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)

GNNMark: A Benchmark Suite to Characterize Graph Neural Network Training on GPUs. - Trinayan Baruah; Kaustubh Shivdikar; Shi Dong 002; Yifan Sun 002; Saiful A. Mojumder; Kihoon Jung; José L. Abellán; Yash Ukidave; Ajay Joshi; John Kim 001; David R. Kaeli (ISPASS, 2021)

JAXED: Reverse Engineering DNN Architectures Leveraging JIT GEMM Libraries. - Malith Jayaweera; Kaustubh Shivdikar; Yanzhi Wang; David R. Kaeli (SEED, 2021)

SMASH: Sparse Matrix Atomic Scratchpad Hashing. - Kaustubh Shivdikar (CoRR, 2021)

Accelerating Polynomial Multiplication for Homomorphic Encryption on GPUs. - Kaustubh Shivdikar; Gilbert Jonatan; Evelio Mora; Neal Livesay; Rashmi Agrawal 001; Ajay Joshi; José L. Abellán; John Kim 001; David R. Kaeli (SEED, 2022)

GME: GPU-based Microarchitectural Extensions to Accelerate Homomorphic Encryption. - Kaustubh Shivdikar; Yuhui Bao; Rashmi Agrawal 001; Michael Tian Shen; Gilbert Jonatan; Evelio Mora; Alexander Ingare; Neal Livesay; José L. Abellán; John Kim 001; Ajay Joshi; David R. Kaeli (MICRO, 2023)

MaxK-GNN: Towards Theoretical Speed Limits for Accelerating Graph Neural Networks Training. - Hongwu Peng; Xi Xie; Kaustubh Shivdikar; Md Amit Hasan 001; Jiahui Zhao; Shaoyi Huang; Omer Khan; David R. Kaeli; Caiwen Ding (CoRR, 2023)

Enabling Accelerators for Graph Computing. - Kaustubh Shivdikar (CoRR, 2023)

Accelerating Finite Field Arithmetic for Homomorphic Encryption on GPUs. - Neal Livesay; Gilbert Jonatan; Evelio Mora; Kaustubh Shivdikar; Rashmi Agrawal 001; Ajay Joshi; José L. Abellán; John Kim 001; David R. Kaeli (IEEE Micro, 2023)

MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training. - Hongwu Peng; Xi Xie; Kaustubh Shivdikar; Md Amit Hasan 001; Jiahui Zhao; Shaoyi Huang; Omer Khan; David R. Kaeli; Caiwen Ding (ASPLOS (2), 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 001; David R. Kaeli (ISCA, 2024)

Scalability Limitations of Processing-in-Memory using Real System Evaluations. - Gilbert Jonatan; Haeyoon Cho 002; Hyojun Son; Xiangyu Wu; Neal Livesay; Evelio Mora; Kaustubh Shivdikar; José L. Abellán; Ajay Joshi; David R. Kaeli; John Kim 001 (Proc. ACM Meas. Anal. Comput. Syst., 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 001; Jiahui Zhao; Shaoyi Huang; Omer Khan; David R. Kaeli; Caiwen Ding (Zenodo, 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 001; Jiahui Zhao; Shaoyi Huang; Omer Khan; David R. Kaeli; Caiwen Ding (Zenodo, 2024)

PIMnet: A Domain-Specific Network for Efficient Collective Communication in Scalable PIM. - Hyojun Son; Gilbert Jonatan; Xiangyu Wu; Haeyoon Cho 002; Kaustubh Shivdikar; José L. Abellán; Ajay Joshi; David R. Kaeli; John Kim 001 (HPCA, 2025)

FIDESlib: A Fully-Fledged Open-Source FHE Library for Efficient CKKS on GPUs. - Carlos Agulló-Domingo; Óscar Vera-López; Seyda Guzelhan; Lohit Daksha; Aymane El Jerari; Kaustubh Shivdikar; Rashmi S. Agrawal 001; David R. Kaeli; Ajay Joshi; José L. Abellán (ISPASS, 2025)