Abhimanyu Bambhaniya

According to our database, Abhimanyu Bambhaniya authored at least 12 papers between 2022 and 2025.

Collaborative distances:

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

2025

Understanding and Optimizing Multi-Stage AI Inference Pipelines.

Abhimanyu Rajeshkumar Bambhaniya, Hanjiang Wu, Suvinay Subramanian, Sudarshan Srinivasan, Souvik Kundu, Amir Yazdanbakhsh, Midhilesh Elavazhagan, Madhu Kumar, Tushar Krishna

CoRR, April, 2025

Progressive Gradient Flow for Robust N:M Sparsity Training in Transformers.

Abhimanyu Rajeshkumar Bambhaniya, Amir Yazdanbakhsh, Suvinay Subramanian, Sheng-Chun Kao, Shivani Agrawal, Utku Evci, Tushar Krishna

Proceedings of the Conference on Parsimony and Learning, 2025

2024

Demystifying Platform Requirements for Diverse LLM Inference Use Cases.

Abhimanyu Bambhaniya, Ritik Raj, Geonhwa Jeong, Souvik Kundu, Sudarshan Srinivasan, Midhilesh Elavazhagan, Madhu Kumar, Tushar Krishna

CoRR, 2024

Abstracting Sparse DNN Acceleration via Structured Sparse Tensor Decomposition.

Geonhwa Jeong, Po-An Tsai, Abhimanyu Rajeshkumar Bambhaniya, Stephen W. Keckler, Tushar Krishna

CoRR, 2024

Progressive Gradient Flow for Robust N: M Sparsity Training in Transformers.

Abhimanyu Rajeshkumar Bambhaniya, Amir Yazdanbakhsh, Suvinay Subramanian, Sheng-Chun Kao, Shivani Agrawal, Utku Evci, Tushar Krishna

CoRR, 2024

Leveraging Memory Expansion to Accelerate Large-Scale DL Training.

Divya Kiran Kadiyala, Saeed Rashidi, Taekyung Heo, Abhimanyu Bambhaniya, Tushar Krishna, Alexandros Daglis

Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software, 2024

2023

Hardware-Software Co-Design for Real-Time Latency-Accuracy Navigation in Tiny Machine Learning Applications.

Payman Behnam, Jianming Tong, Alind Khare, Yangyu Chen, Yue Pan, Pranav Gadikar, Abhimanyu Bambhaniya, Tushar Krishna, Alexey Tumanov

IEEE Micro, 2023

Subgraph Stationary Hardware-Software Inference Co-Design.

Payman Behnam, Alexey Tumanov, Tushar Krishna, Pranav Gadikar, Yangyu Chen, Jianming Tong, Yue Pan, Abhimanyu Rajeshkumar Bambhaniya, Alind Khare

Proceedings of the Sixth Conference on Machine Learning and Systems, 2023

VEGETA: Vertically-Integrated Extensions for Sparse/Dense GEMM Tile Acceleration on CPUs.

Geonhwa Jeong, Sana Damani, Abhimanyu Rajeshkumar Bambhaniya, Eric Qin, Christopher J. Hughes, Sreenivas Subramoney, Hyesoon Kim, Tushar Krishna

Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2023

Proteus : HLS-based NoC Generator and Simulator.

Abhimanyu Rajeshkumar Bambhaniya, Yangyu Chen, Anshuman, Rohan Banerjee, Tushar Krishna

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2023

2022

COMET: A Comprehensive Cluster Design Methodology for Distributed Deep Learning Training.

Divya Kiran Kadiyala, Saeed Rashidi, Taekyung Heo, Abhimanyu Rajeshkumar Bambhaniya, Tushar Krishna, Alexandros Daglis

CoRR, 2022

Enabling Flexibility for Sparse Tensor Acceleration via Heterogeneity.

Eric Qin, Raveesh Garg, Abhimanyu Bambhaniya, Michael Pellauer, Angshuman Parashar, Sivasankaran Rajamanickam, Cong Hao, Tushar Krishna

CoRR, 2022