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        • Orca: A distributed serving system for transformer-based generative models
        • Microsecond-scale preemption for concurrent GPU-accelerated DNN inferences
        • Looking beyond GPUs for DNN scheduling on multi-tenant clusters
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  • Meta Info
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  • Automated Parallelism for DNN Training
  • Scheduling for DNN Training
  • Model Serving
  • Sparse Models
  • DL Compiler
  • Collaborative ML

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  1. Reading Notes
  2. Conference

OSDI 2022

Meta Info

16th USENIX Symposium on Operating Systems Design and Implementation

Homepage: https://www.usenix.org/conference/osdi22

Paper list: https://www.usenix.org/conference/osdi22/technical-sessions

Papers

Automated Parallelism for DNN Training

  • Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep Learning [Code]

  • Unity: Accelerating DNN Training Through Joint Optimization of Algebraic Transformations and Parallelization [Code]

Scheduling for DNN Training

  • Looking Beyond GPUs for DNN Scheduling on Multi-Tenant Clusters [Code]

Model Serving

  • Orca: A Distributed Serving System for Transformer-Based Generative Models [Personal Notes]

  • Microsecond-scale Preemption for Concurrent GPU-accelerated DNN Inferences [Code, Benchmark, Artifact]

Sparse Models

  • SparTA: Deep-Learning Model Sparsity via Tensor-with-Sparsity-Attribute [Code]

DL Compiler

  • ROLLER: Fast and Efficient Tensor Compilation for Deep Learning [Code]

Collaborative ML

  • Walle: An End-to-End, General-Purpose, and Large-Scale Production System for Device-Cloud Collaborative Machine Learning [Code, 中文官网]

Last updated 1 year ago

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