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MoNDE: Mixture of Near-Data Experts for Large-Scale Sparse Models

MoNDE: Mixture of Near-Data Experts for Large-Scale Sparse Models

29 May 2024
Taehyun Kim
Kwanseok Choi
Youngmock Cho
Jaehoon Cho
Hyukzae Lee
Jaewoong Sim
    MoE
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Papers citing "MoNDE: Mixture of Near-Data Experts for Large-Scale Sparse Models"

3 / 3 papers shown
Title
Large Language Model Inference Acceleration: A Comprehensive Hardware Perspective
Large Language Model Inference Acceleration: A Comprehensive Hardware Perspective
Jinhao Li
Jiaming Xu
Shan Huang
Yonghua Chen
Wen Li
...
Jiayi Pan
Li Ding
Hao Zhou
Yu Wang
Guohao Dai
62
16
0
06 Oct 2024
Towards MoE Deployment: Mitigating Inefficiencies in Mixture-of-Expert
  (MoE) Inference
Towards MoE Deployment: Mitigating Inefficiencies in Mixture-of-Expert (MoE) Inference
Haiyang Huang
Newsha Ardalani
Anna Y. Sun
Liu Ke
Hsien-Hsin S. Lee
Anjali Sridhar
Shruti Bhosale
Carole-Jean Wu
Benjamin C. Lee
MoE
70
23
0
10 Mar 2023
ZeRO-Offload: Democratizing Billion-Scale Model Training
ZeRO-Offload: Democratizing Billion-Scale Model Training
Jie Ren
Samyam Rajbhandari
Reza Yazdani Aminabadi
Olatunji Ruwase
Shuangyang Yang
Minjia Zhang
Dong Li
Yuxiong He
MoE
177
416
0
18 Jan 2021
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