GPU Accelerated Data Analytics in Python
GPU Accelerated Data Analytics in Python
Mads R. B. Kristensen, NVIDIA
2
Scale up and out with RAPIDS and Dask
RAPIDS and Others
Accelerated on single GPU
NumPy -> CuPy/PyTorch/.. Pandas -> cuDF Scikit-Learn -> cuML Numba -> Numba
Dask + RAPIDS
Multi-GPU On single Node (DGX) Or across a cluster
Scale Up / Accelerate
PyData
NumPy, Pandas, Scikit-Learn and many more
Single CPU core In-memory data
Dask
Multi-core and Distributed PyData
NumPy -> Dask Array Pandas -> Dask DataFrame Scikit-Learn -> Dask-ML ... -> Dask Futures
Scale out / Parallelize
3
Scale up and out with RAPIDS and Dask
RAPIDS and Others
Accelerated on single GPU
NumPy -> CuPy/PyTorch/.. Pandas -> cuDF Scikit-Learn -> cuML Numba -> Numba
Scale Up / Accelerate
PyData
NumPy, Pandas, Scikit-Learn and many more
Single CPU core In-memory data
Scale out / Parallelize
4
CPU vs GPU
DOI: 10.1016/j.cam.2013.12.032.
5
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