NSDI 2025

Meta Info

Homepage: https://www.usenix.org/conference/nsdi25

Paper list: https://www.usenix.org/conference/nsdi25/technical-sessions

Acceptance Rate

• Fall: 13.7% (= 55 / 401)

Papers

Large Language Models (LLMs)

• LLM Training

  • Minder: Faulty Machine Detection for Large-scale Distributed Model Training [Paper]

    • THU & ByteDance & NEU & Harvard

    • Automatically and efficiently detect faulty distinctive monitoring metric patterns.

  • Holmes: Localizing Irregularities in LLM Training with Mega-scale GPU Clusters [Paper]

    • FDU & Tencent & UChicago

  • Evolution of Aegis: Fault Diagnosis for AI Model Training Cloud Service in Production [Paper]

    • Alibaba Cloud

  • Accelerating Design Space Exploration for LLM Training Systems with Multi-experiment Parallel Simulation [Paper]

    • THU & Zhongguancun Lab & UPenn

  • SimAI: Unifying Architecture Design and Performance Tunning for Large-Scale Large Language Model Training with Scalability and Precision [Paper]

    • Alibaba Cloud

• Reinforcement Learning with Human Feedback (RLHF)

  • Optimizing RLHF Training for Large Language Models with Stage Fusion [Paper] [arXiv]

    • PKU & StepFun

• Checkpointing

  • BCP: A Unified Checkpointing System for Large Foundation Model Development [Paper]

    • HKU & ByteDance

Deep Learning Recommendation Models (DLRMs)

• GPU-Disaggregated Serving for Deep Learning Recommendation Models at Scale [Paper]

  • HKUST & Alibaba

Model Serving

• SuperServe: Fine-Grained Inference Serving for Unpredictable Workloads [Paper]

  • GaTech & UC Berkeley & Adobe

Collective Communication

• AutoCCL: Automated Collective Communication Tuning for Accelerating Distributed and Parallel DNN Training [Paper]

  • USTC & Microsoft

• OptiReduce: Resilient and Tail-Optimal AllReduce for Distributed Deep Learning in the Cloud [Paper]

  • Purdue & NVIDIA & VMware Research & Feldera

• Efficient Direct-Connect Topologies for Collective Communications [Paper]

  • UW & Raytheon BBN Technologies & MIT

Networking

• Remote Direct Memory Access (RDMA)

  • White-Boxing RDMA with Packet-Granular Software Control [Paper]

    • UW & UW-Madison

  • Mitigating Scalability Walls of RDMA-based Container Networks [Paper]

    • Alibaba Cloud

• Application Networks

  • High-level Programming for Application Networks [Paper]

    • UW & Duke

• Container Overlay Network

  • ONCache: A Cache-Based Low-Overhead Container Overlay Network [Paper]

    • SJTU & Broadcom

• Placement

  • Preventing Network Bottlenecks: Accelerating Datacenter Services with Hotspot-Aware Placement for Compute and Storage [Paper]

    • Google & USC & Harvard & UCLA & Columbia

• Network Mitigation

  • Enhancing Network Failure Mitigation with Performance-Aware Ranking [Paper]

    • USC & Microsoft

Resource Management

• Granular Management

  • Quicksand: Harnessing Stranded Datacenter Resources with Granular Computing [Paper]

    • MIT & Brown & USC & VMware Research

      • Provide developers with familiar, high-level abstractions (e.g., data structures, batch computing); decompose them into resource proclets, granular units that each primarily consume resources of one type; split, merge, and migrate resource proclets in milliseconds.

  • GRANNY: Granular Management of Compute-Intensive Applications in the Cloud [Paper]

    • ICL

• Resource Scheduling

  • GREEN: Carbon-efficient Resource Scheduling for Machine Learning Clusters [Paper]

    • HKUST

• Serverless Computing

  • Making Serverless Pay-For-Use a Reality with Leopard [Paper]

    • UW-Madison

• Userspace Scheduling

  • The Benefits and Limitations of User Interrupts for Preemptive Userspace Scheduling [Paper]

    • UCSD

Fault Tolerance

• One-Size-Fits-None: Understanding and Enhancing Slow Fault Tolerance in Modern Distributed Systems [Paper]

  • UMich & SJTU

Memory Disaggregation

• Beehive: A Scalable Disaggregated Memory Runtime Exploiting Asynchrony of Multithreaded Programs [Paper]

  • UCAS & PKU & Huawei Cloud & SJTU

• Eden: Developer-Friendly Application-Integrated Far Memory [Paper]

  • UCSD & Technion & VMware Research

Real-Time Video Streaming

• Mowgli: A Passive Approach to Learning Real-Time Rate Control for Video Conferencing [Paper]

  • Princeton