Miaoxiang Yu

Orcid: 0000-0002-4382-9009

According to our database1, Miaoxiang Yu authored at least 12 papers between 2023 and 2026.

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

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2026
FPGA-Based Adjoint Method Accelerator for Rapid Optical Inverse Design.
IEEE Trans. Circuits Syst. I Regul. Pap., May, 2026

Mapping Gemma3 onto an Edge Dataflow Architecture.
CoRR, February, 2026

Exploring Real-Time Power Electronics Simulation on AMD AIEs.
Proceedings of the 2026 ACM/SIGDA International Symposium on Field Programmable Gate Arrays, 2026

An Efficient Dataflow Framework for DiT-Based Image Generation.
Proceedings of the 34th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines, 2026

Efficient LLM Decoding on Ryzen AI NPUs.
Proceedings of the Design, Automation & Test in Europe Conference, 2026

2025
Tile-Level Pipeline for Linear Scalable Stencil Computation on AMD AI Engines.
Proceedings of the 2025 ACM/SIGDA International Symposium on Field Programmable Gate Arrays, 2025

2024
An FPGA-Enabled Framework for Rapid Automated Design of Photonic Integrated Circuits.
Proceedings of the 2024 ACM/SIGDA International Symposium on Field Programmable Gate Arrays, 2024

TwinStep Network (TwNet): a Neuron-Centric Architecture Achieving Rapid Training.
Proceedings of the 35th IEEE International Conference on Application-specific Systems, 2024

2023
A Novel FPGA Simulator Accelerating Reinforcement Learning-Based Design of Power Converters.
Proceedings of the 2023 ACM/SIGDA International Symposium on Field Programmable Gate Arrays, 2023

A Finite-Difference Time-Domain (FDTD) solver with linearly scalable performance in an FPGA cluster.
Proceedings of the IEEE International Conference on Cluster Computing, 2023

A Heterogeneous Computer Architecture Accelerating Reinforcement Learning-based Design for Silicon Photonic Devices.
Proceedings of the 34th IEEE International Conference on Application-specific Systems, 2023

A Novel FPGA-Based Circuit Simulator for Accelerating Reinforcement Learning-Based Design of Power Converters.
Proceedings of the 34th IEEE International Conference on Application-specific Systems, 2023


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