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