Skip to main content

AIBooster - Performance intelligence and observability tools for AI workloads

Project description

AIBooster

PyPI version Python License

AIBooster is a performance engineering platform for AI workloads.

Overview

AIBooster is an integrated platform that provides performance intelligence and performance observability for AI/ML workloads, consisting of the following components:

  • Performance Intelligence (PI): Performance optimization framework
  • Performance Observability (PO): Dashboards and agents for performance monitoring

Key Features

  • Auto performance tuning
    • Framework-friendly design supporting MMEngine, DeepSpeed, and Megatron-LM
    • Kubernetes support
  • Inference optimization
    • Automatic model conversion for deep learning compilers (TensorRT, etc.)
  • NCCL analysis tools
    • Communication pattern analyzer
    • Benchmark for PyTorch distributed training

Installation

pip install aibooster

Documentation

For detailed usage and API reference, please visit the official documentation.

Examples

For usage examples, please see aibooster-examples.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

aibooster-0.1.1-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (371.4 kB view details)

Uploaded CPython 3.12manylinux: glibc 2.17+ x86-64

aibooster-0.1.1-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (373.4 kB view details)

Uploaded CPython 3.11manylinux: glibc 2.17+ x86-64

aibooster-0.1.1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (359.1 kB view details)

Uploaded CPython 3.10manylinux: glibc 2.17+ x86-64

aibooster-0.1.1-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (363.4 kB view details)

Uploaded CPython 3.9manylinux: glibc 2.17+ x86-64

aibooster-0.1.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (363.1 kB view details)

Uploaded CPython 3.8manylinux: glibc 2.17+ x86-64

aibooster-0.1.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (417.4 kB view details)

Uploaded CPython 3.8manylinux: glibc 2.17+ ARM64

File details

Details for the file aibooster-0.1.1-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.

File metadata

File hashes

Hashes for aibooster-0.1.1-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
Algorithm Hash digest
SHA256 858190de986fbe3d41027c5de939d3211ccc95b294111e16487570116732e222
MD5 c027505259287329faa52bca78914e89
BLAKE2b-256 b117670002339c227d9fe0e4858b2542799572b95061ff72ba8c8cb324f6a9d1

See more details on using hashes here.

File details

Details for the file aibooster-0.1.1-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.

File metadata

File hashes

Hashes for aibooster-0.1.1-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
Algorithm Hash digest
SHA256 a4756beefa15f830d82d6b133fa62bb038f685894261da32bb3e46e94e754da9
MD5 10995104d752002c4c836f28dbb82ded
BLAKE2b-256 568e82efb9f393ec2f58ed219405188d769fb2c772a2a7337d044e161d4e9690

See more details on using hashes here.

File details

Details for the file aibooster-0.1.1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.

File metadata

File hashes

Hashes for aibooster-0.1.1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
Algorithm Hash digest
SHA256 9ad6c1361eed031d589f6d677388d250b8bf5c610392a6d241f90f08f06eddbc
MD5 6720f9bcabdb89d416ce54362977c53f
BLAKE2b-256 0a7085d11165e9e615b37b2c7f25d2e4892bca5e9b4f21e6802e614eea8e998e

See more details on using hashes here.

File details

Details for the file aibooster-0.1.1-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.whl.

File metadata

File hashes

Hashes for aibooster-0.1.1-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
Algorithm Hash digest
SHA256 9a1055793bb9f111bbdab0cc04414a3e4014a4cc0bf9ac5ea8dbfbde98f21f93
MD5 88cef813026aae29d8e967672dfe5646
BLAKE2b-256 c83b8cf95ebb9eeef017b1d754db87be890369306dae00a5d822a5f4d837b3ff

See more details on using hashes here.

File details

Details for the file aibooster-0.1.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for aibooster-0.1.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 2a14a51158d3d49d8052cef457f61fd2b5c5218fb0cac610cae4dbc50bb7158c
MD5 15831c213125d1d590016babe1c9fcd7
BLAKE2b-256 da257be219f02a21a917467da6a6998a87ed52595c863c37f5032a03ab64a160

See more details on using hashes here.

File details

Details for the file aibooster-0.1.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for aibooster-0.1.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 baaafdd00075b437e2c3aa34e017dce0e03f4ee061b56d618c5b8ddf670f70b4
MD5 b1f2fd9480f855a5fc232199ad9d9bda
BLAKE2b-256 0bc8e97080f7193a7c50ab69ac364130b380314b986e1f2af1a855c4c7587329

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page