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CS336 Assignment 1 Key Takeaway

CS336 Assignment 1 Key Takeaway

Reading Notes: “DistServe: Disaggregating Prefill and Decoding for Goodput-optimized Large Language Model Serving”

Reading Notes: “DistServe: Disaggregating Prefill and Decoding for Goodput-optimized Large Language Model Serving”

Reading Notes: “Preble: Efficient Distributed Prompt Scheduling for LLM Serving”

Reading Notes: “Preble: Efficient Distributed Prompt Scheduling for LLM Serving”

Reading Note: “ORCA: A Distributed Serving System for Transformer-Based Generative Models”

Reading Note: “ORCA: A Distributed Serving System for Transformer-Based Generative Models”

Reading Notes: “FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness”

Reading Notes: “FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness”

Reading Notes: “Efficient Memory Management for Large Language Model Serving with PagedAttention”

Reading Notes: “Efficient Memory Management for Large Language Model Serving with PagedAttention”

Reading Notes: “Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep Learning”

Reading Notes: “Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep Learning”

Reading Notes: “GPipe: Easy Scaling with Micro-Batch Pipeline”

Reading Notes: “GPipe: Easy Scaling with Micro-Batch Pipeline”

Distributed Training Basics

Distributed Training Basics

Reading Note: Megatron-LM v1

Reading Note: Megatron-LM v1

Quantization for NN Inference

Quantization for NN Inference

Reading Note: TVM

Reading Note: TVM

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Lifan Sun

Software Dev Engineer

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