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BigDL release 2.2.0
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@Le-Zheng Le-Zheng released this 19 Jan 05:18
· 11 commits to branch-2.2 since this release
v2.2.0
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Highlights

Note: BigDL v2.2.0 has been updated to include functional and security updates. Users should update to the latest version.

  • Nano
    • Extend BigDL Nano inference to support iGPU and more data types (INT8/BF16/FP16 quantization)
    • More performance features (e.g., InferenceOptimizer for Keras, Nano decorator for PyTorch training loop, Nano Context Manager for thread number control and autocast, etc.)
    • Support installation with more PyTorch/TensorFlow versions and conditional dependencies on different platforms
  • PPML
    • Upgrade BigDL PPML solution to support new LibOS (e.g., Gramine1.3.1, Occlum0.29.2) with better security, higher performance, more stability and easier deployment.
    • Support more Big Data frameworks (Spark 3.1.3, Flink, Hive etc.), more Python and Data Science tools (Numpy, Pandas, sklearn, Torch Serv, Triton, Flask etc.), and distributed DL training using Orca
    • Improve the Attestation (e.g., MREnclave Attestation), Key Management (e.g., multi-KMS) & Encryption (e.g., transparent encryption) features for better end-to-end secure pipeline.
    • Initial support of BigDL PPML on SPR TDX (Virtual Machine and TDX Confidential Container)
  • Chronos
    • Extend BigDL Chronos to support Windows and Mac, and new Python versions (3.8/3.9)
    • Provide a benchmark tool for Chronos users to evaluate Chronos performance on their platform
    • More performance features (e.g., accuracy and performance improvement for TCNForecaster, lower memory usage, auto optimization search, faster and portable TSDataset, etc.)
  • Friesian
    • LightGBM training support
    • Performance improvements for online serving pipeline
  • Orca
    • Improve Orca Estimator APIs for better user experience
    • Memory optimization for distributed training with Spark DataFrame,
    • Better support for image inputs and visualization with Xshards
    • Distributed MMCV applications using Orca
  • Documentation
    • Tutorials for running BigDL Orca on YARN/K8s/Databricks
    • BigDL PPML solutions on Azure
    • How-to guides and examples for Chronos forecasting and deployment process
Assets 2