Update README.md

README.md

@@ -63,3 +63,47 @@ results = Parallel(n_jobs=8)(
 Please visit the [Timeloop and Accelergy exercises
 repository](https://github.com/Accelergy-Project/timeloop-accelergy-exercises.git)
 for more examples and tutorials.
+
+## Citation
+Please cite the following:
+
+- A. Parashar, P. Raina, Y. S. Shao, Y.-H. Chen, V. A. Ying, A. Mukkara, R. Venkatesan, B. Khailany, S. W. Keckler, and J. Emer, “Timeloop: A systematic approach to DNN accelerator evaluation,” in 2019 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), 2019, pp. 304–315.
+- M. Horeni, P. Taheri, P. Tsai, A. Parashar, J. Emer, and S. Joshi, “Ruby: Improving hardware efficiency for tensor algebra accelerators through imperfect factorization,” in 2022 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), 2022, pp. 254–266.
+- Y. N. Wu, P.-A. Tsai, A. Parashar, V. Sze, and J. S. Emer, “Sparseloop: An analytical, energy-focused design space exploration methodology for sparse tensor accelerators,” in 2021 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), 2021, pp. 232–234.
+- Y. N. Wu, J. S. Emer, and V. Sze, “Accelergy: An architecture-level energy estimation methodology for accelerator designs,” in 2019 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2019, pp. 1–8.
+- T. Andrulis, J. S. Emer, and V. Sze, “CiMLoop: A flexible, accurate, and fast compute-in-memory modeling tool,” in 2024 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), 2024.
+
+Or use the following BibTeX:
+
+```BibTeX
+@inproceedings{timeloop,
+  author      = {Parashar, Angshuman and Raina, Priyanka and Shao, Yakun Sophia and  Chen, Yu-Hsin and Ying, Victor A and Mukkara, Anurag and Venkatesan, Rangharajan and Khailany, Brucek and Keckler, Stephen W and Emer, Joel},
+  booktitle   = {2019 IEEE international symposium on performance analysis of systems and software (ISPASS)}, pages={304--315}, year={2019},
+  title       = {Timeloop: A systematic approach to dnn accelerator evaluation},
+  year        = {2019},
+}
+@inproceedings{ruby,
+  author      = {M. Horeni and P. Taheri and P. Tsai and A. Parashar and J. Emer and S. Joshi},
+  booktitle   = {2022 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)},
+  title       = {Ruby: Improving Hardware Efficiency for Tensor Algebra Accelerators Through Imperfect Factorization},
+  year        = {2022},
+}
+@inproceedings{sparseloop,
+  author      = {Wu, Yannan N. and Tsai, Po-An, and Parashar, Angshuman and Sze, Vivienne and Emer, Joel S.},
+  booktitle   = {{ ACM/IEEE International Symposium on Microarchitecture (MICRO)}},
+  title       = {{Sparseloop: An Analytical Approach To Sparse Tensor Accelerator Modeling }},
+  year        = {{2022}}
+}
+@inproceedings{accelergy,
+  author      = {Wu, Yannan Nellie and Emer, Joel S and Sze, Vivienne},
+  booktitle   = {2019 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)},
+  title       = {Accelergy: An architecture-level energy estimation methodology for accelerator designs},
+  year        = {2019},
+}
+@inproceedings{cimloop,
+  author      = {Andrulis, Tanner and Emer, Joel S. and Sze, Vivienne},
+  booktitle   = {2024 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)}, 
+  title       = {{CiMLoop}: A Flexible, Accurate, and Fast Compute-In-Memory Modeling Tool}, 
+  year        = {2024},
+}
+```