Dipankar Das

According to our database, Dipankar Das authored at least 35 papers between 2005 and 2021.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2021

A Lightweight Error-Resiliency Mechanism for Deep Neural Networks.

Brunno F. Goldstein, Victor da Cruz Ferreira, Sudarshan Srinivasan, Dipankar Das, Alexandre Solon Nery, Sandip Kundu, Felipe M. G. França

Proceedings of the 22nd International Symposium on Quality Electronic Design, 2021

Extending Sparse Tensor Accelerators to Support Multiple Compression Formats.

Eric Qin, Geonhwa Jeong, William Won, Sheng-Chun Kao, Hyoukjun Kwon, Sudarshan Srinivasan, Dipankar Das, Gordon Euhyun Moon, Sivasankaran Rajamanickam, Tushar Krishna

Proceedings of the 35th IEEE International Parallel and Distributed Processing Symposium, 2021

GNNerator: A Hardware/Software Framework for Accelerating Graph Neural Networks.

Jacob R. Stevens, Dipankar Das, Sasikanth Avancha, Bharat Kaul, Anand Raghunathan

Proceedings of the 58th ACM/IEEE Design Automation Conference, 2021

2020

Reliability Evaluation of Compressed Deep Learning Models.

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

Proceedings of the 11th IEEE Latin American Symposium on Circuits & Systems, 2020

SIGMA: A Sparse and Irregular GEMM Accelerator with Flexible Interconnects for DNN Training.

Eric Qin, Ananda Samajdar, Hyoukjun Kwon, Vineet Nadella, Sudarshan Srinivasan, Dipankar Das, Bharat Kaul, Tushar Krishna

Proceedings of the IEEE International Symposium on High Performance Computer Architecture, 2020

2019

K-TanH: Hardware Efficient Activations For Deep Learning.

Abhisek Kundu, Sudarshan Srinivasan, Eric C. Qin, Dhiraj D. Kalamkar, Naveen K. Mellempudi, Dipankar Das, Kunal Banerjee, Bharat Kaul, Pradeep Dubey

CoRR, 2019

High Performance Scalable FPGA Accelerator for Deep Neural Networks.

Sudarshan Srinivasan, Pradeep Janedula, Saurabh Dhoble, Sasikanth Avancha, Dipankar Das, Naveen Mellempudi, Bharat Daga, Martin Langhammer, Gregg Baeckler, Bharat Kaul

CoRR, 2019

Mixed Precision Training With 8-bit Floating Point.

Naveen Mellempudi, Sudarshan Srinivasan, Dipankar Das, Bharat Kaul

CoRR, 2019

A Study of BFLOAT16 for Deep Learning Training.

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

CoRR, 2019

Manna: An Accelerator for Memory-Augmented Neural Networks.

Jacob R. Stevens, Ashish Ranjan, Dipankar Das, Bharat Kaul, Anand Raghunathan

Proceedings of the 52nd Annual IEEE/ACM International Symposium on Microarchitecture, 2019

X-MANN: A Crossbar based Architecture for Memory Augmented Neural Networks.

Ashish Ranjan, Shubham Jain, Jacob R. Stevens, Dipankar Das, Bharat Kaul, Anand Raghunathan

Proceedings of the 56th Annual Design Automation Conference 2019, 2019

2018

On Scale-out Deep Learning Training for Cloud and HPC.

Srinivas Sridharan, Karthikeyan Vaidyanathan, Dhiraj D. Kalamkar, Dipankar Das, Mikhail E. Smorkalov, Mikhail Shiryaev, Dheevatsa Mudigere, Naveen Mellempudi, Sasikanth Avancha, Bharat Kaul, Pradeep Dubey

CoRR, 2018

Mixed Precision Training of Convolutional Neural Networks using Integer Operations.

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

Proceedings of the 6th International Conference on Learning Representations, 2018

Out-of-Distribution Detection Using an Ensemble of Self Supervised Leave-Out Classifiers.

Apoorv Vyas, Nataraj Jammalamadaka, Xia Zhu, Dipankar Das, Bharat Kaul, Theodore L. Willke

Proceedings of the Computer Vision - ECCV 2018, 2018

RAIL: Risk-Averse Imitation Learning.

Anirban Santara, Abhishek Naik, Balaraman Ravindran, Dipankar Das, Dheevatsa Mudigere, Sasikanth Avancha, Bharat Kaul

Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, 2018

2017

Ternary Neural Networks with Fine-Grained Quantization.

Naveen Mellempudi, Abhisek Kundu, Dheevatsa Mudigere, Dipankar Das, Bharat Kaul, Pradeep Dubey

CoRR, 2017

Mixed Low-precision Deep Learning Inference using Dynamic Fixed Point.

Naveen Mellempudi, Abhisek Kundu, Dipankar Das, Dheevatsa Mudigere, Bharat Kaul

CoRR, 2017

Ternary Residual Networks.

Abhisek Kundu, Kunal Banerjee, Naveen Mellempudi, Dheevatsa Mudigere, Dipankar Das, Bharat Kaul, Pradeep Dubey

CoRR, 2017

ScaleDeep: A Scalable Compute Architecture for Learning and Evaluating Deep Networks.

Swagath Venkataramani, Ashish Ranjan, Subarno Banerjee, Dipankar Das, Sasikanth Avancha, Ashok Jagannathan, Ajaya Durg, Dheemanth Nagaraj, Bharat Kaul, Pradeep Dubey, Anand Raghunathan

Proceedings of the 44th Annual International Symposium on Computer Architecture, 2017

2016

Distributed Deep Learning Using Synchronous Stochastic Gradient Descent.

Dipankar Das, Sasikanth Avancha, Dheevatsa Mudigere, Karthikeyan Vaidyanathan, Srinivas Sridharan, Dhiraj D. Kalamkar, Bharat Kaul, Pradeep Dubey

CoRR, 2016

2015

GraphMat: High performance graph analytics made productive.

Narayanan Sundaram, Nadathur Satish, Md. Mostofa Ali Patwary, Subramanya Dulloor, Michael J. Anderson, Satya Gautam Vadlamudi, Dipankar Das, Pradeep Dubey

Proc. VLDB Endow., 2015

GraphMat: High performance graph analytics made productive.

Narayanan Sundaram, Nadathur Rajagopalan Satish, Md. Mostofa Ali Patwary, Subramanya Dulloor, Satya Gautam Vadlamudi, Dipankar Das, Pradeep Dubey

CoRR, 2015

Parallel Efficient Sparse Matrix-Matrix Multiplication on Multicore Platforms.

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

Proceedings of the High Performance Computing - 30th International Conference, 2015

Improving concurrency and asynchrony in multithreaded MPI applications using software offloading.

Karthikeyan Vaidyanathan, Dhiraj D. Kalamkar, Kiran Pamnany, Jeff R. Hammond, Pavan Balaji, Dipankar Das, Jongsoo Park, Bálint Joó

Proceedings of the International Conference for High Performance Computing, 2015

2013

Prediction Schemes for Compensating Variable Delay for Improving Performance of Real-Time Control Tasks.

Saptarshi Roy, Amit Patra, Partha Pratim Chakrabarti, Purnendu Sinha, Dipankar Das

Proceedings of the 26th International Conference on VLSI Design and 12th International Conference on Embedded Systems, 2013

2012

Finding Critical Components in Embedded Control Systems Sensitive to Quality-Faults.

Vishal Shrivastav, Satya Gautam Vadlamudi, P. P. Chakrabarti, Dipankar Das, Purnendu Sinha

Proceedings of the International Symposium on Electronic System Design, 2012

2011

Robust embedded software design through early analysis of quality faults.

Dipankar Das, P. P. Chakrabarti, Purnendu Sinha

Proceedings of the Proceeding of the 4th Annual India Software Engineering Conference, 2011

A framework for early stage quality-fault tolerance analysis of embedded control systems.

Satya Gautam Vadlamudi, P. P. Chakrabarti, Dipankar Das, Purnendu Sinha

Proceedings of the 2011 IEEE/IFIP International Conference on Dependable Systems and Networks, 2011

2010

Thermal analysis of multiprocessor SoC applications by simulation and verification.

Dipankar Das, P. P. Chakrabarti, Rajeev Kumar

ACM Trans. Design Autom. Electr. Syst., 2010

2009

Scenario-based timing verification of multiprocessor embedded applications.

Dipankar Das, P. P. Chakrabarti, Rajeev Kumar

ACM Trans. Design Autom. Electr. Syst., 2009

2008

Code compression for performance enhancement of variable-length embedded processors.

Rajeev Kumar, Dipankar Das

ACM Trans. Embed. Comput. Syst., 2008

2007

Functional verification of task partitioning for multiprocessor embedded systems.

Dipankar Das, P. P. Chakrabarti, Rajeev Kumar

ACM Trans. Design Autom. Electr. Syst., 2007

2006

SystemC Modeling and Validation of A RISC Processor System.

Rajeev Kumar, Rahul Chaudhry, Dipankar Das, Vibha Rathi, Subrat Kumar Panda, P. P. Chakrabarti

Proceedings of the Forum on specification and Design Languages, 2006

Timing Verification of UML Activity Diagram Based Code Block Level Models for Real Time Multiprocessor System-on-Chip Applications.

Dipankar Das, Rajeev Kumar, P. P. Chakrabarti

Proceedings of the 13th Asia-Pacific Software Engineering Conference (APSEC 2006), 2006

2005

Dictionary Based Code Compression for Variable Length Instruction Encodings.

Dipankar Das, Rajeev Kumar, P. P. Chakrabarti

Proceedings of the 18th International Conference on VLSI Design (VLSI Design 2005), 2005