a96a4a9bcc
* removing programming out of end to end example for now * updating TOPI library to use gemm tensor intrinsic * bug fix, autoschedule in TOPI conv lib * removing the deprecated GEVM intrinsic * refactoring, fixed lint test * fix for integer division bug * python3 bug fix for non matching types due to float division * comment |
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README.md
Open Deep Learning Compiler Stack
Documentation | Contributors | Community | Release Notes
TVM is a compiler 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. TVM works with deep learning frameworks to provide end to end compilation to different backends. Checkout the tvm stack homepage for more information.
License
© Contributors Licensed under an Apache-2.0 license.
Contribute to TVM
TVM adopts apache committer model, we aim to create an open source project that is maintained and owned by the community. Checkout the Contributor Guide
Acknowledgement
We learnt a lot from the following projects when building TVM.
- Halide: TVM uses HalideIR as data structure for arithematic simplification and low level lowering. We also learnt and adapted some part of lowering pipeline from Halide.
- Loopy: use of integer set analysis and its loop transformation primitives.
- Theano: the design inspiration of symbolic scan operator for recurrence.