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Provide Python access to the NVML library for GPU diagnostics
Parallel computing with task scheduling
A library that sits on top of RAPIDS cuDF library providing a range of benefits for processing extremely large tabular datasets, particularly those that do not fit in GPU or CPU memory. NVTabular has many capabilities including fast terabyte-scale data preparation and accelerated tabular data loading, all on GPU, which streamline the first step for both training and inference to any deep recommender system pipelines.
cuDF - GPU DataFrame Library
A distributed task scheduler for Dask
Repositories
57Provide Python access to the NVML library for GPU diagnostics
Scalable toolkit for data curation
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
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Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
GPU accelerated cross filtering with cuDF.
Merlin Systems provides tools for combining recommendation models with other elements of production recommender systems (like feature stores, nearest neighbor search, and exploration strategies) into end-to-end recommendation pipelines that can be served with Triton Inference Server.
cuGraph - RAPIDS Graph Analytics Library
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Morpheus SDK
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
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Parallel computing with task scheduling
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
Distributed SQL Engine in Python using Dask
Experimental repo for proposals of future work
Core Utilities for NVIDIA Merlin
S3 Filesystem
A specification that python filesystems should adhere to.
python implementation of the parquet columnar file format.
A library that sits on top of RAPIDS cuDF library providing a range of benefits for processing extremely large tabular datasets, particularly those that do not fit in GPU or CPU memory. NVTabular has many capabilities including fast terabyte-scale data preparation and accelerated tabular data loading, all on GPU, which streamline the first step for both training and inference to any deep recommender system pipelines.
cuDF - GPU DataFrame Library
A distributed task scheduler for Dask
cuML - RAPIDS Machine Learning Library
No description provided.
The most widely used Python to C compiler