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Projects to be developed as part of Apache MXNet ecosystem can be included.
Q3 2018: Focus on Quality and Technical Debt
- Resolution of github issues: bugs, tests, builds, installation
- Translate Documentation
- Documentation of inference thread support and limitations
- High quality support for MKL (incl. MKL-DNN)
- Subgraph API for integrating backend accelerators with MXNet
- quantization flow for INT8 with MKL-DNN (suggested by Patrick patric.zhao@intel.com)
- Integration with Tensor RT (experimental in Q2)
- Gluon CV, NLP toolkit
- Increase example and tutorial coverage for various application domains - “MXNet by Example”
- Performance profiling and improvements
- Language API improvements - what is the community interest?: R (training), Java (wrapped around Scala?, inference), C++ (inference)
Q4 2018: Focus on feature gaps
- Resolution of github issues: performance, operators, feature requests
- Resolution of github issues: R, Gluon, C++, Python
- Scalability improvement for distributed processing
- Distributed training for Gluon CV, NLP toolkit
- Community contributions: array creation routines
- CI & validation for MXNet examples
- Increase example and tutorial coverage for various application domains - “MXNet by Example”
- Android SDK for mobile devices
Q1 2019: Focus on Language AP
- Increase example and tutorial coverage for various application domains - “MXNet by Example”
- Support for low-bit precision inferencing
- IoT device support for inferencing
- MKL-DNN RNN API supports (patric.zhao@intel.com)
- Support for MacOS High Sierra and Mojave
Q2 2019: TBD
- Increase example and tutorial coverage for various application domains - “MXNet by Example”
Future: Longterm ideas
- Model interpretability