Kaustubh Shivdikar

According to our database, Kaustubh Shivdikar authored at least 14 papers between 2019 and 2024.

Collaborative distances:

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

2024

ASPLOS 2024 Artifact for "MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training".

Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding

Dataset, February, 2024

ASPLOS 2024 Artifact for "MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training".

Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding

Dataset, February, 2024

Scalability Limitations of Processing-in-Memory using Real System Evaluations.

Gilbert Jonatan, Haeyoon Cho, Hyojun Son, Xiangyu Wu, Neal Livesay, Evelio Mora, Kaustubh Shivdikar, José L. Abellán, Ajay Joshi, David R. Kaeli, John Kim

Proc. ACM Meas. Anal. Comput. Syst., 2024

NeuraChip: Accelerating GNN Computations with a Hash-based Decoupled Spatial Accelerator.

Kaustubh Shivdikar, Nicolas Bohm Agostini, Malith Jayaweera, Gilbert Jonatan, José L. Abellán, Ajay Joshi, John Kim, David R. Kaeli

Proceedings of the 51st ACM/IEEE Annual International Symposium on Computer Architecture, 2024

MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training.

Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Md Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding

Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2024

2023

Accelerating Finite Field Arithmetic for Homomorphic Encryption on GPUs.

Neal Livesay, Gilbert Jonatan, Evelio Mora, Kaustubh Shivdikar, Rashmi Agrawal, Ajay Joshi, José L. Abellán, John Kim, David R. Kaeli

IEEE Micro, 2023

Enabling Accelerators for Graph Computing.

Kaustubh Shivdikar

CoRR, 2023

MaxK-GNN: Towards Theoretical Speed Limits for Accelerating Graph Neural Networks Training.

Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Md Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding

CoRR, 2023

GME: GPU-based Microarchitectural Extensions to Accelerate Homomorphic Encryption.

Kaustubh Shivdikar, Yuhui Bao, Rashmi Agrawal, Michael Tian Shen, Gilbert Jonatan, Evelio Mora, Alexander Ingare, Neal Livesay, José L. Abellán, John Kim, Ajay Joshi, David R. Kaeli

Proceedings of the 56th Annual IEEE/ACM International Symposium on Microarchitecture, 2023

2022

Accelerating Polynomial Multiplication for Homomorphic Encryption on GPUs.

Kaustubh Shivdikar, Gilbert Jonatan, Evelio Mora, Neal Livesay, Rashmi Agrawal, Ajay Joshi, José L. Abellán, John Kim, David R. Kaeli

Proceedings of the 2022 IEEE International Symposium on Secure and Private Execution Environment Design (SEED), 2022

2021

SMASH: Sparse Matrix Atomic Scratchpad Hashing.

Kaustubh Shivdikar

CoRR, 2021

JAXED: Reverse Engineering DNN Architectures Leveraging JIT GEMM Libraries.

Malith Jayaweera, Kaustubh Shivdikar, Yanzhi Wang, David R. Kaeli

Proceedings of the 2021 International Symposium on Secure and Private Execution Environment Design (SEED), 2021

GNNMark: A Benchmark Suite to Characterize Graph Neural Network Training on GPUs.

Trinayan Baruah, Kaustubh Shivdikar, Shi Dong, Yifan Sun, Saiful A. Mojumder, Kihoon Jung, José L. Abellán, Yash Ukidave, Ajay Joshi, John Kim, David R. Kaeli

Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software, 2021

2019

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.

Christopher C. Bunn, Harrison Barclay, A. Lazarev, F. Yusuf, J. Fitch, J. Booth, Kaustubh Shivdikar, David R. Kaeli

Parallel Comput., 2019