Commit 7ffcff2d by Tianqi Chen Committed by GitHub

[DOC] Release note (#340)

parent ae6abe82
Subproject commit 326e2fa18734f0592d257da6b8cfaae90a499c5c Subproject commit f3eb854595ff99f4b05a5d8034bcacea30ef045b
...@@ -3,13 +3,32 @@ TVM Change Log ...@@ -3,13 +3,32 @@ TVM Change Log
This file records the changes in TVM library in reverse chronological order. This file records the changes in TVM library in reverse chronological order.
## Initial version (0.1rc) ## 0.1rc
- Language runtime
- python
- javascript
- java
- c++
- Backend
- arm, x86
- javascript, wasm
- CUDA
- opencl
- Metal
- DNN Library integration
- RPC runtime
- TOPI operator pipeline python
- TOPI operator pipeline in C++
- Rough perf of the TOPI GPU pipeline
- Rough pref of TOPI CPU pipeline
- End to end graph executors
## Initial version
- Pack libary into shared library. - Pack libary into shared library.
- External function and contrib libraries - External function and contrib libraries
- Metal backend
- OpenCL backend
- CUDA backend
- LLVM backend
- DLPack integration support - DLPack integration support
- AOT and module system - AOT and module system
- Basic code structure ready. - Basic code structure ready.
\ No newline at end of file
TVM: Tensor IR Stack for Deep Learning Systems
==============================================
[![GitHub license](http://dmlc.github.io/img/apache2.svg)](./LICENSE) [![GitHub license](http://dmlc.github.io/img/apache2.svg)](./LICENSE)
[![Build Status](http://mode-gpu.cs.washington.edu:8080/buildStatus/icon?job=dmlc/tvm/master)](http://mode-gpu.cs.washington.edu:8080/job/dmlc/job/tvm/job/master/) [![Build Status](http://mode-gpu.cs.washington.edu:8080/buildStatus/icon?job=dmlc/tvm/master)](http://mode-gpu.cs.washington.edu:8080/job/dmlc/job/tvm/job/master/)
...@@ -9,12 +12,11 @@ ...@@ -9,12 +12,11 @@
[Contributors](CONTRIBUTORS.md) | [Contributors](CONTRIBUTORS.md) |
[Release Notes](NEWS.md) [Release Notes](NEWS.md)
TVM: Tensor IR Stack for Deep Learning Systems
==============================================
TVM is a Tensor intermediate representation(IR) stack for deep learning systems. It is designed to close the gap between the TVM is a Tensor intermediate representation(IR) stack for deep learning systems. It is designed to close the gap between the
productivity-focused deep learning frameworks, and the performance- and efficiency-focused hardware backends. productivity-focused deep learning frameworks, and the performance- and efficiency-focused hardware backends.
TVM works with deep learning frameworks to provide end to end compilation to different backends. TVM works with deep learning frameworks to provide end to end compilation to different backends.
License License
------- -------
© Contributors, 2017. Licensed under an [Apache-2.0](https://github.com/dmlc/tvm/blob/master/LICENSE) license. © Contributors, 2017. Licensed under an [Apache-2.0](https://github.com/dmlc/tvm/blob/master/LICENSE) license.
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