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Anand Venkat
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2020 – today
- 2021
- [c13]Tharindu Rusira Patabandi
, Anand Venkat
Predictive data locality optimization for higher-order tensor computations. MAPS@PLDI 2021: 43-52 - 2020
- [c12]Evangelos Georganas, Kunal Banerjee, Dhiraj D. Kalamkar, Sasikanth Avancha, Anand Venkat, Michael J. Anderson, Greg Henry, Hans Pabst, Alexander Heinecke:
Harnessing Deep Learning via a Single Building Block. IPDPS 2020: 222-233 - [i5]Fangke Ye, Shengtian Zhou, Anand Venkat, Ryan Marcus, Paul Petersen, Jesmin Jahan Tithi, Tim Mattson, Tim Kraska, Pradeep Dubey, Vivek Sarkar, Justin Gottschlich:
Context-Aware Parse Trees. CoRR abs/2003.11118 (2020) - [i4]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:
MISIM: An End-to-End Neural Code Similarity System. CoRR abs/2006.05265 (2020)
2010 – 2019
- 2019
- [j2]Anand Venkat
SWIRL: High-performance many-core CPU code generation for deep neural networks. Int. J. High Perform. Comput. Appl. 33(6) (2019) - [c11]Matthew Sotoudeh
ISA mapper: a compute and hardware agnostic deep learning compiler. CF 2019: 164-173 - [c10]Tharindu Rusira Patabandi
SWIRL++ : Evaluating Performance Models to Guide Code Transformation in Convolutional Neural Networks. LCPC 2019: 108-126 - [c9]Mahdi Soltan Mohammadi, Tomofumi Yuki, Kazem Cheshmi, Eddie C. Davis, Mary W. Hall
Sparse computation data dependence simplification for efficient compiler-generated inspectors. PLDI 2019: 594-609 - [i3]Evangelos Georganas, Kunal Banerjee, Dhiraj D. Kalamkar, Sasikanth Avancha, Anand Venkat, Michael J. Anderson, Greg Henry, Hans Pabst, Alexander Heinecke:
High-Performance Deep Learning via a Single Building Block. CoRR abs/1906.06440 (2019) - 2018
- [c8]Mahdi Soltan Mohammadi, Kazem Cheshmi, Maryam Mehri Dehnavi, Anand Venkat, Tomofumi Yuki, Michelle Mills Strout:
Extending Index-Array Properties for Data Dependence Analysis. LCPC 2018: 78-93 - [i2]Mahdi Soltan Mohammadi, Kazem Cheshmi, Ganesh Gopalakrishnan, Mary W. Hall, Maryam Mehri Dehnavi, Anand Venkat, Tomofumi Yuki, Michelle Mills Strout:
Sparse Matrix Code Dependence Analysis Simplification at Compile Time. CoRR abs/1807.10852 (2018) - [i1]Matthew Sotoudeh, Anand Venkat, Michael J. Anderson, Evangelos Georganas, Alexander Heinecke, Jason Knight:
ISA Mapper: A Compute and Hardware Agnostic Deep Learning Compiler. CoRR abs/1810.09958 (2018) - 2016
- [b1]Anand Venkat:
An Integrated Compiler and Runtime Framework for Sparse Matrix Codes. University of Utah, USA, 2016 - [c7]Rashid Kaleem, Anand Venkat, Sreepathi Pai
Synchronization Trade-Offs in GPU Implementations of Graph Algorithms. IPDPS 2016: 514-523 - [c6]Khalid Ahmad, Anand Venkat, Mary W. Hall
Optimizing LOBPCG: Sparse Matrix Loop and Data Transformations in Action. LCPC 2016: 218-232 - [c5]Huihui Zhang, Anand Venkat, Mary W. Hall:
Compiler Transformation to Generate Hybrid Sparse Computations. IA3@SC 2016: 34-41 - [c4]Anand Venkat, Mahdi Soltan Mohammadi, Jongsoo Park, Hongbo Rong, Rajkishore Barik, Michelle Mills Strout, Mary W. Hall
Automating wavefront parallelization for sparse matrix computations. SC 2016: 480-491 - 2015
- [c3]Anand Venkat, Mary W. Hall
Loop and data transformations for sparse matrix code. PLDI 2015: 521-532 - 2014
- [c2]Anand Venkat, Manu Shantharam, Mary W. Hall, Michelle Mills Strout:
Non-affine Extensions to Polyhedral Code Generation. CGO 2014: 185 - 2013
- [j1]Protonu Basu, Mary W. Hall
Towards making autotuning mainstream. Int. J. High Perform. Comput. Appl. 27(4): 379-393 (2013) - [c1]Protonu Basu, Anand Venkat, Mary W. Hall
Compiler generation and autotuning of communication-avoiding operators for geometric multigrid. HiPC 2013: 452-461
Coauthor Index
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