@@ -9,6 +9,77 @@ Refer to the Roadmap issue for complete list on on-going version features.
...
@@ -9,6 +9,77 @@ Refer to the Roadmap issue for complete list on on-going version features.
If you check in something that is not reflected in Roadmap issue, please reply
If you check in something that is not reflected in Roadmap issue, please reply
to that issue so it can get added.
to that issue so it can get added.
## 0.5
This release features several major improvements. Some of the highlights are: Arbitrary bits quantization algorithm; High-level auto-differentiable programming IR -- Relay.
- Fully featured 8-bit network support
- 8bit quantizer
- Arbitrary bits quantization algorithm
- Intel cpu support
- ARM cpu support
- NVidia GPU 8-bit kernel
- int8 gemm recipe
- int8 conv2d
- Autotvm integration
- Automated tuning and scheduling
- AutoTVM optimizations for mobile GPUs
- AutoTVM optimizations for CUDA
- AutoTVM optimizations for x86
- Initial release of the differentiable programming IR, Relay
- Gcc / g++ compatible C code generator for TVM #2161
- Device type annotation for heterogeneous compilation #2361
- Cache packed func ptr, lift alloca #2070
- Generalize compute to tensor region #1476
- Runtime
- Relay interpreter and compiler #1954
- Heterogeneous runtime #1695
- Language bindings: Golang runtime #1470 , Rust runtime #1597
- Add min_repeat_ms to time_evaluator #2200
- Bundled interpreter demonstration #2297
- Enable PlanMemory in the graph runtime #2120
- Language Binding
- Rust frontend #2292
- VTA
- Improved RPC for VTA #2043
- Hybrid python programming model
- Support for scheduling #2416
- Support for Inter-function call #2287
- Backend support #2477
- TOPI
- Initial support for sparse tensor computation
- Improve ARM CPU depthwise convolution performance #2345
- Port winograd ops to relay #2356
- Add faster-rcnn proposal op #2420
- Tutorials and docs
- Relay language docs #2232
- Tutorials on how to use SGX backend
- How to write a pass in python
- General lowering flow of TVM
- How to do tensorize
- TFLite frontend tutorial #2508
- Keras seq2seq model for translation tutorial #1815
- Committer guide and tips #2468
- Code review guideline on API designs #2459
## 0.4
## 0.4
This release features several major improvements. The high-level graph optimizer is now part of TVM repo. Some of the highlights are: Initial support of AutoTVM for automated optimization; customized accelerator backend VTA.
This release features several major improvements. The high-level graph optimizer is now part of TVM repo. Some of the highlights are: Initial support of AutoTVM for automated optimization; customized accelerator backend VTA.