Dipankar Das

40 papers A* 5A 4C 3Misc 2Journal 20Unranked 6
YearRankTypeTitle / Venue / Authors
2021 — conf
A Lightweight Error-Resiliency Mechanism for Deep Neural Networks.
ISQED
Brunno F. Goldstein, Victor da Cruz Ferreira, Sudarshan Srinivasan, Dipankar Das, Alexandre Solon Nery, Sandip Kundu, Felipe M. G. França
2021 A conf
Extending Sparse Tensor Accelerators to Support Multiple Compression Formats.
IPDPS
Eric Qin, Geonhwa Jeong, William Won, Sheng-Chun Kao, Hyoukjun Kwon, Sudarshan Srinivasan, Dipankar Das, Gordon Euhyun Moon, Sivasankaran Rajamanickam, Tushar Krishna
2021 J jnl
Extending Sparse Tensor Accelerators to Support Multiple Compression Formats.
CoRR
Eric Qin, Geonhwa Jeong, William Won, Sheng-Chun Kao, Hyoukjun Kwon, Sudarshan Srinivasan, Dipankar Das, Gordon Euhyun Moon, Sivasankaran Rajamanickam, Tushar Krishna
2021 A* conf
GNNerator: A Hardware/Software Framework for Accelerating Graph Neural Networks.
DAC
Jacob R. Stevens, Dipankar Das, Sasikanth Avancha, Bharat Kaul, Anand Raghunathan
2021 J jnl
GNNerator: A Hardware/Software Framework for Accelerating Graph Neural Networks.
CoRR
Jacob R. Stevens, Dipankar Das, Sasikanth Avancha, Bharat Kaul, Anand Raghunathan
2020 — conf
Reliability Evaluation of Compressed Deep Learning Models.
LASCAS
Brunno F. Goldstein, Sudarshan Srinivasan, Dipankar Das, Kunal Banerjee, Leandro Santiago de Araújo, Victor da Cruz Ferreira, Alexandre Solon Nery, Sandip Kundu, Felipe M. G. França
2020 A* conf
SIGMA: A Sparse and Irregular GEMM Accelerator with Flexible Interconnects for DNN Training.
HPCA
Eric Qin, Ananda Samajdar, Hyoukjun Kwon, Vineet Nadella, Sudarshan Srinivasan, Dipankar Das, Bharat Kaul, Tushar Krishna
2019 J jnl
A Study of BFLOAT16 for Deep Learning Training.
CoRR
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
2019 J jnl
High Performance Scalable FPGA Accelerator for Deep Neural Networks.
CoRR
Sudarshan Srinivasan, Pradeep Janedula, Saurabh Dhoble, Sasikanth Avancha, Dipankar Das, Naveen Mellempudi, Bharat Daga, Martin Langhammer, Gregg Baeckler, Bharat Kaul
2019 J jnl
K-TanH: Hardware Efficient Activations For Deep Learning.
CoRR
Abhisek Kundu, Sudarshan Srinivasan, Eric C. Qin, Dhiraj D. Kalamkar, Naveen K. Mellempudi, Dipankar Das, Kunal Banerjee, Bharat Kaul, Pradeep Dubey
2019 A* conf
Manna: An Accelerator for Memory-Augmented Neural Networks.
MICRO
Jacob R. Stevens, Ashish Ranjan, Dipankar Das, Bharat Kaul, Anand Raghunathan
2019 J jnl
Mixed Precision Training With 8-bit Floating Point.
CoRR
Naveen Mellempudi, Sudarshan Srinivasan, Dipankar Das, Bharat Kaul
2019 A* conf
X-MANN: A Crossbar based Architecture for Memory Augmented Neural Networks.
DAC
Ashish Ranjan, Shubham Jain, Jacob R. Stevens, Dipankar Das, Bharat Kaul, Anand Raghunathan
2018 — conf
Mixed Precision Training of Convolutional Neural Networks using Integer Operations.
ICLR (Poster)
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
2018 J jnl
Mixed Precision Training of Convolutional Neural Networks using Integer Operations.
CoRR
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
2018 J jnl
On Scale-out Deep Learning Training for Cloud and HPC.
CoRR
Srinivas Sridharan, Karthikeyan Vaidyanathan, Dhiraj D. Kalamkar, Dipankar Das, Mikhail E. Smorkalov, Mikhail Shiryaev, Dheevatsa Mudigere, Naveen Mellempudi, Sasikanth Avancha, Bharat Kaul, Pradeep Dubey
2018 — conf
Out-of-Distribution Detection Using an Ensemble of Self Supervised Leave-Out Classifiers.
ECCV (8)
Apoorv Vyas, Nataraj Jammalamadaka, Xia Zhu, Dipankar Das, Bharat Kaul, Theodore L. Willke
2018 J jnl
Out-of-Distribution Detection Using an Ensemble of Self Supervised Leave-out Classifiers.
CoRR
Apoorv Vyas, Nataraj Jammalamadaka, Xia Zhu, Dipankar Das, Bharat Kaul, Theodore L. Willke
2018 A conf
RAIL: Risk-Averse Imitation Learning.
AAMAS
Anirban Santara, Abhishek Naik, Balaraman Ravindran, Dipankar Das, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul
2017 J jnl
Mixed Low-precision Deep Learning Inference using Dynamic Fixed Point.
CoRR
Naveen Mellempudi, Abhisek Kundu, Dipankar Das, Dheevatsa Mudigere, Bharat Kaul
2017 J jnl
RAIL: Risk-Averse Imitation Learning.
CoRR
Anirban Santara, Abhishek Naik, Balaraman Ravindran, Dipankar Das, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul
2017 A* conf
ScaleDeep: A Scalable Compute Architecture for Learning and Evaluating Deep Networks.
ISCA
Swagath Venkataramani, Ashish Ranjan, Subarno Banerjee, Dipankar Das, Sasikanth Avancha, Ashok Jagannathan, Ajaya Durg, Dheemanth Nagaraj, Bharat Kaul, Pradeep Dubey, Anand Raghunathan
2017 J jnl
Ternary Neural Networks with Fine-Grained Quantization.
CoRR
Naveen Mellempudi, Abhisek Kundu, Dheevatsa Mudigere, Dipankar Das, Bharat Kaul, Pradeep Dubey
2017 J jnl
Ternary Residual Networks.
CoRR
Abhisek Kundu, Kunal Banerjee, Naveen Mellempudi, Dheevatsa Mudigere, Dipankar Das, Bharat Kaul, Pradeep Dubey
2016 J jnl
Distributed Deep Learning Using Synchronous Stochastic Gradient Descent.
CoRR
Dipankar Das, Sasikanth Avancha, Dheevatsa Mudigere, Karthikeyan Vaidyanathan, Srinivas Sridharan, Dhiraj D. Kalamkar, Bharat Kaul, Pradeep Dubey
2015 J jnl
GraphMat: High performance graph analytics made productive.
CoRR
Narayanan Sundaram, Nadathur Rajagopalan Satish, Md. Mostofa Ali Patwary, Subramanya Dulloor, Satya Gautam Vadlamudi, Dipankar Das, Pradeep Dubey
2015 J jnl
GraphMat: High performance graph analytics made productive.
Proc. VLDB Endow.
Narayanan Sundaram, Nadathur Satish, Md. Mostofa Ali Patwary, Subramanya Dulloor, Michael J. Anderson, Satya Gautam Vadlamudi, Dipankar Das, Pradeep Dubey
2015 A conf
Improving concurrency and asynchrony in multithreaded MPI applications using software offloading.
SC
Karthikeyan Vaidyanathan, Dhiraj D. Kalamkar, Kiran Pamnany, Jeff R. Hammond, Pavan Balaji, Dipankar Das, Jongsoo Park, Bálint Joó
2015 C conf
Parallel Efficient Sparse Matrix-Matrix Multiplication on Multicore Platforms.
ISC
Md. Mostofa Ali Patwary, Nadathur Rajagopalan Satish, Narayanan Sundaram, Jongsoo Park, Michael J. Anderson, Satya Gautam Vadlamudi, Dipankar Das, Sergey G. Pudov, Vadim O. Pirogov, Pradeep Dubey
2013 Misc conf
Prediction Schemes for Compensating Variable Delay for Improving Performance of Real-Time Control Tasks.
VLSI Design
Saptarshi Roy, Amit Patra, Partha Pratim Chakrabarti, Purnendu Sinha, Dipankar Das
2012 — conf
Finding Critical Components in Embedded Control Systems Sensitive to Quality-Faults.
ISED
Vishal Shrivastav, Satya Gautam Vadlamudi, P. P. Chakrabarti, Dipankar Das, Purnendu Sinha
2011 A conf
A framework for early stage quality-fault tolerance analysis of embedded control systems.
DSN
Satya Gautam Vadlamudi, P. P. Chakrabarti, Dipankar Das, Purnendu Sinha
2011 — conf
Robust embedded software design through early analysis of quality faults.
ISEC
Dipankar Das, P. P. Chakrabarti, Purnendu Sinha
2010 J jnl
Thermal analysis of multiprocessor SoC applications by simulation and verification.
ACM Trans. Design Autom. Electr. Syst.
Dipankar Das, P. P. Chakrabarti, Rajeev Kumar
2009 J jnl
Scenario-based timing verification of multiprocessor embedded applications.
ACM Trans. Design Autom. Electr. Syst.
Dipankar Das, P. P. Chakrabarti, Rajeev Kumar
2008 J jnl
Code compression for performance enhancement of variable-length embedded processors.
ACM Trans. Embed. Comput. Syst.
Rajeev Kumar, Dipankar Das
2007 J jnl
Functional verification of task partitioning for multiprocessor embedded systems.
ACM Trans. Design Autom. Electr. Syst.
Dipankar Das, P. P. Chakrabarti, Rajeev Kumar
2006 C conf
SystemC Modeling and Validation of A RISC Processor System.
FDL
Rajeev Kumar, Rahul Chaudhry, Dipankar Das, Vibha Rathi, Subrat Kumar Panda, P. P. Chakrabarti
2006 C conf
Timing Verification of UML Activity Diagram Based Code Block Level Models for Real Time Multiprocessor System-on-Chip Applications.
APSEC
Dipankar Das, Rajeev Kumar, P. P. Chakrabarti
2005 Misc conf
Dictionary Based Code Compression for Variable Length Instruction Encodings.
VLSI Design
Dipankar Das, Rajeev Kumar, P. P. Chakrabarti