Anand Venkat
Anand Venkat
Research Scientist, Intel Labs
Verified email at intel.com
Title
Cited by
Cited by
Year
Non-affine extensions to polyhedral code generation
A Venkat, M Shantharam, M Hall, MM Strout
Proceedings of Annual IEEE/ACM International Symposium on Code Generation …, 2014
652014
Loop and data transformations for sparse matrix code
A Venkat, M Hall, M Strout
ACM SIGPLAN Notices 50 (6), 521-532, 2015
582015
Automating wavefront parallelization for sparse matrix computations
A Venkat, MS Mohammadi, J Park, H Rong, R Barik, MM Strout, M Hall
SC'16: Proceedings of the International Conference for High Performance …, 2016
372016
Towards making autotuning mainstream
P Basu, M Hall, M Khan, S Maindola, S Muralidharan, S Ramalingam, ...
The International journal of high performance computing applications 27 (4 …, 2013
222013
Compiler generation and autotuning of communication-avoiding operators for geometric multigrid
P Basu, A Venkat, M Hall, S Williams, B Van Straalen, L Oliker
20th Annual International Conference on High Performance Computing, 452-461, 2013
212013
Synchronization Trade-offs in GPU implementations of Graph Algorithms
R Kaleem, A Venkat, S Pai, M Hall, K Pingali
IEEE International Parallel & Distributed Processing Symposium (IPDPS 2016), 2016
162016
Optimizing LOBPCG: Sparse Matrix Loop and Data Transformations in Action
K Ahmad, A Venkat, M Hall
The 29th International Workshop on Languages and Compilers for Parallel …, 2016
92016
SWIRL: High-performance many-core CPU code generation for deep neural networks
A Venkat, T Rusira, R Barik, M Hall, L Truong
The International Journal of High Performance Computing Applications 33 (6 …, 2019
62019
Sparse computation data dependence simplification for efficient compiler-generated inspectors
MS Mohammadi, T Yuki, K Cheshmi, EC Davis, M Hall, MM Dehnavi, ...
Proceedings of the 40th ACM SIGPLAN Conference on Programming Language …, 2019
52019
High-Performance Deep Learning via a Single Building Block
E Georganas, K Banerjee, D Kalamkar, S Avancha, A Venkat, ...
arXiv preprint arXiv:1906.06440, 2019
32019
Combining Polyhedral and AST Transformations in CHiLL
H Zhang, A Venkat, P Basu, M Hall
Proceedings of the Sixth International Workshop on Polyhedral Compilation …, 2016
32016
Extending index-array properties for data dependence analysis
MS Mohammadi, K Cheshmi, MM Dehnavi, A Venkat, T Yuki, MM Strout
International Workshop on Languages and Compilers for Parallel Computing, 78-93, 2018
22018
Compiler transformation to generate hybrid sparse computations
H Zhang, A Venkat, M Hall
2016 6th Workshop on Irregular Applications: Architecture and Algorithms …, 2016
22016
ISA mapper: a compute and hardware agnostic deep learning compiler
M Sotoudeh, A Venkat, M Anderson, E Georganas, A Heinecke, J Knight
Proceedings of the 16th ACM International Conference on Computing Frontiers …, 2019
12019
Sparse matrix code dependence analysis simplification at compile time
M Soltan Mohammadi, K Cheshmi, G Gopalakrishnan, M Hall, ...
arXiv, arXiv: 1807.10852, 2018
12018
Understanding the performance of small convolution operations for cnn on intel architecture
A Heinecke, E Georganas, K Banerjee, D Kalmakar, N Sundaram, ...
SC, 2017
12017
MISIM: An End-to-End Neural Code Similarity System
F Ye, S Zhou, A Venkat, R Marucs, N Tatbul, JJ Tithi, P Petersen, ...
arXiv preprint arXiv:2006.05265, 2020
2020
Context-Aware Parse Trees
F Ye, S Zhou, A Venkat, R Marcus, P Petersen, JJ Tithi, T Mattson, ...
arXiv preprint arXiv:2003.11118, 2020
2020
Extending Index-Array Properties for Data Dependence Analysis
A Venkat, T Yuki, MM Strout
Languages and Compilers for Parallel Computing: 31st International Workshop …, 2019
2019
Sparse Matrix Code Dependence Analysis Simplification at Compile Time
MS Mohammadi, K Cheshmi, G Gopalakrishnan, M Hall, MM Dehnavi, ...
arXiv preprint arXiv:1807.10852, 2018
2018
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