Media Summary: OptiReduce: Resilient and Tail-Optimal AllReduce for Distributed Deep Learning in the Cloud Ertza Warraich, Purdue University; ... Region-based Content Enhancement for Efficient Video Analytics at the Edge Weijun Wang, Institute for AI Industry Research ... SuperServe: Fine-Grained Inference Serving for Unpredictable Workloads Alind Khare and Dhruv Garg, Georgia Institute of ...

Nsdi 25 Cato End To - Detailed Analysis & Overview

OptiReduce: Resilient and Tail-Optimal AllReduce for Distributed Deep Learning in the Cloud Ertza Warraich, Purdue University; ... Region-based Content Enhancement for Efficient Video Analytics at the Edge Weijun Wang, Institute for AI Industry Research ... SuperServe: Fine-Grained Inference Serving for Unpredictable Workloads Alind Khare and Dhruv Garg, Georgia Institute of ... Finding Network Misconfigurations by Automatic Template Inference Siva Kesava Reddy Kakarla and Alan Tang, UCLA; Ryan ... This presentation was recorded at GOTO Copenhagen 2025. Daniel Terhorst-North ... Yiran Lei, Carnegie Mellon University and MangoBoost; Dongjoo Lee, MangoBoost; Liangyu Zhao, University of Washington; ...

This talk was recorded at NDC Oslo in Oslo, Norway. Attend the next ...

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NSDI '25 - CATO: End-to-End Optimization of ML-Based Traffic Analysis Pipelines
NSDI '25 - OptiReduce: Resilient and Tail-Optimal AllReduce for Distributed Deep Learning in the...
NSDI '25 - Region-based Content Enhancement for Efficient Video Analytics at the Edge
OSDI '25 - Low End-to-End Latency atop a Speculative Shared Log with Fix-Ante Ordering
NSDI '25 - SuperServe: Fine-Grained Inference Serving for Unpredictable Workloads
NSDI '24 - Towards provably performant congestion control
NSDI '20 - Finding Network Misconfigurations by Automatic Template Inference
Best Simple System for Now • Daniel Terhorst-North • GOTO 2025
NSDI '26 - FAST: An Efficient Scheduler for All-to-All GPU Communication
The fundamental misunderstanding in Team Topologies - Patricia Aas - NDC Oslo 2025
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NSDI '25 - CATO: End-to-End Optimization of ML-Based Traffic Analysis Pipelines

NSDI '25 - CATO: End-to-End Optimization of ML-Based Traffic Analysis Pipelines

CATO

NSDI '25 - OptiReduce: Resilient and Tail-Optimal AllReduce for Distributed Deep Learning in the...

NSDI '25 - OptiReduce: Resilient and Tail-Optimal AllReduce for Distributed Deep Learning in the...

OptiReduce: Resilient and Tail-Optimal AllReduce for Distributed Deep Learning in the Cloud Ertza Warraich, Purdue University; ...

NSDI '25 - Region-based Content Enhancement for Efficient Video Analytics at the Edge

NSDI '25 - Region-based Content Enhancement for Efficient Video Analytics at the Edge

Region-based Content Enhancement for Efficient Video Analytics at the Edge Weijun Wang, Institute for AI Industry Research ...

OSDI '25 - Low End-to-End Latency atop a Speculative Shared Log with Fix-Ante Ordering

OSDI '25 - Low End-to-End Latency atop a Speculative Shared Log with Fix-Ante Ordering

Low

NSDI '25 - SuperServe: Fine-Grained Inference Serving for Unpredictable Workloads

NSDI '25 - SuperServe: Fine-Grained Inference Serving for Unpredictable Workloads

SuperServe: Fine-Grained Inference Serving for Unpredictable Workloads Alind Khare and Dhruv Garg, Georgia Institute of ...

NSDI '24 - Towards provably performant congestion control

NSDI '24 - Towards provably performant congestion control

NSDI

NSDI '20 - Finding Network Misconfigurations by Automatic Template Inference

NSDI '20 - Finding Network Misconfigurations by Automatic Template Inference

Finding Network Misconfigurations by Automatic Template Inference Siva Kesava Reddy Kakarla and Alan Tang, UCLA; Ryan ...

Best Simple System for Now • Daniel Terhorst-North • GOTO 2025

Best Simple System for Now • Daniel Terhorst-North • GOTO 2025

This presentation was recorded at GOTO Copenhagen 2025. #GOTOcon #GOTOcph https://gotocph.com Daniel Terhorst-North ...

NSDI '26 - FAST: An Efficient Scheduler for All-to-All GPU Communication

NSDI '26 - FAST: An Efficient Scheduler for All-to-All GPU Communication

Yiran Lei, Carnegie Mellon University and MangoBoost; Dongjoo Lee, MangoBoost; Liangyu Zhao, University of Washington; ...

The fundamental misunderstanding in Team Topologies - Patricia Aas - NDC Oslo 2025

The fundamental misunderstanding in Team Topologies - Patricia Aas - NDC Oslo 2025

This talk was recorded at NDC Oslo in Oslo, Norway. #ndcoslo #ndcconferences #developer #softwaredeveloper Attend the next ...