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RIBBON: cost-effective and qos-aware deep learning model inference using a diverse pool of cloud computing instances.

, , , , , and . SC, page 24. ACM, (2021)

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Exploring the Optimal Platform Configuration for Power-Constrained HPC Workflows., , , , and . ICCCN, page 1-9. IEEE, (2018)GUIDE: a scalable information directory service to collect, federate, and analyze logs for operational insights into a leadership HPC facility., , , , , , , and . SC, page 45. ACM, (2017)Reliability Characterization of Solid State Drives in a Scalable Production Datacenter., , , , , , , , , and . IEEE BigData, page 3341-3349. IEEE, (2018)DASH: Scheduling Deep Learning Workloads on Multi-Generational GPU-Accelerated Clusters., , , , , and . HPEC, page 1-7. IEEE, (2022)Characterizing Temperature, Power, and Soft-Error Behaviors in Data Center Systems: Insights, Challenges, and Opportunities., , , , , and . MASCOTS, page 22-31. IEEE Computer Society, (2017)AnalyzeThis: an analysis workflow-aware storage system., , , , , , and . SC, page 20:1-20:12. ACM, (2015)Granularity and the cost of error recovery in resilient AMR scientific applications., , , , and . SC, page 492-501. IEEE Computer Society, (2016)HAQu: Hardware-accelerated queueing for fine-grained threading on a chip multiprocessor., , , and . HPCA, page 99-110. IEEE Computer Society, (2011)Understanding and Exploiting Spatial Properties of System Failures on Extreme-Scale HPC Systems., , , , and . DSN, page 37-44. IEEE Computer Society, (2015)MapReuse: Reusing Computation in an In-Memory MapReduce System., and . IPDPS, page 61-71. IEEE Computer Society, (2014)