NAMD† is a portable parallel application for biomolecular simulations. NAMD pioneered the use of hybrid spatial and force decomposition, a technique now used by most scalable pr...
Abhinav Bhatele, Sameer Kumar, Chao Mei, James C. ...
We present SpeedBoost, a natural extension of functional gradient descent, for learning anytime predictors, which automatically trade computation time for predictive accuracy by s...
Whenever large homogeneous data structures need to be processed in a non-trivial way, e.g. in computational sciences, image processing, or system simulation, high-level array prog...
We propose an analysis for detecting procedures and goals that are deterministic (i.e. that produce at most one solution), or predicates whose clause tests are mutually exclusive (...
We describe an acoustic chord transcription system that uses symbolic data to train hidden Markov models and gives best-of-class frame-level recognition results. We avoid the extre...