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Thursday, September 19
Energy Aware Data Center (EADC) Innovations: Save Energy, Boost PerformanceKenny Gross, Oracle's Physical Sciences Research Center,
Computer Science and Mathematics Division
10:00 AM — 11:00 AM, Joint Institute for Computational Sciences, Building 5100, Room 128 (Lecture Hall)
Contact: Barney Maccabe (firstname.lastname@example.org), 865.241.6504
AbstractThe global electricity consumption for enterprise and high-performance computing data centers continues to grow much faster than Moore's Law as data centers push into emerging markets, and as developed countries see explosive growth in computing demand as well as supraexponential growth in demand for exabyte (and now zettabyte) storage systems. The USDOE reported that data centers now consume 38 gigawatts of electricity worldwide, a number that is growing exponentially even during times of global economic slowdowns. Oracle has developed a suite of novel algorithmic innovations that can be applied nonintrusively to any IT servers and substantially reduces the energy usage and thermal dissipation for the IT assets (saving additional energy for the data center HVAC systems), while significantly boosting performance (and hence Return-On-Assets) for the IT assets, thereby avoiding additional server purchases (that would consume more energy). The key enabler for this suite of algorithmic innovations is Oracle's Intelligent Power Monitoring (IPM) telemetry harness (implemented in software...no hardware mods anywhere in the data center). IPM, when coupled with advanced pattern recognition, identifies and quantifies three significant nonlinear (heretofore 'invisible') energy-wastage mechanisms that are present in all enterprise and HPC computing assets today, including in low-PUE high-efficiency data centers: 1) leakage power in the CPUs (grows exponentially with CPU temperature), 2) aggregate fan-motor power inside the servers (grows with the cubic power of fan RPMs), and 3) substantial degradation of server energy efficiency by low-level ambient vibrations in the data center racks. This presentation shows how continuous system internal telemetry coupled with advanced pattern recognition technology that was developed for nuclear reactor applications by the presenter and his team back at Argonne National Lab in the 1990s are significantly cutting energy utilization while boosting performance for enterprise and HPC computing assets.
Speaker Bio Info: ------------------ Kenny Gross is a Distinguished Engineer for Oracle and team leader for the System Dynamics Characterization and Control team in Oracle's Physical Sciences Research Center in San Diego. Kenny specializes in advanced pattern recognition, continuous system telemetry, and dynamic system characterization for improving the reliability, availability, and energy efficiency of enterprise computing systems and for the datacenters in which the systems are deployed. Kenny has 220 US patents issued and others pending, 180 scientific publications, and was awarded a 1998 R&D 100 Award for one of the top 100 technological innovations of that year, for an advanced statistical pattern recognition technique that was originally developed for nuclear plant applications and is now being used for a variety of applications to improve the quality-of-service, availability, and optimal energy efficiency for enterprise and HPC computer servers. Kenny earned his Ph.D. in nuclear engineering from the U. of Cincinnati in 1977.