HybridBackend

HybridBackend is a high-performance framework for training wide-and-deep recommender systems on heterogeneous cluster.

Features

Memory-efficient loading of categorical data

Install

Using pip packages

GLIBC	CUDA	Python	Tensorflow	Command
`>= 2.4`	-	3.6	`>=1.15, < 2.0`	`pip install hybridbackend-cpu`
`>= 2.4`	-	3.6	`>=1.14, < 1.15`	`pip install hybridbackend-cpu-legacy`

Build from source

See Building Instructions.

Usage

Please see documentation for more information.

License

HybridBackend is licensed under the Apache 2.0 License.

Community

Please see Contributing Guide before your first contribution.
Please register as an adopter if your organization is interested in adoption. We will discuss new feature requirements with registered adopters in advance.

Please cite HybridBackend in your publications if it helps:

@article{zhang2022picasso,
  title={PICASSO: Unleashing the Potential of GPU-centric Training for Wide-and-deep Recommender Systems},
  author={Zhang, Yuanxing and Chen, Langshi and Yang, Siran and Yuan, Man and Yi, Huimin and Zhang, Jie and Wang, Jiamang and Dong, Jianbo and Xu, Yunlong and Song, Yue and others},
  journal={arXiv preprint arXiv:2204.04903},
  year={2022}
}

Contact Us

If you would like to share your experiences with others, you are welcome to contact us in DingTalk:

Metadata

Release files for hybridbackend-cpu-legacy 0.5.4.post1

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Built distribution (wheel)

Table of built distributions (wheels) for hybridbackend-cpu-legacy 0.5.4.post1
File	Interpreter	ABI	Platform	Reset
hybridbackend_cpu_legacy-0.5.4.post1-cp36-cp36m-manylinux_2_27_x86_64.whl 19.9 MB Aug 3, 2022 Without provenance	CPython 3.6	CPython 3.6 pymalloc	Linux glibc 2.27+ x86-64	Details

Release files / hybridbackend_cpu_legacy-0.5.4.post1-cp36-cp36m-manylinux_2_27_x86_64.whl

Download URL	hybridbackend_cpu_legacy-0.5.4.post1-cp36-cp36m-manylinux_2_27_x86_64.whl
Size	19.9 MB
Tags	CPython 3.6 CPython 3.6 pymalloc Linux glibc 2.27+ x86-64
SHA-256 checksum How to use checksums	`7d388ab446b8734c7fbd4f6474a43405ddcac0524238f318e55a292f74b7ca82`
BLAKE2b-256 checksum How to use checksums	`5ad959a80f22f5b3ffef74d78bc8b2b273fc1d857bd0b9dee137728015335e1f`
Upload date	Aug 3, 2022
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/4.0.1 CPython/3.9.13`

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