Skip to main content
Pre-release

This release is a pre-release and may not be stable for production use.

SPU: Secure Processing Unit

CircleCI Python PyPI version OpenSSF Scorecard OpenSSF Best Practices

SPU (Secure Processing Unit) aims to be a provable, measurable secure computation device, which provides computation ability while keeping your private data protected.

SPU could be treated as a programmable device, it's not designed to be used directly. Normally we use SecretFlow framework, which use SPU as the underline secure computing device.

Currently, we mainly focus on provable security. It contains a secure runtime that evaluates XLA-like tensor operations, which use MPC as the underline evaluation engine to protect privacy information.

SPU python package also contains a simple distributed module to demo SPU usage, but it's NOT designed for production due to system security and performance concerns, please DO NOT use it directly in production.

Contribution Guidelines

If you would like to contribute to SPU, please check Contribution guidelines.

This documentation also contains instructions for build and testing.

Installation Guidelines

Supported platforms

Linux x86_64 Linux aarch64 macOS x64 macOS Apple Silicon Windows x64 Windows WSL2 x64
CPU yes yes yes1 yes no yes
NVIDIA GPU experimental no no n/a no experimental
  1. Due to CI resource limitation, macOS x64 prebuild binary is no longer available.

Instructions

Please follow Installation Guidelines to install SPU.

Hardware Requirements

General Features FourQ based PSI GPU
AVX/ARMv8 AVX2/ARMv8 CUDA 11.8+

Citing SPU

If you think SPU is helpful for your research or development, please consider citing our paper:

@inproceedings {spu,
    author = {Junming Ma and Yancheng Zheng and Jun Feng and Derun Zhao and Haoqi Wu and Wenjing Fang and Jin Tan and Chaofan Yu and Benyu Zhang and Lei Wang},
    title = {{SecretFlow-SPU}: A Performant and {User-Friendly} Framework for {Privacy-Preserving} Machine Learning},
    booktitle = {2023 USENIX Annual Technical Conference (USENIX ATC 23)},
    year = {2023},
    isbn = {978-1-939133-35-9},
    address = {Boston, MA},
    pages = {17--33},
    url = {https://www.usenix.org/conference/atc23/presentation/ma},
    publisher = {USENIX Association},
    month = jul,
}

Acknowledgement

We thank the significant contributions made by Alibaba Gemini Lab.

Metadata

Release files for spu 0.9.1.dev20240513

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distributions (wheels)

Table of built distributions (wheels) for spu 0.9.1.dev20240513
File Interpreter ABI Platform
spu-0.9.1.dev20240513-cp310-cp310-manylinux_2_28_aarch64.whl CPython 3.10 CPython 3.10 Linux glibc 2.28+ ARM64 Details
spu-0.9.1.dev20240513-cp310-cp310-manylinux2014_x86_64.whl CPython 3.10 CPython 3.10 Linux glibc 2.17+ x86-64 Details
spu-0.9.1.dev20240513-cp310-cp310-macosx_12_0_arm64.whl CPython 3.10 CPython 3.10 macOS 12.0+ ARM64 Details

Total release size: 107.1 MB

Release files / spu-0.9.1.dev20240513-cp310-cp310-manylinux_2_28_aarch64.whl

Download URL spu-0.9.1.dev20240513-cp310-cp310-manylinux_2_28_aarch64.whl
Size 36.7 MB
Tags CPython 3.10 Linux glibc 2.28+ ARM64
SHA-256 checksum
How to use checksums
496b0b01a8e22e3653c363139951a548a45f626a0bf18a95be0de2ab2bd124c9
BLAKE2b-256 checksum
How to use checksums
1355ea6984ca4b024a2c088260ef9900a0ee90ec09d83dc61669725af245a62e
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.0.0 CPython/3.10.14

Release files / spu-0.9.1.dev20240513-cp310-cp310-manylinux2014_x86_64.whl

Download URL spu-0.9.1.dev20240513-cp310-cp310-manylinux2014_x86_64.whl
Size 37.6 MB
Tags CPython 3.10 Linux glibc 2.17+ x86-64
SHA-256 checksum
How to use checksums
b1e00f8b86215542890beba60568fcd1e4b541ec0e91c86c4ccb59a2029f7b17
BLAKE2b-256 checksum
How to use checksums
cd5834156ed4ea4999b54dd35557e90b5207c60b584e55dc499c18ffea40f3f3
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.0.0 CPython/3.10.14

Release files / spu-0.9.1.dev20240513-cp310-cp310-macosx_12_0_arm64.whl

Download URL spu-0.9.1.dev20240513-cp310-cp310-macosx_12_0_arm64.whl
Size 32.8 MB
Tags CPython 3.10 macOS 12.0+ ARM64
SHA-256 checksum
How to use checksums
d7d7c44518a63f60d379536750d1402df1655e53edc92d99461f346771beb39d
BLAKE2b-256 checksum
How to use checksums
934aa9a092db10d4c81b51fb8a69beafd2cfa23da8fe762b211bf24973e8c23e
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.0.0 CPython/3.10.14

Release history Release notifications | RSS feed

0.9.5

6 release files

0.9.4

6 release files

This release
Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page