Glenn G. Ko

发表

FlexGibbs: Reconfigurable Parallel Gibbs Sampling Accelerator for Structured Graphs

Rob A. Rutenbar, Gu-Yeon Wei, David Brooks, 2019, 2019 IEEE 27th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM).

Stereophonic spectrogram segmentation using Markov random fields

Rob A. Rutenbar, Paris Smaragdis, Minje Kim, 2012, 2012 IEEE International Workshop on Machine Learning for Signal Processing.

CHIPKIT: An Agile, Reusable Open-Source Framework for Rapid Test Chip Development

Gu-Yeon Wei, Paul N. Whatmough, Glenn G. Ko, 2020, IEEE Micro.

Demystifying Bayesian Inference Workloads

David Brooks, Gu-Yeon Wei, Yuhao Zhu, 2019, 2019 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS).

Sampling architectures for probabilistic inference

Glenn G. Ko, 2017 .

A case study of machine learning hardware: Real-time source separation using Markov Random Fields via sampling-based inference

Rob A. Rutenbar, Glenn G. Ko, 2017, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

A 16nm 25mm2 SoC with a 54.5x Flexibility-Efficiency Range from Dual-Core Arm Cortex-A53 to eFPGA and Cache-Coherent Accelerators

Gu-Yeon Wei, Sae Kyu Lee, Paul N. Whatmough, 2019, 2019 Symposium on VLSI Circuits.

Accelerating Bayesian Inference on Structured Graphs Using Parallel Gibbs Sampling

Rob A. Rutenbar, Gu-Yeon Wei, Glenn G. Ko, 2019, 2019 29th International Conference on Field Programmable Logic and Applications (FPL).

Real-Time and Low-Power Streaming Source Separation Using Markov Random Field

Rob A. Rutenbar, Glenn G. Ko, 2018, ACM J. Emerg. Technol. Comput. Syst..

A 3mm2 Programmable Bayesian Inference Accelerator for Unsupervised Machine Perception using Parallel Gibbs Sampling in 16nm

Rob A. Rutenbar, Paul N. Whatmough, Glenn G. Ko, 2020, 2020 IEEE Symposium on VLSI Circuits.

EMERALD: Characterization of emerging applications and algorithms for low-power devices

Rob A. Rutenbar, Narayanan Vijaykrishnan, Mei Chen, 2013, 2013 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS).

9.8 A 25mm2 SoC for IoT Devices with 18ms Noise-Robust Speech-to-Text Latency via Bayesian Speech Denoising and Attention-Based Sequence-to-Sequence DNN Speech Recognition in 16nm FinFET

Alexander M. Rush, Gu-Yeon Wei, David Brooks, 2021, 2021 IEEE International Solid- State Circuits Conference (ISSCC).

Bigger&Faster: Two-stage Neural Architecture Search for Quantized Transformer Models

Glenn G. Ko, Yunho Jin, Yuji Chai, 2022, ArXiv.

A 16-nm SoC for Noise-Robust Speech and NLP Edge AI Inference With Bayesian Sound Source Separation and Attention-Based DNNs

Alexander M. Rush, Glenn G. Ko, Gu-Yeon Wei, 2023, IEEE Journal of Solid-State Circuits.

INT2.1: Towards Fine-Tunable Quantized Large Language Models with Error Correction through Low-Rank Adaptation

Glenn G. Ko, D. Brooks, Gu-Yeon Wei, 2023, ArXiv.

SpeedLimit: Neural Architecture Search for Quantized Transformer Models

Glenn G. Ko, D. Brooks, Gu-Yeon Wei, 2022, 2209.12127.

SMIV: A 16-nm 25-mm² SoC for IoT With Arm Cortex-A53, eFPGA, and Coherent Accelerators

Glenn G. Ko, Sae Kyu Lee, Gu-Yeon Wei, 2022, IEEE Journal of Solid-State Circuits.

SpeedLimit: Neural Architecture Search for Quantized Transformer Models

Glenn G. Ko, D. Brooks, Gu-Yeon Wei, 2022, 2209.12127.