Overview on Optimizing Python Based Spectroscopic Data Processing On Nersc Supercomputers Scipy 2019
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Day 2 SciPy Tools Plenary Session | SciPy 2019 |
Monitoring Scientific Python Usage on a Supercomputer | SciPy 2021
CuPy: A NumPy Compatible Library for High Performance Computing with GPU | SciPy 2019 | SciPy 2019 |
Turning HPC Systems into Interactive Data Analysis Platforms | SciPy 2019 | A. Banihirwe
Reproducible Data Science in Python | Scipy 2019 Tutorial | Xu Fei, Chandrasekhar Ramakrishnan
apricot: Submodular Selection for Data Summarization | SciPy 2019 | Jacob Schreiber
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Last Updated: October 31, 2026
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Summary
This talk is a case study that describes how a At the National Energy Research Scientific Computing ( Over the past year, and for the first time since its creation, Okay well uh thank you for that uh our next question is from bill little are you able to monitor CuPy is an open-source library which has This talk demonstrates how to use Dask and Jupyter on large high-performance computing (HPC) systems to scale and accelerate ... The expectation of reproducibility in scientific work has been long established, and, increasingly, communities and funding ... Submodular selection can be used to reduce a complex
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