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cs.PL2020
Nimble: Efficiently Compiling Dynamic Neural Networks for Model Inference
Haichen Shen, Jared Roesch, Zhi Chen +6
Modern deep neural networks increasingly make use of features such as dynamic control flow, data structures and dynamic tensor shapes. Existing deep learning systems focus on optim…
cs.PL2019
Tea: A High-level Language and Runtime System for Automating Statistical Analysis
Eunice Jun, Maureen Daum, Jared Roesch +4
Though statistical analyses are centered on research questions and hypotheses, current statistical analysis tools are not. Users must first translate their hypotheses into specific…
cs.PL2018
Relay: A New IR for Machine Learning Frameworks
Jared Roesch, Steven Lyubomirsky, Logan Weber +4
Machine learning powers diverse services in industry including search, translation, recommendation systems, and security. The scale and importance of these models require that they…