Skip to content
This repository has been archived by the owner on Aug 5, 2022. It is now read-only.

Caffe_v1.1.1

Compare
Choose a tag to compare
@jgong5 jgong5 released this 27 Mar 00:16
· 231 commits to master since this release
  • Features
  1. INT8 inference
    Inference speed improved with upgraded MKL-DNN library.
    Accuracy improved with channel-wise scaling factor. Support added in calibration tool as well.
  2. Multi-node training
    Better training scalability on 10Gbe with prioritized communication in gradient all-reduce.
    Support Python binding for multi-node training in pycaffe.
    Default build now includes multi-node training feature.
  3. Layer performance optimization: dilated convolution and softmax
  4. Auxiliary scripts
    Added a script to parse the training log and plot loss trends (tools/extra/caffe_log_parser.py and tools/extra/plot_loss_trends.py).
    Added a script to identify the batch size for optimal throughput given a model (scripts/obtain_optimal_batch_size.py).
    Improved benchmark scripts to support Inception-V3 and VGG-16
  5. New models
    Support inference of R-FCN object detection model.
    Added the Inception-V3 multi-node model that converges to SOTA.
  6. Build improvement
    Merged PR#167 "Extended cmake install package script for MKL"
    Fixed all ICC/GCC compiler warnings and enabled warning as error.
    Added build options to turn off each inference model optimization.
    Do not try to download MKL-DNN when there is no network connection.
  • Misc
  1. MLSL upgraded to 2018-Preview
  2. MKL-DNN upgraded to 464c268e544bae26f9b85a2acb9122c766a4c396