#计算机科学#cuML - RAPIDS Machine Learning Library
翻译 - cuML-RAPIDS机器学习库
RAPIDS Community Notebooks
RAPIDS Sample Notebooks
cuGraph - RAPIDS Graph Analytics Library
RAPIDS Memory Manager
Spark RAPIDS plugin - accelerate Apache Spark with GPUs
cuSignal - RAPIDS Signal Processing Library
Rapids Core Integration
cuCIM - RAPIDS GPU-accelerated image processing library
nuclio integration and demos with NVIDIA RAPIDS
BlazingSQL is a lightweight, GPU accelerated, SQL engine for Python. Built on RAPIDS cuDF.
翻译 - BlazingSQL是一个基于RAPIDS的轻量级GPU加速的SQL引擎。
Spark RAPIDS MLlib – accelerate Apache Spark MLlib with GPUs
A collection of open-source GPU accelerated Python tools and examples for quantitative analyst tasks and leverages RAPIDS AI project, Numba, cuDF, and Dask.
Go from graph data to a secure and interactive visual graph app in 15 minutes. Batteries-included self-hosting of graph data apps with Streamlit, Graphistry, RAPIDS, and more!
Rapid large-scale fractional differencing with NVIDIA RAPIDS and GPU to minimize memory loss while making a time series stationary. 6x-400x speed up over CPU implementation.
Rapids团队 (https://github.com/CheYulin , https://github.com/shixuansun and https://github.com/WANG-lp), Engine Race (Key-Value Store on Intel Optane SSD, https://tianchi.aliyun.com/competition/entranc...
rapids团队 (https://github.com/WANG-lp and https://github.com/CheYulin )，香港科技大学，2017年，第三届阿里中间件性能挑战赛复赛代码/答辩ppt/比赛攻略文档(第6名，最终答辩成绩：季军)