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Paper Notes

PPoPP'21 | A Fast Work-Efficient SSSP Algorithm for GPUs

TACO'22 | Performance and Power Prediction for Concurrent Execution on GPUs

OSDI'20 | AntMan: Dynamic Scaling on GPU Clusters for Deep Learning

OSDI'18 | Gandiva: Introspective Cluster Scheduling for Deep Learning

RTSS'17 | GPU Scheduling on the NVIDIA TX2: Hidden Details Revealed

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Blog

When LLMs Learn Memory, Reasoning, and Planning: The Three Core Capabilities of Language Agents

LLM Reasoning: Prompting, Multi-Path Search, and Iterative Self-Improvement

RLHF and Test-Time Compute: Reinforcement Learning and Inference-Time Optimization for LLMs

LLM Basics: Pretraining, Prompting, Fine-tuning and Reinforcement Learning

Computational and Communication Modeling of LLM Serving System

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