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ORCIDSasikanth Avancha
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2020 – today
- 2024
[i20]Maksym Korablyov, Cheng-Hao Liu, Moksh Jain, Almer M. van der Sloot
, Eric Jolicoeur, Edward Ruediger, Andrei Cristian Nica, Emmanuel Bengio, Kostiantyn Lapchevskyi, Daniel St-Cyr, Doris Alexandra Schuetz, Victor Ion Butoi, Jarrid Rector-Brooks, Simon Blackburn, Leo Feng, Hadi Nekoei, Sai Krishna Gottipati, Priyesh Vijayan, Prateek Gupta, Ladislav Rampásek, Sasikanth Avancha, Pierre-Luc Bacon, William L. Hamilton, Brooks Paige, Sanchit Misra, Stanislaw Kamil Jastrzebski, Bharat Kaul, Doina Precup, José Miguel Hernández-Lobato, Marwin H. S. Segler, Michael M. Bronstein, Anne Marinier, Mike Tyers, Yoshua Bengio:
Generative Active Learning for the Search of Small-molecule Protein Binders. CoRR abs/2405.01616 (2024)- 2022
- [j11]Evangelos Georganas, Dhiraj D. Kalamkar, Sasikanth Avancha, Menachem Adelman, Deepti Aggarwal, Cristina Anderson, Alexander Breuer, Jeremy Bruestle, Narendra Chaudhary, Abhisek Kundu, Denise Kutnick, Frank Laub, Md. Vasimuddin, Sanchit Misra, Ramanarayan Mohanty, Hans Pabst, Brian Retford, Barukh Ziv, Alexander Heinecke:
Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning and HPC Workloads. Frontiers Appl. Math. Stat. 8: 826269 (2022) - [i19]Md. Vasimuddin, Ramanarayan Mohanty, Sanchit Misra, Sasikanth Avancha:
DistGNN-MB: Distributed Large-Scale Graph Neural Network Training on x86 via Minibatch Sampling. CoRR abs/2211.06385 (2022) - 2021
- [j10]Shail Dave, Riyadh Baghdadi, Tony Nowatzki, Sasikanth Avancha, Aviral Shrivastava, Baoxin Li:
Hardware Acceleration of Sparse and Irregular Tensor Computations of ML Models: A Survey and Insights. Proc. IEEE 109(10): 1706-1752 (2021) - [j9]Sanket Tavarageri, Alexander Heinecke, Sasikanth Avancha, Bharat Kaul, Gagandeep Goyal, Ramakrishna Upadrasta:
PolyDL: Polyhedral Optimizations for Creation of High-performance DL Primitives. ACM Trans. Archit. Code Optim. 18(1): 11:1-11:27 (2021) - [c18]Rohan Saphal, Balaraman Ravindran, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul:
SEERL: Sample Efficient Ensemble Reinforcement Learning. AAMAS 2021: 1100-1108 - [c17]Jacob R. Stevens, Dipankar Das, Sasikanth Avancha, Bharat Kaul, Anand Raghunathan:
GNNerator: A Hardware/Software Framework for Accelerating Graph Neural Networks. DAC 2021: 955-960 - [c16]Evangelos Georganas, Dhiraj D. Kalamkar, Sasikanth Avancha, Menachem Adelman, Cristina Anderson, Alexander Breuer, Jeremy Bruestle, Narendra Chaudhary, Abhisek Kundu, Denise Kutnick, Frank Laub, Md. Vasimuddin, Sanchit Misra, Ramanarayan Mohanty, Hans Pabst, Barukh Ziv, Alexander Heinecke:
Tensor processing primitives: a programming abstraction for efficiency and portability in deep learning workloads. SC 2021: 14 - [c15]Md. Vasimuddin, Sanchit Misra, Guixiang Ma, Ramanarayan Mohanty, Evangelos Georganas, Alexander Heinecke, Dhiraj D. Kalamkar, Nesreen K. Ahmed, Sasikanth Avancha:
DistGNN: scalable distributed training for large-scale graph neural networks. SC 2021: 76 - [i18]Jacob R. Stevens, Dipankar Das, Sasikanth Avancha, Bharat Kaul, Anand Raghunathan:
GNNerator: A Hardware/Software Framework for Accelerating Graph Neural Networks. CoRR abs/2103.10836 (2021) - [i17]Sanket Tavarageri, Gagandeep Goyal, Sasikanth Avancha, Bharat Kaul, Ramakrishna Upadrasta:
AI Powered Compiler Techniques for DL Code Optimization. CoRR abs/2104.05573 (2021) - [i16]Evangelos Georganas, Dhiraj D. Kalamkar, Sasikanth Avancha, Menachem Adelman, Cristina Anderson, Alexander Breuer, Narendra Chaudhary, Abhisek Kundu, Md. Vasimuddin, Sanchit Misra, Ramanarayan Mohanty, Hans Pabst, Barukh Ziv, Alexander Heinecke:
Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning Workloads. CoRR abs/2104.05755 (2021) - [i15]Md. Vasimuddin, Sanchit Misra, Guixiang Ma, Ramanarayan Mohanty, Evangelos Georganas, Alexander Heinecke, Dhiraj D. Kalamkar, Nesreen K. Ahmed, Sasikanth Avancha:
DistGNN: Scalable Distributed Training for Large-Scale Graph Neural Networks. CoRR abs/2104.06700 (2021) - 2020
- [c14]Rohan Saphal, Balaraman Ravindran, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul:
ERLP: Ensembles of Reinforcement Learning Policies (Student Abstract). AAAI 2020: 13905-13906 - [c13]Brian Hickmann, Jieasheng Chen, Michael Rotzin, Andrew Yang, Maciej Urbanski, Sasikanth Avancha:
Intel Nervana Neural Network Processor-T (NNP-T) Fused Floating Point Many-Term Dot Product. ARITH 2020: 133-136 - [c12]Shail Dave, Aviral Shrivastava, Youngbin Kim, Sasikanth Avancha, Kyoungwoo Lee:
dMazeRunner: Optimizing Convolutions on Dataflow Accelerators. ICASSP 2020: 1544-1548 - [c11]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 - [i14]Rohan Saphal, Balaraman Ravindran, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul:
SEERL: Sample Efficient Ensemble Reinforcement Learning. CoRR abs/2001.05209 (2020) - [i13]Sanket Tavarageri, Alexander Heinecke, Sasikanth Avancha, Gagandeep Goyal, Ramakrishna Upadrasta, Bharat Kaul:
PolyScientist: Automatic Loop Transformations Combined with Microkernels for Optimization of Deep Learning Primitives. CoRR abs/2002.02145 (2020) - [i12]Sanket Tavarageri, Alexander Heinecke, Sasikanth Avancha, Gagandeep Goyal, Ramakrishna Upadrasta, Bharat Kaul:
PolyDL: Polyhedral Optimizations for Creation of High Performance DL primitives. CoRR abs/2006.02230 (2020) - [i11]Shail Dave, Riyadh Baghdadi, Tony Nowatzki, Sasikanth Avancha, Aviral Shrivastava, Baoxin Li:
Hardware Acceleration of Sparse and Irregular Tensor Computations of ML Models: A Survey and Insights. CoRR abs/2007.00864 (2020) - [i10]Sasikanth Avancha, Md. Vasimuddin, Sanchit Misra, Ramanarayan Mohanty:
Deep Graph Library Optimizations for Intel(R) x86 Architecture. CoRR abs/2007.06354 (2020)
2010 – 2019
- 2019
- [j8]Shail Dave, Youngbin Kim, Sasikanth Avancha, Kyoungwoo Lee, Aviral Shrivastava:
dMazeRunner: Executing Perfectly Nested Loops on Dataflow Accelerators. ACM Trans. Embed. Comput. Syst. 18(5s): 70:1-70:27 (2019) - [i9]Dhiraj D. Kalamkar, Dheevatsa Mudigere, Naveen Mellempudi, Dipankar Das, Kunal Banerjee, Sasikanth Avancha, Dharma Teja Vooturi, Nataraj Jammalamadaka, Jianyu Huang, Hector Yuen, Jiyan Yang, Jongsoo Park, Alexander Heinecke, Evangelos Georganas, Sudarshan Srinivasan, Abhisek Kundu, Misha Smelyanskiy, Bharat Kaul, Pradeep Dubey:
A Study of BFLOAT16 for Deep Learning Training. CoRR abs/1905.12322 (2019) - [i8]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) - [i7]Sudarshan Srinivasan, Pradeep Janedula, Saurabh Dhoble, Sasikanth Avancha, Dipankar Das, Naveen Mellempudi, Bharat Daga, Martin Langhammer, Gregg Baeckler, Bharat Kaul:
High Performance Scalable FPGA Accelerator for Deep Neural Networks. CoRR abs/1908.11809 (2019) - 2018
- [c10]Anirban Santara, Abhishek Naik, Balaraman Ravindran, Dipankar Das, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul:
RAIL: Risk-Averse Imitation Learning. AAMAS 2018: 2062-2063 - [c9]Dipankar Das, Naveen Mellempudi, Dheevatsa Mudigere, Dhiraj D. Kalamkar, Sasikanth Avancha, Kunal Banerjee, Srinivas Sridharan, Karthik Vaidyanathan, Bharat Kaul, Evangelos Georganas, Alexander Heinecke, Pradeep Dubey, Jesús Corbal, Nikita Shustrov, Roman Dubtsov, Evarist Fomenko, Vadim O. Pirogov:
Mixed Precision Training of Convolutional Neural Networks using Integer Operations. ICLR (Poster) 2018 - [c8]Evangelos Georganas, Sasikanth Avancha, Kunal Banerjee, Dhiraj D. Kalamkar, Greg Henry, Hans Pabst, Alexander Heinecke:
Anatomy of high-performance deep learning convolutions on SIMD architectures. SC 2018: 66:1-66:12 - [i6]Srinivas Sridharan, Karthikeyan Vaidyanathan, Dhiraj D. Kalamkar, Dipankar Das, Mikhail E. Smorkalov, Mikhail Shiryaev, Dheevatsa Mudigere, Naveen Mellempudi, Sasikanth Avancha, Bharat Kaul, Pradeep Dubey:
On Scale-out Deep Learning Training for Cloud and HPC. CoRR abs/1801.08030 (2018) - [i5]Dipankar Das, Naveen Mellempudi, Dheevatsa Mudigere, Dhiraj D. Kalamkar, Sasikanth Avancha, Kunal Banerjee, Srinivas Sridharan, Karthik Vaidyanathan, Bharat Kaul, Evangelos Georganas, Alexander Heinecke, Pradeep Dubey, Jesús Corbal, Nikita Shustrov, Roman Dubtsov, Evarist Fomenko, Vadim O. Pirogov:
Mixed Precision Training of Convolutional Neural Networks using Integer Operations. CoRR abs/1802.00930 (2018) - [i4]Dharma Teja Vooturi, Dheevatsa Mudigere, Sasikanth Avancha:
Hierarchical Block Sparse Neural Networks. CoRR abs/1808.03420 (2018) - [i3]Evangelos Georganas, Sasikanth Avancha, Kunal Banerjee, Dhiraj D. Kalamkar, Greg Henry, Hans Pabst, Alexander Heinecke:
Anatomy Of High-Performance Deep Learning Convolutions On SIMD Architectures. CoRR abs/1808.05567 (2018) - 2017
- [c7]Swagath Venkataramani, Ashish Ranjan, Subarno Banerjee, Dipankar Das, Sasikanth Avancha, Ashok Jagannathan, Ajaya Durg, Dheemanth Nagaraj, Bharat Kaul, Pradeep Dubey, Anand Raghunathan:
ScaleDeep: A Scalable Compute Architecture for Learning and Evaluating Deep Networks. ISCA 2017: 13-26 - [i2]Anirban Santara, Abhishek Naik, Balaraman Ravindran, Dipankar Das, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul:
RAIL: Risk-Averse Imitation Learning. CoRR abs/1707.06658 (2017) - 2016
- [i1]Dipankar Das, Sasikanth Avancha, Dheevatsa Mudigere, Karthikeyan Vaidyanathan, Srinivas Sridharan, Dhiraj D. Kalamkar, Bharat Kaul, Pradeep Dubey:
Distributed Deep Learning Using Synchronous Stochastic Gradient Descent. CoRR abs/1602.06709 (2016) - 2012
- [j7]Sasikanth Avancha, Amit S. Baxi, David Kotz:
Privacy in mobile technology for personal healthcare. ACM Comput. Surv. 45(1): 3:1-3:54 (2012) - [c6]Karthikeyan Vaidyanathan, Sasikanth Avancha, Sunil Sherlekar:
Exascale Computing & Beyond: Meeting the Challenges. High Performance Computing Workshop (2) 2012: 24-34
2000 – 2009
- 2008
- [c5]Sasikanth Avancha:
A Framework for Trustworthy Service-Oriented Computing (Short Paper). ICISS 2008: 124-131 - 2007
- [p1]Li Ding, Pranam Kolari, Zhongli Ding, Sasikanth Avancha:
Using Ontologies in the Semantic Web: A Survey. Ontologies 2007: 79-113 - 2004
- [c4]Sasikanth Avancha, Chintan Patel, Anupam Joshi:
Ontology-Driven Adaptive Sensor Networks. MobiQuitous 2004: 194-202 - [r1]Sasikanth Avancha, Dipanjan Chakraborty, Filip Perich, Anupam Joshi:
Data and Services for Mobile Computing. The Practical Handbook of Internet Computing 2004 - 2003
- [j6]Sasikanth Avancha, Jeffrey Undercoffer, Anupam Joshi, John Pinkston:
Secure sensor networks for perimeter protection. Comput. Networks 43(4): 421-435 (2003) - [j5]Sasikanth Avancha, Peter D'Souza, Filip Perich, Anupam Joshi, Yelena Yesha:
P2P M-commerce in pervasive environments. SIGecom Exch. 3(4): 1-9 (2003) - 2002
- [j4]Sasikanth Avancha, Vlad Korolev, Anupam Joshi, Timothy W. Finin, Yelena Yesha:
On experiments with a transport protocol for pervasive computing environments. Comput. Networks 40(4): 515-535 (2002) - [j3]Sasikanth Avancha, Anupam Joshi, Timothy W. Finin:
Enhanced Service Discovery in Bluetooth. Computer 35(6): 96-99 (2002) - [j2]Timothy W. Finin, Anupam Joshi, Lalana Kagal, Olga Ratsimore, Sasikanth Avancha, Vlad Korolev, Harry Chen, Filip Perich, R. Scott Cost:
Intelligent Agents for Mobile and Embedded Devices. Int. J. Cooperative Inf. Syst. 11(3): 205-230 (2002) - [j1]Lalana Kagal, Vlad Korolev, Sasikanth Avancha, Anupam Joshi, Timothy W. Finin, Yelena Yesha:
Centaurus: An Infrastructure for Service Management in Ubiquitous Computing Environments. Wirel. Networks 8(6): 619-635 (2002) - [c3]Filip Perich, Sasikanth Avancha, Dipanjan Chakraborty, Anupam Joshi, Yelena Yesha:
Profile Driven Data Management for Pervasive Environments. DEXA 2002: 361-370 - [c2]Bhagyalaxmi Bethala, Anupam Joshi, Dhananjay S. Phatak, Sasikanth Avancha, Tom Goff:
Simulation of a Common Access Point for Bluetooth, 802.11 and Wired LANs. PDPTA 2002: 918-922 - 2001
- [c1]Sasikanth Avancha, Vladimir Korolev, Anupam Joshi, Timothy W. Finin:
Transport protocols in wireless networks. ICCCN 2001: 310-317
Coauthor Index
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last updated on 2024-10-07 21:22 CEST by the dblp team
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