Meng Wu

Orcid: 0000-0002-7676-343X

Affiliations:
  • Peking University, School of Integrated Circuits, Institute of Microelectronics, Beijing, China


According to our database1, Meng Wu authored at least 15 papers between 2021 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
DCIM-GCN: Digital Computing-in-Memory Accelerator for Graph Convolutional Network.
IEEE Trans. Circuits Syst. I Regul. Pap., June, 2024

A Heterogeneous TinyML SoC with Energy-Event-Performance-Aware Management and Compute-in-Memory Two-Stage Event-Driven Wakeup.
Proceedings of the IEEE Symposium on VLSI Technology and Circuits 2024, 2024

30.2 A 22nm 0.26nW/Synapse Spike-Driven Spiking Neural Network Processing Unit Using Time-Step-First Dataflow and Sparsity-Adaptive In-Memory Computing.
Proceedings of the IEEE International Solid-State Circuits Conference, 2024

AIG-CIM: A Scalable Chiplet Module with Tri-Gear Heterogeneous Compute-in-Memory for Diffusion Acceleration.
Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024

An In-Memory Computing Accelerator with Reconfigurable Dataflow for Multi-Scale Vision Transformer with Hybrid Topology.
Proceedings of the 61st ACM/IEEE Design Automation Conference, 2024

S2D-CIM: A 22nm 128Kb Systolic Digital Compute-in-Memory Macro with Domino Data Path for Flexible Vector Operation and 2-D Weight Update in Edge AI Applications.
Proceedings of the IEEE Custom Integrated Circuits Conference, 2024

Quartet: A 22nm 0.09mJ/lnference Digital Compute-in-Memory Versatile AI Accelerator with Heterogeneous Tensor Engines and Off-Chip-Less Dataflow.
Proceedings of the IEEE Custom Integrated Circuits Conference, 2024

2023
Research progress on low-power artificial intelligence of things (AIoT) chip design.
Sci. China Inf. Sci., October, 2023

A 22nm Delta-Sigma Computing-In-Memory (Δ∑CIM) SRAM Macro with Near-Zero-Mean Outputs and LSB-First ADCs Achieving 21.38TOPS/W for 8b-MAC Edge AI Processing.
Proceedings of the IEEE International Solid- State Circuits Conference, 2023

DCIM-3DRec: A 3D Reconstruction Accelerator with Digital Computing-in-Memory and Octree-Based Scheduler.
Proceedings of the IEEE/ACM International Symposium on Low Power Electronics and Design, 2023

RIMAC: An Array-Level ADC/DAC-Free ReRAM-Based in-Memory DNN Processor with Analog Cache and Computation.
Proceedings of the 28th Asia and South Pacific Design Automation Conference, 2023

2022
An 82nW 0.53pJ/SOP Clock-Free Spiking Neural Network with 40µs Latency for AloT Wake-Up Functions Using Ultimate-Event-Driven Bionic Architecture and Computing-in-Memory Technique.
Proceedings of the IEEE International Solid-State Circuits Conference, 2022

Reliability-Improved Read Circuit and Self-Terminating Write Circuit for STT-MRAM in 16 nm FinFET.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2022

DCIM-GCN: Digital Computing-in-Memory to Efficiently Accelerate Graph Convolutional Networks.
Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design, 2022

2021
The Challenges and Emerging Technologies for Low-Power Artificial Intelligence IoT Systems.
IEEE Trans. Circuits Syst. I Regul. Pap., 2021


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