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Adam Paszke: Getting to the Point - Safe Parallel Programming for Scientific Applications
PyCon.DE 2018: PyTorch As A Scientific Computing Library: Past, Present And Future - Adam Paszke
Getting to the Point: Index Sets and Parallelism-Preserving Autodiff for Pointful Array Programming
Adam Paszke: PyTorch 1.0: now and in the future
Parallel computing and efficient coding for data science
From Research to Production with PyTorch
SPMLJ 01 JULIA1 6D Further Topics Part D Parallel computation: multithreading, multiprocessing
3.2 Parallel computing - Getting started with scientific computing/HPC (winter 2022)
SIGGRAPH 2021 Significant New Researcher Award Talk by Jonathan Ragan-Kelley
2022 02 03 CS 51590 Parallel Programming
CIS-30E Unit 8 Lecture: Parallel Programming in Python
3_Handson_Adam Paskze_FAIR
