Compiler generation and autotuning of communication-avoiding operators for geometric multigrid. - Protonu Basu; Anand Venkat; Mary W. Hall; Samuel Williams 001; Brian van Straalen; Leonid Oliker (HiPC, 2013)

Towards making autotuning mainstream. - Protonu Basu; Mary W. Hall; Malik Murtaza Khan 001; Suchit Maindola; Saurav Muralidharan; Shreyas Ramalingam; Axel Rivera; Manu Shantharam; Anand Venkat (Int. J. High Perform. Comput. Appl., 2013)

Non-affine Extensions to Polyhedral Code Generation. - Anand Venkat; Manu Shantharam; Mary W. Hall; Michelle Mills Strout (CGO, 2014)

Loop and data transformations for sparse matrix code. - Anand Venkat; Mary W. Hall; Michelle Strout (PLDI, 2015)

Synchronization Trade-Offs in GPU Implementations of Graph Algorithms. - Rashid Kaleem; Anand Venkat; Sreepathi Pai; Mary W. Hall; Keshav Pingali (IPDPS, 2016)

Optimizing LOBPCG: Sparse Matrix Loop and Data Transformations in Action. - Khalid Ahmad; Anand Venkat; Mary W. Hall (LCPC, 2016)

Automating wavefront parallelization for sparse matrix computations. - Anand Venkat; Mahdi Soltan Mohammadi; Jongsoo Park; Hongbo Rong; Rajkishore Barik; Michelle Mills Strout; Mary W. Hall (SC, 2016)

Compiler Transformation to Generate Hybrid Sparse Computations. - Huihui Zhang; Anand Venkat; Mary W. Hall (IA3@SC, 2016)

An Integrated Compiler and Runtime Framework for Sparse Matrix Codes. - Anand Venkat (2016)

Extending Index-Array Properties for Data Dependence Analysis. - Mahdi Soltan Mohammadi; Kazem Cheshmi; Maryam Mehri Dehnavi; Anand Venkat; Tomofumi Yuki; Michelle Mills Strout (LCPC, 2018)

Sparse Matrix Code Dependence Analysis Simplification at Compile Time. - Mahdi Soltan Mohammadi; Kazem Cheshmi; Ganesh Gopalakrishnan; Mary W. Hall; Maryam Mehri Dehnavi; Anand Venkat; Tomofumi Yuki; Michelle Mills Strout (CoRR, 2018)

ISA mapper: a compute and hardware agnostic deep learning compiler. - Matthew Sotoudeh; Anand Venkat; Michael J. Anderson; Evangelos Georganas; Alexander Heinecke; Jason Knight (CF, 2019)

SWIRL++ : Evaluating Performance Models to Guide Code Transformation in Convolutional Neural Networks. - Tharindu Rusira Patabandi; Anand Venkat; Rajkishore Barik; Mary W. Hall (LCPC, 2019)

Sparse computation data dependence simplification for efficient compiler-generated inspectors. - Mahdi Soltan Mohammadi; Tomofumi Yuki; Kazem Cheshmi; Eddie C. Davis; Mary W. Hall; Maryam Mehri Dehnavi; Payal Nandy; Catherine Olschanowsky; Anand Venkat; Michelle Mills Strout (PLDI, 2019)

High-Performance Deep Learning via a Single Building Block. - Evangelos Georganas; Kunal Banerjee 001; Dhiraj D. Kalamkar; Sasikanth Avancha; Anand Venkat; Michael J. Anderson; Greg Henry; Hans Pabst; Alexander Heinecke (CoRR, 2019)

SWIRL: High-performance many-core CPU code generation for deep neural networks. - Anand Venkat; Tharindu Rusira; Raj Barik; Mary W. Hall; Leonard Truong (Int. J. High Perform. Comput. Appl., 2019)

Harnessing Deep Learning via a Single Building Block. - Evangelos Georganas; Kunal Banerjee 001; Dhiraj D. Kalamkar; Sasikanth Avancha; Anand Venkat; Michael J. Anderson; Greg Henry; Hans Pabst; Alexander Heinecke (IPDPS, 2020)

Context-Aware Parse Trees. - Fangke Ye; Shengtian Zhou; Anand Venkat; Ryan Marcus; Paul Petersen; Jesmin Jahan Tithi; Tim Mattson; Tim Kraska; Pradeep Dubey; Vivek Sarkar; Justin Gottschlich (CoRR, 2020)

MISIM: An End-to-End Neural Code Similarity System. - Fangke Ye; Shengtian Zhou; Anand Venkat; Ryan Marcus; Nesime Tatbul; Jesmin Jahan Tithi; Paul Petersen; Timothy G. Mattson; Tim Kraska; Pradeep Dubey; Vivek Sarkar; Justin Gottschlich (CoRR, 2020)

Predictive data locality optimization for higher-order tensor computations. - Tharindu Rusira Patabandi; Anand Venkat; Abhishek Kulkarni; Pushkar Ratnalikar; Mary W. Hall; Justin Gottschlich (MAPS@PLDI, 2021)