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performance and funding availability. VISION Position Purdue as a national leader in AI-driven software and systems research spanning edge computing, cloud and distributed systems, high-performance
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Lab researches on a variety of computer systems topics including HPC resilience, data center power management, large-scale job scheduling and performance tuning, parallel storage systems and
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benchmarking of parallel and distributed computing systems and of the workflow systems that run on them. Familiarity with the FAIR data and research software principles, and with producing AI-ready
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developing and managing automated and parallel scientific workflows , including task execution systems, dependency management, and pipeline execution on distributed computing resources. Experience with HPC
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compiler optimization techniques. Experience with distributed and parallel computing technologies such as MPI and OpenMP. Experience with large-scale neural network architectures for processing
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research interest include, but are not limited to, numerical algorithms and high-performance scientific software; parallel and distributed computing; performance analysis, modeling, and benchmarking
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engineering workflows for data analysis and decision support. These workflows require distributed parallel computing, utilizing both cloud and on-premise high-performance computing (HPC) resources