Performance- and Energy-Aware HEC Storage Stacks

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High-End Computing (HEC) systems are designed for performance, not energy efficiency. In recent years, HEC users have found that as energy costs increase, network and disks have become significant bottlenecks; worse, scientific workloads vary wildly, exercising different parts of HEC clusters, making it impossible to understand where the bottlenecks are and where energy is being wasted.This project explores the impact of storage-stack configurations on power and performance, using actual cluster configurations and realistic scientific workloads. The research follows three thrusts: tracing and analysis, adaptive cluster reconfiguration, and new storage software stacks.(1) Traces are collected and analyzed which combine both performance and energy data on a large set of scientific workloads: I/O-, network-, memory-, and CPU-intensive. Three popular scientific cluster configurations are investigated, varying many configuration parameters. (2) Tools are being developed to dynamically adapt a cluster's configurations to a given workload, so as to optimize power and performance prior to running long-term scientific experiments or simulations. (3) New operating systems software is developed specifically to optimize power and performance for scientific workloads: a new lightweight file system and disk I/O scheduler.The long-term results of this project help society save energy in computing without unduly hurting performance.