Andy Terrel
I lead CUDA Python Product Management, working to make CUDA a Python native.
I received my Ph.D. from the University of Chicago in 2010, where Ibuilt domain-specific languages to generate high-performance code for physics simulations with the PETSc and FEniCS projects. After spending a brief time as a research professor at the University of Texas and Texas Advanced Computing Center, I have been a serial startup executive, including a founding team member of Anaconda.
I am a leader in the Python open data science community (PyData). A contributor to Python's scientific computing stack since 2006, I am most notably a co-creator of the popular Dask distributed computing framework, the Conda package manager, and the SymPy symbolic computing library. I was a founder of the NumFOCUS foundation. At NumFOCUS, I served as the president and director, leading the development of programs supporting open-source codes such as Pandas, NumPy, and Jupyter.
Session
We discuss bringing Python natively to the CUDA ecosystem. From low level bindings to domain specific applications, CUDA is supporting Python standards and ecosystem. New libraries include nvmath-python for managing optimized mathematics libraries, cccl-python for cooperative threading and device parallelism, cuda-core for managing the complete CUDA toolstack from Python with no need for C++, and finally numba-cuda for generating device side kernels with integration of C++ device libraries and LTO IR.