Ravi Subramaniam

17 papers A* 2A 2C 1Journal 9Unranked 3
YearRankTypeTitle / Venue / Authors
2024 J jnl
EvoLP: Self-Evolving Latency Predictor for Model Compression in Real-Time Edge Systems.
IEEE Embed. Syst. Lett.
Shuo Huai, Hao Kong, Shiqing Li, Xiangzhong Luo, Ravi Subramaniam, Christian Makaya, Qian Lin, Weichen Liu
2024 — conf
FedTR: Federated Learning Framework with Transfer Learning for Industrial Visual Inspection.
ACM Great Lakes Symposium on VLSI
Vikash Sathiamoorthy, Shuo Huai, Hao Kong, Di Liu, Wendy Yong Yi Loy, Christian Makaya, Daren Ho, Ravi Subramaniam, Qian Lin, Weichen Liu
2023 J jnl
CRIMP: Compact & Reliable DNN Inference on In-Memory Processing via Crossbar-Aligned Compression and Non-ideality Adaptation.
ACM Trans. Embed. Comput. Syst.
Shuo Huai, Hao Kong, Xiangzhong Luo, Shiqing Li, Ravi Subramaniam, Christian Makaya, Qian Lin, Weichen Liu
2023 — conf
Crossbar-Aligned & Integer-Only Neural Network Compression for Efficient in-Memory Acceleration.
ASP-DAC
Shuo Huai, Di Liu, Xiangzhong Luo, Hui Chen, Weichen Liu, Ravi Subramaniam
2023 A conf
EMNAPE: Efficient Multi-Dimensional Neural Architecture Pruning for EdgeAI.
DATE
Hao Kong, Xiangzhong Luo, Shuo Huai, Di Liu, Ravi Subramaniam, Christian Makaya, Qian Lin, Weichen Liu
2023 J jnl
EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.
Hao Kong, Di Liu, Shuo Huai, Xiangzhong Luo, Ravi Subramaniam, Christian Makaya, Qian Lin, Weichen Liu
2023 J jnl
Latency-constrained DNN architecture learning for edge systems using zerorized batch normalization.
Future Gener. Comput. Syst.
Shuo Huai, Di Liu, Hao Kong, Weichen Liu, Ravi Subramaniam, Christian Makaya, Qian Lin
2023 J jnl
On Hardware-Aware Design and Optimization of Edge Intelligence.
IEEE Des. Test
Shuo Huai, Hao Kong, Xiangzhong Luo, Di Liu, Ravi Subramaniam, Christian Makaya, Qian Lin, Weichen Liu
2023 A* conf
Towards Efficient Convolutional Neural Network for Embedded Hardware via Multi-Dimensional Pruning.
DAC
Hao Kong, Di Liu, Xiangzhong Luo, Shuo Huai, Ravi Subramaniam, Christian Makaya, Qian Lin, Weichen Liu
2022 J jnl
Bringing AI to edge: From deep learning's perspective.
Neurocomputing
Di Liu, Hao Kong, Xiangzhong Luo, Weichen Liu, Ravi Subramaniam
2022 C conf
Collate: Collaborative Neural Network Learning for Latency-Critical Edge Systems.
ICCD
Shuo Huai, Di Liu, Hao Kong, Xiangzhong Luo, Weichen Liu, Ravi Subramaniam, Christian Makaya, Qian Lin
2022 J jnl
EDLAB: A Benchmark for Edge Deep Learning Accelerators.
IEEE Des. Test
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
2022 — conf
HACScale: Hardware-Aware Compound Scaling for Resource-Efficient DNNs.
ASP-DAC
Hao Kong, Di Liu, Xiangzhong Luo, Weichen Liu, Ravi Subramaniam
2022 A conf
Smart Scissor: Coupling Spatial Redundancy Reduction and CNN Compression for Embedded Hardware.
ICCAD
Hao Kong, Di Liu, Shuo Huai, Xiangzhong Luo, Weichen Liu, Ravi Subramaniam, Christian Makaya, Qian Lin
2021 A* conf
ZeroBN: Learning Compact Neural Networks For Latency-Critical Edge Systems.
DAC
Shuo Huai, Lei Zhang, Di Liu, Weichen Liu, Ravi Subramaniam
2020 J jnl
Bringing AI To Edge: From Deep Learning's Perspective.
CoRR
Di Liu, Hao Kong, Xiangzhong Luo, Weichen Liu, Ravi Subramaniam
2012 J jnl
SIEPON conformance testing and certification.
IEEE Commun. Mag.
Lowell D. Lamb, Yang Lu, Qian Liu, Ravi Subramaniam, Toshihiko Kusano, Masashi Tadokoro, Motoyuki Takizawa