Difference between revisions of "Kaustubh Shivdikar"

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[[File:Kaustubh Shivdikar Cropped and Mirrored Image.jpg|thumb]]
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I am a Ph.D. candidate studying in [https://ece.northeastern.edu/groups/nucar/index.html NUCAR] lab at [https://www.northeastern.edu/ Northeastern University] under the guidance of [https://ece.northeastern.edu/fac-ece/kaeli.html Dr. David Kaeli].
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I am a Ph.D. candidate studying in [https://ece.northeastern.edu/groups/nucar/index.html NUCAR] lab at [https://www.northeastern.edu/ Northeastern University] under the guidance of [https://ece.northeastern.edu/fac-ece/kaeli.html Dr. David Kaeli]. My research focuses on designing '''hardware accelerators''' for '''sparse graph workloads'''.
 
 
My research focuses on designing '''hardware accelerators''' for '''sparse graph workloads'''.
 
  
 
My expertise lies in:
 
My expertise lies in:
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*Sparse Matrix Accelerators
 
*Sparse Matrix Accelerators
 
*Homomorphic Encryption Accelerators
 
*Homomorphic Encryption Accelerators
*GPU Kernel Designs
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*GPU Kernel Design
  
 
Contact: shivdikar.k [at] northeastern [dot] edu, mail [at] kaustubh [dot] us
 
Contact: shivdikar.k [at] northeastern [dot] edu, mail [at] kaustubh [dot] us
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==Recent News==
 
==Recent News==
  
*April 2022: Served Submission co-chair for [https://hpca-conf.org/2022/ HPCA 2022] conference.
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*May 2022: Served '''Submission co-chair''' for [https://hpca-conf.org/2022/ HPCA 2022] conference.
*
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*April 2019: '''Graduate Innovator Award''' at the RISE 2019 Research Expo for our poster Pi-Tiles
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*April 2018: '''Best Poster Award''' at the RISE 2018 Research Expo for our poster The Prime Hexagon
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*November 2018: Mentored the NEU team for '''Student Cluster Contest''' at Super Computing Conference 2018
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*November 2017: Joined the NEU Team for '''Student Cluster Contest''' at Super Computing Conference 2017
  
 
==Publications==
 
==Publications==
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[https://www.researchgate.net/profile/Kaustubh-Shivdikar ResearchGate]  [https://scholar.google.com/citations?user=NCTXsGMAAAAJ&hl=en&oi=ao Google Scholar]
  
 
*'''Accelerating Polynomial Multiplication for Homomorphic Encryption on GPUs'''
 
*'''Accelerating Polynomial Multiplication for Homomorphic Encryption on GPUs'''
**SEED 2022: International Symposium on Secure and Private Execution Environment Design
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*'''JAXED: Reverse Engineering DNN Architectures Leveraging JIT GEMM Libraries'''
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*'''GNNMark: A benchmark suite to characterize graph neural network training on GPUs'''
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*'''SMASH: Sparse Matrix Atomic Scratchpad Hashing'''
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*'''Student cluster competition 2018, team northeastern university: Reproducing performance of a multi-physics simulations of the Tsunamigenic 2004 Sumatra Megathrust earthquake on the AMD EPYC 7551 architecture'''
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*'''Speeding up DNNs using HPL based Fine-grained Tiling for Distributed Multi-GPU Training'''
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*'''Video steganography using encrypted payload for satellite communication'''
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*'''Missing'Middle Scenarios' Uncovering Nuanced Conditions in Latin America's Housing Crisis'''
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*'''Dynamic power allocation using Stackelberg game in a wireless sensor network'''
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*'''Automatic image annotation using a hybrid engine'''
  
 
<br />
 
<br />
 
==What is KTB Wiki?==
 
==What is KTB Wiki?==
 
This website was built on KTB Wiki. KTB wiki is my side project/attempt to consolidate knowledge gained during my Ph.D. journey. Though many other platforms provide similar service, the process of creating KTB Wiki was a learning experience since it taught me concepts indexing, load balancing, and in-memory file systems. KTB Wiki was built using MediaWiki and is intended for research purposes only.<blockquote>''<big>KTB Wiki, because the best way to store your knowledge is in an indexed SQL database.</big>''</blockquote>
 
This website was built on KTB Wiki. KTB wiki is my side project/attempt to consolidate knowledge gained during my Ph.D. journey. Though many other platforms provide similar service, the process of creating KTB Wiki was a learning experience since it taught me concepts indexing, load balancing, and in-memory file systems. KTB Wiki was built using MediaWiki and is intended for research purposes only.<blockquote>''<big>KTB Wiki, because the best way to store your knowledge is in an indexed SQL database.</big>''</blockquote>
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== Hobbies ==
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<br />
 
==Interesting Reads==
 
==Interesting Reads==
 
Coming soon...
 
Coming soon...

Revision as of 17:06, 19 August 2022

Kaustubh Shivdikar Cropped and Mirrored Image.jpg

I am a Ph.D. candidate studying in NUCAR lab at Northeastern University under the guidance of Dr. David Kaeli. My research focuses on designing hardware accelerators for sparse graph workloads.

My expertise lies in:

  • Computer Architecture Simulator Design
  • Graph Neural Network Accelerators
  • Sparse Matrix Accelerators
  • Homomorphic Encryption Accelerators
  • GPU Kernel Design

Contact: shivdikar.k [at] northeastern [dot] edu, mail [at] kaustubh [dot] us

Education

  • Ph.D., Compuer Engineering, Northeastern University, Boston [Expected Fall 2022]
  • M.S., Electrical and Computer Engineering, Northeastern University, Boston [May 2021]
  • B.S., Electrical Engineering, Veermata Jijabai Technological Institute, University of Mumbai, India [May 2016]

Work

  • Summer-Fall 2020 Coop: Parallel Computing Lab (Fabrizio Petrini), Intel, developed novel architectural features.
  • Summer-Fall 2019 Coop: Parallel Computing Lab (Fabrizio Petrini), Intel, designed SpGEMM kernels for Intel’s new architecture.
  • Summer-Fall 2018 Coop: Omron Adept (George Paul), implemented parallel graph traversal algorithms for Robot Path Planning.

Recent News

  • May 2022: Served Submission co-chair for HPCA 2022 conference.
  • April 2019: Graduate Innovator Award at the RISE 2019 Research Expo for our poster Pi-Tiles
  • April 2018: Best Poster Award at the RISE 2018 Research Expo for our poster The Prime Hexagon
  • November 2018: Mentored the NEU team for Student Cluster Contest at Super Computing Conference 2018
  • November 2017: Joined the NEU Team for Student Cluster Contest at Super Computing Conference 2017

Publications

ResearchGate Google Scholar

  • Accelerating Polynomial Multiplication for Homomorphic Encryption on GPUs
  • JAXED: Reverse Engineering DNN Architectures Leveraging JIT GEMM Libraries
  • GNNMark: A benchmark suite to characterize graph neural network training on GPUs
  • SMASH: Sparse Matrix Atomic Scratchpad Hashing
  • Student cluster competition 2018, team northeastern university: Reproducing performance of a multi-physics simulations of the Tsunamigenic 2004 Sumatra Megathrust earthquake on the AMD EPYC 7551 architecture
  • Speeding up DNNs using HPL based Fine-grained Tiling for Distributed Multi-GPU Training
  • Video steganography using encrypted payload for satellite communication
  • Missing'Middle Scenarios' Uncovering Nuanced Conditions in Latin America's Housing Crisis
  • Dynamic power allocation using Stackelberg game in a wireless sensor network
  • Automatic image annotation using a hybrid engine


What is KTB Wiki?

This website was built on KTB Wiki. KTB wiki is my side project/attempt to consolidate knowledge gained during my Ph.D. journey. Though many other platforms provide similar service, the process of creating KTB Wiki was a learning experience since it taught me concepts indexing, load balancing, and in-memory file systems. KTB Wiki was built using MediaWiki and is intended for research purposes only.

KTB Wiki, because the best way to store your knowledge is in an indexed SQL database.

Hobbies


Interesting Reads

Coming soon...