Congratulations to Siyuan and Wenjie. We will present both near-memory (3D-based and LPDDR-based) and in-memory (SRAM-based) acceleration solutions with co-optimization considerations with algorithm, thermal, and testing.
Congratulations to Kangbo, Yiyang and Wentao. We will present three accelerator designs for Multimodal LLM, 3D Gaussian Splatting, and LLM inference with 3D stacked memory.
Congratulations to Zhantong (senior-year undergrad). We demonstrate CIM has great efficiency benefits for the generative model inference in TPU architecture.
Congratulations to Yanchi. A power modeling and analysis framework for LLM chiplets and a SoC thermal optimization solution (collaborated with Prof. Yibo Lin) will be presented.
Congratulations to Yiqi and Mingxuan (senior-year undergrad). A CIM-based chiplet design for Diffusion and sparsity-aware training accelerator are introduced.
A MHA ViT accelerator paper will also be presented (collaborated with Prof. Yufei Ma).
One paper introduces a flexible systolic CIM macro (collaborated with Prof. Le Ye), and the other paper shows a heterogeneous CIM-based processor (collaborated with Prof. Yufei Ma).
