Dynamic GPU Energy Optimization for Machine Learning Training Workloads

Dynamic GPU Energy Optimization for Machine Learning Training Workloads

5 January 2022

Zheng Wang

Papers citing "Dynamic GPU Energy Optimization for Machine Learning Training Workloads"

10 / 10 papers shown

Title
Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach Xiongxiao Xu Solomon Abera Bekele Brice Videau Kai Shu 13 0 0 03 Oct 2024
DynamoLLM: Designing LLM Inference Clusters for Performance and Energy Efficiency Jovan Stojkovic Chaojie Zhang Íñigo Goiri Josep Torrellas Esha Choukse 35 29 0 01 Aug 2024
Resource Allocation and Workload Scheduling for Large-Scale Distributed Deep Learning: A Survey Feng Liang Zhen Zhang Haifeng Lu Chengming Li Victor C. M. Leung Yanyi Guo Xiping Hu 38 3 0 12 Jun 2024
Communication-Efficient Large-Scale Distributed Deep Learning: A Comprehensive Survey Feng Liang Zhen Zhang Haifeng Lu Victor C. M. Leung Yanyi Guo Xiping Hu GNN 29 6 0 09 Apr 2024
Tensor-Aware Energy Accounting Timur Babakol Yu David Liu 16 3 0 19 Nov 2023
PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices Minghao Yan Hongyi Wang Shivaram Venkataraman 10 0 0 30 Oct 2023
FusionAI: Decentralized Training and Deploying LLMs with Massive Consumer-Level GPUs Zhenheng Tang Yuxin Wang Xin He Longteng Zhang Xinglin Pan ... Rongfei Zeng Kaiyong Zhao S. Shi Bingsheng He Xiaowen Chu 33 30 0 03 Sep 2023
Zeus: Understanding and Optimizing GPU Energy Consumption of DNN Training Jie You Jaehoon Chung Mosharaf Chowdhury 16 75 0 12 Aug 2022
Deep Learning Workload Scheduling in GPU Datacenters: Taxonomy, Challenges and Vision Wei Gao Qi Hu Zhisheng Ye Peng Sun Xiaolin Wang Yingwei Luo Tianwei Zhang Yonggang Wen 78 26 0 24 May 2022
Benchmarking Graph Neural Networks Vijay Prakash Dwivedi Chaitanya K. Joshi Anh Tuan Luu T. Laurent Yoshua Bengio Xavier Bresson 189 914 0 02 Mar 2020