TVM: Tensor IR Stack for Deep Learning Systems
Installation | Documentation | Tutorials | Operator Inventory | FAQ | Contributors | Release Notes
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. TVM works with deep learning frameworks to provide end to end compilation to different backends. Checkout our announcement for more details.
License
© Contributors, 2017. 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.
- Contributor Guide
- Please add your name to CONTRIBUTORS.md
- Please also update NEWS.md on changes and improvements in API and codes.
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.