Fixstars to Present Paper on GLM-5.1 Inference Acceleration at IEEE DTDA 2026

September 24, 2026 Events

A paper authored by a Fixstars employee has been accepted at the 2026 IEEE International Conference on Device Technologies for Diversified Applications (IEEE DTDA 2026), an international conference to be held from Sunday, October 11 to Wednesday, October 14, 2026. The paper will be presented orally on Wednesday, October 14, 2026.

IEEE DTDA is an international conference sponsored by the IEEE Electron Devices Society. Focusing on the diverse applications of device technologies, it brings together researchers, engineers, and industry professionals to share their latest advances.

The accepted paper shows that for inference with large Mixture-of-Experts (MoE) models, it is memory capacity, not compute performance, that bounds performance. It also presents our work reducing latency on the open-weight LLM GLM-5.1 by approximately 15x.

The findings of this paper are also covered in the following white paper:

Fixstars White Paper: Bringing the Large-Scale MoE Model GLM-5.1 to Practical Speeds on a Single NVIDIA H200 Node
https://www.fixstars.com/en/whitepaper/glm-5

Conference Overview

Name22026 IEEE International Conference on Device Technologies for Diversified Applications (IEEE DTDA 2026)
DatesSunday, October 11 – Wednesday, October 14, 2026
VenueSapporo Grand Hotel and Former Hokkaido Government Office Building “Red Brick Building,” Sapporo, Japan
SponsorIEEE Electron Devices Society
Official websitehttps://ieee-dtda.org/

Presentation Overview

Date & timeOctober 14, 2026, 13:20–13:35 (JST)
Paper NoAR-5-10
SessionApplication Session Area 5: Environmental Impact Mitigation, Energy Reduction and Water Risk Management (Session 2: AI x Sustainability)
TitleMemory Capacity, Not Compute, Bounds Large-MoE Serving: A 15x Latency Reduction on GLM-5.1
FormatOral presentation
PresenterYoshiki Kunimoto (Fixstars Corporation)

* The program is subject to change. Please check the official website for the latest information.


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