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Ghaleb Abdulla
Also published under:G. Abdulla, G. M. Abdulla
Affiliation
Lawrence Livermore National Laboratory, Livermore, USA
Topic
Allocation Scheme,Amount Of Power,Job Completion,Power Allocation Scheme,Power Constraint,Power Consumption,Resource Utilization,Scheduling Algorithm,Scheduling Decisions,Soft Threshold,Supercapacitors,System Utility,Aggregate Power,Average Temperature,Benchmark,CPU Power,Classification Applications,Cluster Level,Cold Side,Commensurate Increase,Completion Time,Computing Units,Cooling System,Decrease In Performance,Differences In Efficiency,Dynamic Algorithm,Dynamic Allocation,Dynamic Power,Dynamic Strategy,Energy Measurements,Energy Meter,Environmental Metrics,Hard Threshold,Hardware Configuration,High Production,High-performance Computing,High-performance Computing Systems,Hybrid Algorithm,Idle Resources,Iteration Count,Job Scheduling,Large-sized Problems,Local Temperature,Maximum Temperature,Mean Absolute Percentage Error,Metrics Of Interest,Minimum Read,Minimum Slope,Minimum Temperature,Net Gain,
Biography
Ghaleb Abdulla received the bachelor's degree in electrical engineering from Yarmouk University in Jordan, the MS degree in computer science from Virginia Tech, Blacksburg, Virginia, in 1993, and the PhD degree in computer science from Virginia Tech in 1998. Before joining LLNL, he worked for the Dow Chemical Company as an information technology specialist. Since joining LLNL in 2000, he has embraced projects that depend on teamwork and data sharing. His tenure includes establishing partnerships with universities seeking LLNL's expertise in HPC and large-scale data analysis. He supported approximate queries over large-scale simulation datasets for the AQSim project and helped design a multi-petabyte database for the Large Synoptic Survey Telescope. He used machine learning (ML) to inspect and predict optics damage at the National Ignition Facility, and leveraged data management and analytics to enhance HPC energy efficiency. Recently, he led a Cancer Registry of Norway project developing personalized prevention and treatment strategies through pattern recognition, ML, and time-series statistical analysis of cervical cancer screening data. Currently, he is a co-PI of the Earth System Grid Federation, an international collaboration that manages a global climate database for 25,000 users of six continents.