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        • PilotFish: Harvesting Free Cycles of Cloud Gaming with Deep Learning Training
        • Memory Harvesting in Multi-GPU Systems with Hierarchical Unified Virtual Memory
        • Whale: Efficient Giant Model Training over Heterogeneous GPUs
        • DVABatch: Diversity-aware Multi-Entry Multi-Exit Batching for Efficient Processing of DNN Service...
        • Serving Heterogeneous Machine Learning Models on Multi-GPU Servers with Spatio-Temporal Sharing
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For the complete documentation index, see llms.txt. This page is also available as Markdown.
  1. Reading Notes
  2. Conference

ATC 2022

Meta Info

2022 USENIX Annual Technical Conference

Homepage: https://www.usenix.org/conference/atc22

Paper list: https://www.usenix.org/conference/atc22/technical-sessions

Papers

DNN Inference

  • DVABatch: Diversity-aware Multi-Entry Multi-Exit Batching for Efficient Processing of DNN Services on GPUs [Personal Note, Code]

  • Serving Heterogeneous Machine Learning Models on Multi-GPU Servers with Spatio-Temporal Sharing [Personal Note, Code]

  • SOTER: Guarding Black-box Inference for General Neural Networks at the Edge [Personal Note, Code]

DNN Training

  • Whale: Efficient Giant Model Training over Heterogeneous GPUs [Personal Note, Code]

Resource Manager

  • PilotFish: Harvesting Free Cycles of Cloud Gaming with Deep Learning Training [Personal Note]

  • Memory Harvesting in Multi-GPU Systems with Hierarchical Unified Virtual Memory [Personal Note]

Last updated 2 years ago

  • Meta Info
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  • DNN Inference
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