diff --git a/README.md b/README.md index 30147f9..f779f33 100644 --- a/README.md +++ b/README.md @@ -77,21 +77,26 @@ target_link_libraries(LLVMMLPass PRIVATE LLVMMLBridge) ``` To use TensorFlow AOT Model Runner, you need to make use of `tf_find_and_compile` method exposed in [`cmake/modules/TensorFlowCompile.cmake`](cmake/modules/TensorFlowCompile.cmake) in the CMakeLists.txt of your pass with appropriate arguments. An example of integrating TF AOT Model with inlining pass is shown [here](https://github.com/IITH-Compilers/ml-llvm-project/blob/tfmodel/llvm/lib/Analysis/CMakeLists.txt). -## Examples -TBD - ## Artifacts Libraries are autogenerated for every relevant check-in with GitHub actions. Such generated artifacts are tagged along with the successful runs of [`Publish`]() action. ## Citation ``` -@misc{venkatakeerthy-2023-MLCompilerBridge, - title={The Next 700 ML-Enabled Compiler Optimizations}, - author={S. VenkataKeerthy and Siddharth Jain and Umesh Kalvakuntla and Pranav Sai Gorantla and Rajiv Shailesh Chitale and Eugene Brevdo and Albert Cohen and Mircea Trofin and Ramakrishna Upadrasta}, - year={2023}, - eprint={2311.10800}, - archivePrefix={arXiv}, - primaryClass={cs.PL} +@inproceedings{venkatakeerthy-2024-MLCompilerBridge, +author = {VenkataKeerthy, S. and Jain, Siddharth and Kalvakuntla, Umesh and Gorantla, Pranav Sai and Chitale, Rajiv Shailesh and Brevdo, Eugene and Cohen, Albert and Trofin, Mircea and Upadrasta, Ramakrishna}, +title = {The Next 700 ML-Enabled Compiler Optimizations}, +year = {2024}, +isbn = {9798400705076}, +publisher = {Association for Computing Machinery}, +address = {New York, NY, USA}, +url = {https://doi.org/10.1145/3640537.3641580}, +doi = {10.1145/3640537.3641580}, +booktitle = {Proceedings of the 33rd ACM SIGPLAN International Conference on Compiler Construction}, +pages = {238–249}, +numpages = {12}, +keywords = {Machine Learning for Compiler Optimizations, ONNX, Pipes, TensorFlow AOT, gRPC}, +location = {, Edinburgh, United Kingdom, }, +series = {CC 2024} } ```