Cover Image

AIReSim: A Discrete Event Simulator for Large-scale AI Cluster Reliability Modeling

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Pattabiraman, Karthik, Patel, Mihir, Lin, Fred
Format:	Preprint
Published:	2026
Subjects:	Distributed, Parallel, and Cluster Computing
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

DRackSim: Simulator for Rack-scale Memory Disaggregation
by: Puri, Amit, et al.
Published: (2023)

An Efficient, Reliable and Observable Collective Communication Library in Large-scale GPU Training Clusters
by: Zhang, Mingjun, et al.
Published: (2025)

PARSIR: a Package for Effective Parallel Discrete Event Simulation on Multi-processor Machines
by: Quaglia, Francesco
Published: (2024)

Bridging Simulation and Silicon: A Study of RISC-V Hardware and FireSim Simulation
by: Barai, Atanu, et al.
Published: (2025)

PALM: A Efficient Performance Simulator for Tiled Accelerators with Large-scale Model Training
by: Fang, Jiahao, et al.
Published: (2024)

MOSS: A Large-scale Open Microscopic Traffic Simulation System
by: Zhang, Jun, et al.
Published: (2024)

Mitigating Interference of Microservices with a Scoring Mechanism in Large-scale Clusters
by: Yang, Dingyu, et al.
Published: (2024)

Kavier: Exploring Performance, Sustainability, and Efficiency of LLM Ecosystems under Inference through Cache-Aware Discrete-Event Simulation
by: Nicolae, Radu, et al.
Published: (2026)

Fantasy: Efficient Large-scale Vector Search on GPU Clusters with GPUDirect Async
by: Liu, Yi, et al.
Published: (2025)

TokenSim: Enabling Hardware and Software Exploration for Large Language Model Inference Systems
by: Wu, Feiyang, et al.
Published: (2025)

SimDC: A High-Fidelity Device Simulation Platform for Device-Cloud Collaborative Computing
by: Pei, Ruiguang, et al.
Published: (2025)

C-Koordinator: Interference-aware Management for Large-scale and Co-located Microservice Clusters
by: Song, Shengye, et al.
Published: (2025)

UNIFERENCE: A Discrete Event Simulation Framework for Developing Distributed AI Models
by: Eldenk, Doğaç, et al.
Published: (2026)

Large-scale Neural Network Quantum States for ab initio Quantum Chemistry Simulations on Fugaku
by: Xu, Hongtao, et al.
Published: (2025)

Model Input Verification of Large Scale Simulations
by: Neykova, Rumyana, et al.
Published: (2024)

CrashEventLLM: Predicting System Crashes with Large Language Models
by: Mudgal, Priyanka, et al.
Published: (2024)

Falafels: A tool for Estimating Federated Learning Energy Consumption via Discrete Simulation
by: de Barochez, Andrew Mary Huet, et al.
Published: (2025)

Malleus: Straggler-Resilient Hybrid Parallel Training of Large-scale Models via Malleable Data and Model Parallelization
by: Li, Haoyang, et al.
Published: (2024)

Revisiting Reliability in Large-Scale Machine Learning Research Clusters
by: Kokolis, Apostolos, et al.
Published: (2024)

SuperBench: Improving Cloud AI Infrastructure Reliability with Proactive Validation
by: Xiong, Yifan, et al.
Published: (2024)

Beyond A Single AI Cluster: A Survey of Decentralized LLM Training
by: Dong, Haotian, et al.
Published: (2025)

Humas: A Heterogeneity- and Upgrade-aware Microservice Auto-scaling Framework in Large-scale Data Centers
by: Hua, Qin, et al.
Published: (2024)

Automated, Reliable, and Efficient Continental-Scale Replication of 7.3 Petabytes of Climate Simulation Data: A Case Study
by: Lacinski, Lukasz, et al.
Published: (2024)

Reliable Communication in Hybrid Authentication and Trust Models
by: Chotkan, Rowdy, et al.
Published: (2024)

Towards Efficient Verification of Parallel Applications with Mc SimGrid
by: Laurent, Matthieu, et al.
Published: (2025)

MoEntwine: Unleashing the Potential of Wafer-scale Chips for Large-scale Expert Parallel Inference
by: Tang, Xinru, et al.
Published: (2025)

ScaleSim: Serving Large-Scale Multi-Agent Simulation with Invocation Distance-Based Memory Management
by: Pan, Zaifeng, et al.
Published: (2026)

Pro-Prophet: A Systematic Load Balancing Method for Efficient Parallel Training of Large-scale MoE Models
by: Wang, Wei, et al.
Published: (2024)

Towards Cloud Efficiency with Large-scale Workload Characterization
by: Parayil, Anjaly, et al.
Published: (2024)

Strongly-Consistent Distributed Discrete-event Systems
by: Donovan, Peter, et al.
Published: (2024)

SplitSim: Large-Scale Simulations for Evaluating Network Systems Research
by: Li, Hejing, et al.
Published: (2024)

Blockchain and Edge Computing Nexus: A Large-scale Systematic Literature Review
by: Nezami, Zeinab, et al.
Published: (2025)

BandPilot: Towards Performance- and Contention-Aware GPU Dispatching in AI Clusters
by: Zhang, Kunming, et al.
Published: (2025)

SWIFT: Expedited Failure Recovery for Large-scale DNN Training
by: Zhong, Yuchen, et al.
Published: (2023)

GPU-Accelerated Distributed QAOA on Large-scale HPC Ecosystems
by: Xu, Zhihao, et al.
Published: (2025)

Estimating CO$_2$ emissions of distributed applications and platforms with SimGrid/Batsim
by: Saraiva, Gabriella, et al.
Published: (2025)

CloudNativeSim: a toolkit for modeling and simulation of cloud-native applications
by: Wu, Jingfeng, et al.
Published: (2024)

Efficient Coordination for Distributed Discrete-Event Systems
by: Jun, Byeonggil, et al.
Published: (2024)

Cultivating Multidisciplinary AI Workforce Development on iTiger GPU Cluster: Practices and Challenges
by: Sharif, Mayira, et al.
Published: (2025)

PRISM: Dynamic Primitive-Based Forecasting for Large-Scale GPU Cluster Workloads
by: Wu, Xin, et al.
Published: (2026)