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singa-incubating-0.3.0 Release Notes

SINGA is a general distributed deep learning platform for training big deep learning models over large datasets. It is designed with an intuitive programming model based on the layer abstraction. SINGA supports a wide variety of popular deep learning models.

This release includes following features:

  • GPU Support

    • [SINGA-131] Implement and optimize hybrid training using both CPU and GPU
    • [SINGA-136] Support cuDNN v4
    • [SINGA-134] Extend SINGA to run over a GPU cluster
    • [Singa-157] Change the priority of cudnn library and install libsingagpu.so

  • Remove Dependences

    • [SINGA-156] Remove the dependency on ZMQ for single process training
    • [SINGA-155] Remove zookeeper for single-process training

  • Python Binding

    • [SINGA-126] Python Binding for Interactive Training

  • Other Improvements

    • [SINGA-80] New Blob Level and Address Level Math Operation Interface
    • [SINGA-130] Data Prefetching
    • [SINGA-145] New SGD based optimization Updaters: AdaDelta, Adam, AdamMax

  • Bugs Fixed

    • [SINGA-148] Race condition between Worker threads and Driver
    • [SINGA-150] Mesos Docker container failed
    • [SIGNA-141] Undesired Hash collision when locating process id to worker…
    • [SINGA-149] Docker build fail
    • [Singa-143] The compilation cannot detect libsingagpu.so file