Chao Wu

Orcid: 0000-0002-7829-1413

Affiliations:

Northeastern University, Department of Electrical and Computer Engineering, Boston, MA, USA
City University of Hong Kong, Department of Computer Science, Hong Kong (PhD 2020)

According to our database¹, Chao Wu authored at least 28 papers between 2016 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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Bibliography

2024

Automated Optical Accelerator Search Toward Superior Acceleration Efficiency, Inference Robustness, and Development Speed.

[BibT_eX]

[DOI]

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., January, 2024

Search for Efficient Large Language Models.

[BibT_eX]

[DOI]

CoRR, 2024

AyE-Edge: Automated Deployment Space Search Empowering Accuracy yet Efficient Real-Time Object Detection on the Edge.

[BibT_eX]

[DOI]

CoRR, 2024

Efficient Pruning of Large Language Model with Adaptive Estimation Fusion.

[BibT_eX]

[DOI]

CoRR, 2024

EdgeOL: Efficient in-situ Online Learning on Edge Devices.

[BibT_eX]

[DOI]

CoRR, 2024

Waxing-and-Waning: a Generic Similarity-based Framework for Efficient Self-Supervised Learning.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

SuperFlow: A Fully-Customized RTL-to-GDS Design Automation Flow for Adiabatic Quantum- Flux - Parametron Superconducting Circuits.

[BibT_eX]

[DOI]

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2024

LOTUS: learning-based online thermal and latency variation management for two-stage detectors on edge devices.

[BibT_eX]

[DOI]

Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024

2023

Predicting for I/O stack optimizations on cyber-physical systems.

[BibT_eX]

[DOI]

Microprocess. Microsystems, 2023

PackQViT: Faster Sub-8-bit Vision Transformers via Full and Packed Quantization on the Mobile.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

MOC: Multi-Objective Mobile CPU-GPU Co-Optimization for Power-Efficient DNN Inference.

[BibT_eX]

[DOI]

Proceedings of the IEEE/ACM International Conference on Computer Aided Design, 2023

RLAlloc: A Deep Reinforcement Learning-Assisted Resource Allocation Framework for Enhanced Both I/O Throughput and QoS Performance of Multi-Streamed SSDs.

[BibT_eX]

[DOI]

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

Condense: A Framework for Device and Frequency Adaptive Neural Network Models on the Edge.

[BibT_eX]

[DOI]

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

A Scalable Real-time Semantic Segmentation Network for Autonomous Driving.

[BibT_eX]

[DOI]

Proceedings of the 2023 Workshop on Advanced Multimedia Computing for Smart Manufacturing and Engineering, 2023

2022

DeltaFS: Pursuing Zero Update Overhead via Metadata-Enabled Delta Compression for Log-structured File System on Mobile Devices.

[BibT_eX]

[DOI]

CoRR, 2022

All-in-One: A Highly Representative DNN Pruning Framework for Edge Devices with Dynamic Power Management.

[BibT_eX]

[DOI]

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

2021

Pattern-Guided File Compression with User-Experience Enhancement for Log-Structured File System on Mobile Devices.

[BibT_eX]

[DOI]

Proceedings of the 19th USENIX Conference on File and Storage Technologies, 2021

2020

Boosting User Experience via Foreground-Aware Cache Management in UFS Mobile Devices.

[BibT_eX]

[DOI]

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2020

Pruning Deep Reinforcement Learning for Dual User Experience and Storage Lifetime Improvement on Mobile Devices.

[BibT_eX]

[DOI]

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2020

Maximizing I/O Throughput and Minimizing Performance Variation via Reinforcement Learning Based I/O Merging for SSDs.

[BibT_eX]

[DOI]

IEEE Trans. Computers, 2020

Machine learning assisted OSP approach for improved QoS performance on 3D charge-trap based SSDs.

[BibT_eX]

[DOI]

Int. J. Intell. Syst., 2020

2019

Reinforcement Learning based Background Segment Cleaning for Log-structured File System on Mobile Devices.

[BibT_eX]

[DOI]

Chao Wu

Cheng Ji

Chun Jason Xue

Proceedings of the 15th IEEE International Conference on Embedded Software and Systems, 2019

2018

An I/O Scheduling Strategy for Embedded Flash Storage Devices With Mapping Cache.

[BibT_eX]

[DOI]

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2018

Maximizing I/O throughput and minimizing performance variation via reinforcement learning based I/O merging for SSDs: work-in-progress.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Compilers, 2018

2017

Lightweight Data Compression for Mobile Flash Storage.

[BibT_eX]

[DOI]

ACM Trans. Embed. Comput. Syst., 2017

2016

Dynamic merging/splitting for better responsiveness in mobile devices.

[BibT_eX]

[DOI]

Proceedings of the 5th Non-Volatile Memory Systems and Applications Symposium, 2016

An Empirical Study of File-System Fragmentation in Mobile Storage Systems.

[BibT_eX]

[DOI]

Proceedings of the 8th USENIX Workshop on Hot Topics in Storage and File Systems, 2016

I/O scheduling with mapping cache awareness for flash based storage systems.

[BibT_eX]

[DOI]

Proceedings of the 2016 International Conference on Embedded Software, 2016

Chao Wu

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