Co-design approach that encompasses neuromorphic computing, systems architecture, and datacentric applications. Focus on high energy physics (HEP) and nuclear physics (NP) detector experiments
Multi-dimensional automated scalability tests, program analysis, performance learning and prediction at various levels of the software/hardware stack.
Machine learning-based probabilistic I/O performance models that take the background traffic, and system state into account while prediciting application performance on HPC system.