Accelerating and Scaling Python for HPC

#	Exercise	Link	Solution
1	NumPy Intro: ndarray Basics
2	NumPy Linear Algebra: SVD Reconstruction
3	NumPy to CuPy: ndarray Basics
4	NumPy to CuPy: SVD Reconstruction
5	Memory Spaces: Power Iteration
6	Asynchrony: Power Iteration
7	Kernel Authoring: Copy
8	MPI
9.1	nvmath-python: Interoperability with CPU and GPU tensor libraries
9.2	nvmath-python: Kernel fusion
9.3	nvmath-python: stateful APIs: Amortizing task preparation costs
9.4	nvmath-python: scaling to many GPUs