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This paper presents a novel Network Request Scheduler (NRS) for a large-scale, LustreTM storage system. It proposes a quantum-based, Object Based Round Robin (OBRR) NRS algorithm that reorders the execution of I/O requests per data object, presenting a workload to backend storage that can be optimized more easily. According to the drawback of static(More)
As part of the SCinet Research Sandbox at the 2011 International Conference for High Performance Computing, Networking, Storage and Analysis (SC11), Indiana University utilized a dedicated 100 Gbps wide area network (WAN) link spanning more than 3,500 km (2,175 mi) to demonstrate the capabilities of the Lustre high performance parallel file system in a high(More)
Current production HPC IO stack design is unlikely to offer sufficient features and performance to adequately serve extreme scale science platform requirements as well as Big Data problems. A joint effort between the US Department of Energy's Office of Advanced Simulation and Computing and Advanced Scientific Computing Research commissioned a project to(More)
Designing a large scale, high performance storage system presents significant challenges. This paper describes a systematic approach to designing a storage system, considering the most important requirements first and then iteratively adding requirements and revising the design at each step before proceeding to the next step. The paper includes a detailed(More)
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