Serve as Senior Computational Research Scientist by identifying and enabling strategic thrusts. The emphasis is on working with computational scientists to prepare them for unprecedented Exascale systems coming online in about 2020. To do this, the person in this position will leverage and continue development of the science of performance modeling for Exascale HPC systems with an emphasis on energy efficiency, resiliency, interconnect technologies and scalability. The position will work with high-profile users of HPC systems to enable them to compute at Exascale. Identify funding opportunities, potential collaborators, and work to win proposals for collaborative Exascale application development and performance modeling. Provide technical competency and leadership to management. Publish peer-reviewed papers in reputed journals, conferences and workshops. Prepare and deliver high-quality, advanced technical presentations and conference proceedings to share technical information. Identify new strategic technical opportunities and help managers and staff members pursue such opportunities.
Participate in collaborative research projects. Develop an infrastructure for identifying and improving performance bottlenecks, especially computation and network bottlenecks, to time-to-solution and energy-to-solution on scientific applications. Develop and deploy system for automatically characterizing and tuning applications. Develop suites of benchmarks for characterizing machines and for determining application bottlenecks. Continue to develop convolution and modeling methods for predicting the performance of future machines on emerging workloads (with close ties to co-design center workloads) and use this to guide tuning and scaling of Exascale applications. Managing projects and people under the general direction of director, focusing their efforts to achieve the prime goal of enabling Exascale computational science enabled by a framework of performance modeling, and drawing upon their expertise, along with that of external collaborators, to initiate independent research in algorithms, applications and high performance computing architectures required to enable Exascale performance.
Work to change the way HPC applications are developed and further the process of performance modeling as a practical framework for profiling applications and mapping their expected performance to the capabilities of Exascale machines. Understand emerging needs of computational science as a whole and identify pertinent initiatives. This includes identifying and pursuing funding opportunities for relevant research. Expertise includes technical mastery of algorithms, applications, operating systems, and advanced computing architectures, and the interrelationship between these. Understand emerging trends in high performance computing including mixed-mode programming models, multithreading technologies and new approaches to building scalable systems including the use of solid-state memory. Responsible to management for strategy, goal setting, budget, cost, timeliness and results.
Ph.D. in Computer Science or related field; or comparable combination of education and experience.
Comprehensive knowledge and expertise in the concepts, principles, codes, standards, techniques and methods of scientific programming, and a very broad comprehension of principles and practices in fundamental computer science as well as energy-efficient HPC, performance modeling/analysis, or HPC fault tolerance/resiliency.
Established academic reputation via published papers in journals, workshops and symposia in the field of high performance scientific computing.
Demonstrated ability and experience working in an organized and effective manner in an environment that has rapidly shifting and often contradictory demands and priorities. Experience leading in such an environment.
UC San Diego is an Equal Opportunity / Staff Affirmative Action Employer that values a diverse workforce.
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