Area of research
Hardware and Architecture · Materials Chemistry
Research interest
Research interests include Computer science, Machine learning, Benchmark (surveying), Software portability, Implementation, and Bayesian optimization.
ORBIT-2: Scaling Exascale Vision Foundation Models for Weather and Climate Downscaling
ytopt: Autotuning Scientific Applications for Energy Efficiency at Large Scales
Streamlining Ocean Dynamics Modeling with Fourier Neural Operators: A Multiobjective Hyperparameter and Architecture Optimization Approach
Efficient high-dimensional variational data assimilation with machine-learned reduced-order models
A cross-study analysis of drug response prediction in cancer cell lines
Autotuning PolyBench benchmarks with LLVM Clang/Polly loop optimization pragmas using Bayesian optimization
FIdelity: Efficient Resilience Analysis Framework for Deep Learning Accelerators
Autotuning PolyBench Benchmarks with LLVM Clang/Polly Loop Optimization Pragmas Using Bayesian Optimization
A Framework for Enabling OpenMP Autotuning
Autotuning in High-Performance Computing Applications
Explaining Wide Area Data Transfer Performance
Generating Efficient Tensor Contractions for GPUs
Active-learning-based surrogate models for empirical performance tuning