Ravi Subramaniam

According to our database, Ravi Subramaniam authored at least 14 papers between 2012 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI.

Hao Kong, Di Liu, Shuo Huai, Xiangzhong Luo, Ravi Subramaniam, Christian Makaya, Qian Lin, Weichen Liu

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., December, 2023

On Hardware-Aware Design and Optimization of Edge Intelligence.

Shuo Huai, Hao Kong, Xiangzhong Luo, Di Liu, Ravi Subramaniam, Christian Makaya, Qian Lin, Weichen Liu

IEEE Des. Test, December, 2023

CRIMP: Compact & Reliable DNN Inference on In-Memory Processing via Crossbar-Aligned Compression and Non-ideality Adaptation.

Shuo Huai, Hao Kong, Xiangzhong Luo, Shiqing Li, Ravi Subramaniam, Christian Makaya, Qian Lin, Weichen Liu

ACM Trans. Embed. Comput. Syst., October, 2023

Latency-constrained DNN architecture learning for edge systems using zerorized batch normalization.

Shuo Huai, Di Liu, Hao Kong, Weichen Liu, Ravi Subramaniam, Christian Makaya, Qian Lin

Future Gener. Comput. Syst., May, 2023

EMNAPE: Efficient Multi-Dimensional Neural Architecture Pruning for EdgeAI.

Hao Kong, Xiangzhong Luo, Shuo Huai, Di Liu, Ravi Subramaniam, Christian Makaya, Qian Lin, Weichen Liu

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

Towards Efficient Convolutional Neural Network for Embedded Hardware via Multi-Dimensional Pruning.

Hao Kong, Di Liu, Xiangzhong Luo, Shuo Huai, Ravi Subramaniam, Christian Makaya, Qian Lin, Weichen Liu

Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

Crossbar-Aligned & Integer-Only Neural Network Compression for Efficient in-Memory Acceleration.

Shuo Huai, Di Liu, Xiangzhong Luo, Hui Chen, Weichen Liu, Ravi Subramaniam

Proceedings of the 28th Asia and South Pacific Design Automation Conference, 2023

2022

Bringing AI to edge: From deep learning's perspective.

Di Liu, Hao Kong, Xiangzhong Luo, Weichen Liu, Ravi Subramaniam

Neurocomputing, 2022

EDLAB: A Benchmark for Edge Deep Learning Accelerators.

Hao Kong, Shuo Huai, Di Liu, Lei Zhang, Hui Chen, Shien Zhu, Shiqing Li, Weichen Liu, Manu Rastogi, Ravi Subramaniam, Madhu Athreya, M. Anthony Lewis

IEEE Des. Test, 2022

Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems.

Shuo Huai, Di Liu, Hao Kong, Xiangzhong Luo, Weichen Liu, Ravi Subramaniam, Christian Makaya, Qian Lin

Proceedings of the IEEE 40th International Conference on Computer Design, 2022

Smart Scissor: Coupling Spatial Redundancy Reduction and CNN Compression for Embedded Hardware.

Hao Kong, Di Liu, Shuo Huai, Xiangzhong Luo, Weichen Liu, Ravi Subramaniam, Christian Makaya, Qian Lin

Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design, 2022

HACScale: Hardware-Aware Compound Scaling for Resource-Efficient DNNs.

Hao Kong, Di Liu, Xiangzhong Luo, Weichen Liu, Ravi Subramaniam

Proceedings of the 27th Asia and South Pacific Design Automation Conference, 2022

2021

ZeroBN: Learning Compact Neural Networks For Latency-Critical Edge Systems.

Shuo Huai, Lei Zhang, Di Liu, Weichen Liu, Ravi Subramaniam

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

2012

SIEPON conformance testing and certification.

Lowell D. Lamb, Yang Lu, Qian Liu, Ravi Subramaniam, Toshihiko Kusano, Masashi Tadokoro, Motoyuki Takizawa

IEEE Commun. Mag., 2012