Open deep learning compiler stack for cpu, gpu and specialized accelerators

Clone this repo:
  1. 8bd857d [RPC][REFACTOR] Use PopenWorker to handle RPC Server. (#7889) by Tianqi Chen · 14 hours ago main
  2. 78657e1 [Relay] Add support for relay expressions as pad value for static pad (#7860) by AndrewZhaoLuo · 17 hours ago
  3. bd2520f [PROFILER] Add CSV output to profiler (#7797) by Tristan Konolige · 19 hours ago
  4. d0a0194 [VTA][OpenCL] intelfocl (#6126) by ZHANG Hao · 20 hours ago
  5. fbdffeb Protect child process enumeration in AutoTVM (#7887) by PENGUINLIONG · 21 hours ago

Open Deep Learning Compiler Stack

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Apache 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.


© 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. Check out the Contributor Guide.


We learned a lot from the following projects when building TVM.

  • Halide: Part of TVM's TIR and arithmetic simplification module originates from Halide. We also learned 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.