All Versions
18
Latest Version
Avg Release Cycle
183 days
Latest Release
938 days ago

Changelog History
Page 1

  • v2.4.0 Changes

    November 13, 2023

    Highlights

    _ Note: _ BigDL v2.4.0 has been updated to include functional and security updates. Users should update to the latest version.

  • v2.3.0 Changes

    April 16, 2025

    🚀 Please to go https://github.com/ipex-llm/ipex-llm/releases/tag/v2.3.0-nightly for the downloads.

  • v2.2.0 Changes

    April 07, 2025

    Highlights

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

    🚀 Please go to https://github.com/ipex-llm/ipex-llm/releases/tag/v2.2.0 for the downloads.

  • v2.1.0 Changes

    August 22, 2024

    Highlights

    _ Note: _ IPEX-LLM v2.1.0 has been updated to include functional and security updates. Users should update to the latest version.

  • v2.0.0 Changes

    March 09, 2022

    Highlights

    _ Note: _ BigDL v2.0.0 has been updated to include functional and security updates. Users should update to the latest version.

  • v0.13.0

    July 09, 2021

  • v0.12.2

    April 21, 2021

  • v0.10.0 Changes

    November 05, 2019

    Highlights

    🐎 Continue RNN optimization. We support both LSTM and GRU integration with MKL-DNN which acheives ~3x performance

    👍 ONNX support. We support loading third party framework models via ONNX

    👍 Richer data preprocssing support and segmentation inference pipeline support

    Details

    • 👍 [New Feature] Full MaskRCNN model support with data processing
    • 👍 [New Feature] Support variable-size Resize
    • 👍 [New Feature] Support batch input for region proposal
    • 👍 [New Feature] Support samples of different size in one minibatch
    • [New Feature] MAP validation method implementation
    • 👍 [New Feature] ROILabel enhancement to support both object detection and segmentation
    • 👍 [New Feature] Grey image support for segmentation
    • 👍 [New Feature] Add TopBlocks support for Feature Pyramid Networks (FPN)
    • 👍 [New Feature] GRU integration with MKL-DNN support
    • 👍 [New Feature] MaskHead support for MaskRCNN
    • 👍 [New Feature] BoxHead support for MaskRCNN
    • 👍 [New Feature] RegionalProposal support for MaskRCNN
    • 👍 [New Feature] Shape operation support for ONNX
    • 👍 [New Feature] Gemm operation support for ONNX
    • 👍 [New Feature] Gather operation support for ONNX
    • 👍 [New Feature] AveragePool operation support for ONNX
    • 👍 [New Feature] BatchNormalization operation support for ONNX
    • 👍 [New Feature] Concat operation support for ONNX
    • 👍 [New Feature] Conv operation support for ONNX
    • 👍 [New Feature] MaxPool operation support for ONNX
    • 👍 [New Feature] Reshape operation support for ONNX
    • 👍 [New Feature] Relu operation support for ONNX
    • 👍 [New Feature] SoftMax operation support for ONNX
    • 👍 [New Feature] Sum operation support for ONNX
    • 👍 [New Feature] Squeeze operation support for ONNX
    • 👍 [New Feature] Const operation support for ONNX
    • [New Feature] ONNX model loader implementation
    • 👍 [New Feature] RioAlign layer support
    • [Enhancement] Align batch normalization layer between mklblas and mkl-dnn
    • 👍 [Enhancement] Python API enhancement to support nested list input
    • 👍 [Enhancement] Multi-model training/inference support with MKL-DNN
    • [Enhancement] BatchNormalization fusion with Scale
    • 👍 [Enhancement] SoftMax companion object support no argument initialization
    • 👍 [Enhancement] Python support for training with MKL-DNN
    • 📄 [Enhancement] Docs enhancement
    • [Bug Fix] Fix model version comparison
    • [Bug Fix] Fix graph backward bug for ParallelTable
    • [Bug Fix] Fix memory leak for training with MKL-DNN
    • 🐎 [Bug Fix] Fix performance caused by denormal values during training
    • [Bug Fix] Fix SoftMax segment fault issue under MKL-DNN
    • [Bug Fix] Fix TimeDistributedCriterion python API inconsistent with Scala

  • v0.9.0 Changes

    July 22, 2019

    Highlights

    ✨ Continue VNNI acceleration support, we add optimization for more CNN models including object detection models, enhance model scales generation support for VNNI.

    ➕ Add attention based model support, we add Transformer implementation for both lanuage model and translation model.

    🐎 RNN optimization, We support LSTM integration with MKL-DNN which acheives ~3x performance speedup.

    Details

    • 👍 [New Feature] Add attention layer support
    • 👍 [New Feature] Add FeedForwardNetwork layer support
    • 👍 [New Feature] Add ExpandSize layer support
    • 👍 [New Feature] Add TableOperation layer to support table calculation with different input sizes
    • 👍 [New Feature] Add LayerNormalizaiton layer support
    • 🌐 [New Feature] Add Transformer support for both language and translation models
    • 👍 [New Feature] Add beam search support in Transformer model
    • [New Feature] Add Layer-wise adaptve rate scaling optim method
    • 👍 [New Feature] Add LSTM integration with MKL-DNN support
    • 👍 [New Feature] Add dilated convolution integration with MKL-DNN support
    • [New Feature] Add parameter process for LarsSGD optim method
    • 👍 [New Feature] Support Affinity binding option with mkl-dnn
    • 🏗 [Enhancement] Document enhancement for configuration and build
    • 0️⃣ [Enhancement] Reflection enhancement to get default values for constructor parameters
    • [Enhhancement] User one AllReducemParameter for multi-optim method training
    • 👍 [Enhancement] CAddTable layer enhancement to support input expansion along specific dimension
    • [Enhancement] Resnet-50 preprocessing pipeline enhancement to replace RandomCropper with CenterCropper
    • [Enhancement] Calculate model scales for arbitrary mask
    • [Enhancment] Enable global average pooling
    • [Enhancement] Check input shape and underlying MKL-DNN layout consistency
    • 👻 [Enhancement] Threadpool enhancement to throw proper exception at executor runtime
    • 👍 [Enhancement] Support mkl-dnn format conversion from ntc to tnc
    • [Bug Fix] Fix backward graph generation topology ordering issue
    • [Bug Fix] Fix MemoryData hash code calculation
    • 🌲 [Bug Fix] Fix log output for BCECriterion
    • [Bug Fix] Fix setting mask for container quantization
    • 👷 [Bug Fix] Fix validation accuracy issue when multi-executor running with the same worker
    • [Bug Fix] Fix INT8 layer fusion between conlution with multi-group masks and BatchNormalization
    • [Bug Fix] Fix JoinTable scales generation issue
    • [Bug Fix] Fix CMul forward issue with special input format
    • [Bug Fix] Fix weights change issue after model fusion issue
    • [Bug Fix] Fix SpatinalConvolution primitives initializaiton issue

  • v0.8.0 Changes

    March 28, 2019

    Highlights

    • ➕ Add MKL-DNN Int8 support, especially for VNNI acceleration support. Low precision inference accelerates both latency and throughput significantly
    • ➕ Add support for runnning MKL-BLAS models under MKL-DNN. We leverage MKL-DNN to speed up both training and inference for MKL-BLAS models
    • ➕ Add Spark 2.4 support. Our examples and APIs are fully compatible with Spark 2.4, we released the binary for Spark 2.4 together with other Spark versions

    Details

    • 👍 [New Feature] Add MKL-DNN Int8 support, especially for VNNI support
    • 👍 [New Feature] Add support for runnning MKL-BLAS models under MKL-DNN
    • 👍 [New Feature] Add Spark 2.4 support
    • [New Feature] Add auto fusion to speed up model inference
    • 👍 [New Feature] Memoery reorder support for low precision inference
    • 👍 [New Feature] Add bytes support for DNN Tensor
    • [New Feature] Add SAME padding in MKL-DNN layers
    • [New Feature] Add combined (add/or) triggers for training completion
    • 👍 [Enhancement] Inception-V1 python training support enhancement
    • ⚡️ [Enhancement] Distributed Optimizer enhancement to support customized optimizer
    • 👍 [Enhancement] Add compute output shape for DNN supported layers
    • [Enhancement] New MKL-DNN computing thread pool
    • 👍 [Enhancement] Add MKL-DNN support for Predictor
    • 📚 [Enhancement] Documentation enhancement for Sparse Tensor, MKL-DNN support, etc
    • [Enhancement] Add ceilm mode for AvgPooling and MaxPooling layers
    • 👍 [Enhacement] Add binary classification support for DLClassifierModel
    • 👍 [Enhacement] Improvement to support conversion between NHWC and NCHW for memory reoder
    • [Bug Fix] Fix SoftMax layer with narrowed input
    • 👍 [Bug Fix] TensorFlow loader to support checking all data types
    • 👍 [Bug Fix] Fix Add operation bug to support double type when loading TensorFlow graph
    • ⚡️ [Bug Fix] Fix one-step weight update missing issue in validation during training
    • 🔒 [Bug Fix] Fix scala compiler security issue in 2.10 & 2.11
    • [Bug Fix] Fix model broadcast cache UUID issue
    • [Bug Fix] Fix predictor issue for batch size == 1