alamos National Laboratory Learn More: SNIA Compute+Memory+Storage Summit: https://www.snia.org/cms-summit SNIA Website: https://snia.org/ SNIA Educational Library: https://snia.org/library Twitter: / snia LinkedIn: / snia