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Classroom Contents
Distributed Multi-GPU Computing with Dask, CuPy and RAPIDS
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- 1 Intro
- 2 GPU-Accelerated Clustering Code Example
- 3 What is RAPIDS? New GPU Accelerated Data Science Pipeline
- 4 RAPIDS End-to-End GPU-Accelerated Data Science
- 5 Learning from Apache Arrow
- 6 Data Science Workflow with RAPIDS
- 7 Ecosystem Partners
- 8 ML Technology Stack
- 9 Distributing Dask
- 10 Dask SVD Example
- 11 Numpy Array Function (NEP-18)
- 12 Python CUDA Array Interface
- 13 Interoperability for the Win
- 14 Challenges: Communication
- 15 SVD Benchmark
- 16 Scale up with RAPIDS
- 17 Road to 1.0
- 18 Additional Reading Material
