Resources

Michael Bauer, Legate NumPy: Accelerated and Distributed Array Computing (SC’19, 2019-11-17) Paper

Michael Bauer, Legate Numpy: Accelerated and Distributed Array Computing (SciPy’20, 2020-07-05) Video

Michael Bauer, Reprising the Zen of Python for High Performance Computing (PyHPC’20 Keynote, 2020-11-30) Video

Jeff Larkin, Scale Python and NumPy Performance with Legate (ISC’21, 2021-06-28) Video

Michael Bauer & Wonchan Lee & Manolis Papadakis & Marcin Zalewski & Michael Garland Supercomputing in Python With Legate (IEEE CiSE journal, 2021-07-28) Paper

Manolis Papadakis, Legate: High Productivity High Performance Computing (NERSC Data Seminar, 2021-08-03) Video Slides

Michael Bauer & Michael McCarty, Legate: Scaling the Python Ecosystem (GTC’21, 2021-11-09) Video

Rohan Yadav, Legate Sparse: Distributed and Accelerated Sparse Computing in Python (HPC-AI Advisory Council 2023 Stanford Conference, 2023-02-23) Video

Manolis Papadakis, Implementing Quantitative Use Cases with Accelerated Computing for Faster Time-to-Insight (GTC Spring 2023, 2023-03-21) Video Slides

Wonchan Lee, cuNumeric and Legate: How to Create a Distributed GPU Accelerated Library (GTC Spring 2023, 2023-03-23) Video

Seshu Yamajala, Scaling NumPy Applications from 1 CPU to Thousands of GPUs (UCLA Institute for Pure & Applied Mathematics, 2023-06-04) Video Slides

Elliott Slaughter, Task-Based Runtimes and Applications (Stanford CME 213, 2023-06-07) Slides

Rohan Yadav, Distributed and Accelerated Sparse Computing in Python (MIT CSAIL Fast Code Seminar, 2023-10-17) Video Slides

Rohan Yadav, Legate & cuNumeric (PAW-ATM’23, 2023-11-13) Slides

Rohan Yadav, Legate Sparse: Distributed Sparse Computing in Python (SC’23, 2023-11-14) Slides

Wonchan Lee, Legate: A Productive Programming Framework for Composable, Scalable, Accelerated Libraries (GTC’24, 2024-03-20) Video

Rohan Yadav, Composing Distributed Computations Through Task and Kernel Fusion (2024-06-26) Paper