Cover Image

A Deep Dive into the Google Cluster Workload Traces: Analyzing the Application Failure Characteristics and User Behaviors

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Bappy, Faisal Haque, Islam, Tariqul, Zaman, Tarannum Shaila, Hasan, Raiful, Caicedo, Carlos
Format:	Preprint
Published:	2023
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

FASTEN: Towards a FAult-tolerant and STorage EfficieNt Cloud: Balancing Between Replication and Deduplication
by: Ahmed, Sabbir, et al.
Published: (2023)

SEAM: A Secure Automated and Maintainable Smart Contract Upgrade Framework
by: Hossain, Tahrim, et al.
Published: (2024)

ConChain: A Scheme for Contention-free and Attack Resilient BlockChain
by: Bappy, Faisal Haque, et al.
Published: (2023)

Maximizing Blockchain Performance: Mitigating Conflicting Transactions through Parallelism and Dependency Management
by: Bappy, Faisal Haque, et al.
Published: (2024)

MRL-PoS: A Multi-agent Reinforcement Learning based Proof of Stake Consensus Algorithm for Blockchain
by: Islam, Tariqul, et al.
Published: (2023)

SWORD: A Secure LoW-Latency Offline-First Authentication and Data Sharing Scheme for Resource Constrained Distributed Networks
by: Bappy, Faisal Haque, et al.
Published: (2026)

Impact of Conflicting Transactions in Blockchain: Detecting and Mitigating Potential Attacks
by: Bappy, Faisal Haque, et al.
Published: (2024)

Securing Proof of Stake Blockchains: Leveraging Multi-Agent Reinforcement Learning for Detecting and Mitigating Malicious Nodes
by: Bappy, Faisal Haque, et al.
Published: (2024)

Collaborative Proof-of-Work: A Secure Dynamic Approach to Fair and Efficient Blockchain Mining
by: Haque, Rizwanul, et al.
Published: (2024)

Agentic AI Workload Characteristics
by: Yuan, Yichao, et al.
Published: (2026)

Minos: Systematically Classifying Performance and Power Characteristics of GPU Workloads on HPC Clusters
by: Jain, Rutwik, et al.
Published: (2026)

SmartShift: A Secure and Efficient Approach to Smart Contract Migration
by: Hossain, Tahrim, et al.
Published: (2025)

Profiling and Modeling of Power Characteristics of Leadership-Scale HPC System Workloads
by: Karimi, Ahmad Maroof, et al.
Published: (2024)

Resource Optimization with MPI Process Malleability for Dynamic Workloads in HPC Clusters
by: Iserte, Sergio, et al.
Published: (2025)

Dispatching Odyssey: Exploring Performance in Computing Clusters under Real-world Workloads
by: Yildiz, Mert, et al.
Published: (2025)

Evaluating Malleable Job Scheduling in HPC Clusters using Real-World Workloads
by: Zojer, Patrick, et al.
Published: (2026)

PAL: A Variability-Aware Policy for Scheduling ML Workloads in GPU Clusters
by: Jain, Rutwik, et al.
Published: (2024)

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

Dynamic Client Clustering, Bandwidth Allocation, and Workload Optimization for Semi-synchronous Federated Learning
by: Yu, Liangkun, et al.
Published: (2024)

Performance Characterization of Distributed Deep Learning Strategies: A Quantitative Evaluation of DDP, FSDP, and Parameter Server Architectures on GPU Clusters
by: Ovi, Md Sultanul Islam
Published: (2025)

Tally: Non-Intrusive Performance Isolation for Concurrent Deep Learning Workloads
by: Zhao, Wei, et al.
Published: (2024)

Prediction-Assisted Online Distributed Deep Learning Workload Scheduling in GPU Clusters
by: Luo, Ziyue, et al.
Published: (2025)

Sustainable Graph Analytics Workload Scheduling with Evolutionary Reinforcement Learning in Edge-Cloud Systems
by: Ramicetty, P., et al.
Published: (2026)

QONNECT: A QoS-Aware Orchestration System for Distributed Kubernetes Clusters
by: Aslan, Haci Ismail, et al.
Published: (2025)

CRIUgpu: Transparent Checkpointing of GPU-Accelerated Workloads
by: Stoyanov, Radostin, et al.
Published: (2025)

AI Surrogate Model for Distributed Computing Workloads
by: Park, David K., et al.
Published: (2024)

Accelerating Compound LLM Training Workloads with Maestro
by: Yuan, Xiulong, et al.
Published: (2026)

Optimal Workload Placement on Multi-Instance GPUs
by: Turkkan, Bekir, et al.
Published: (2024)

Union: An Automatic Workload Manager for Accelerating Network Simulation
by: Wang, Xin, et al.
Published: (2024)

Crossword: Adaptive Consensus for Dynamic Data-Heavy Workloads
by: Hu, Guanzhou, et al.
Published: (2025)

Distributed Load Balancing with Workload-Dependent Service Rates
by: Zhang, Wenxin, et al.
Published: (2024)

Eventually-Consistent Federated Scheduling for Data Center Workloads
by: Thiyyakat, Meghana, et al.
Published: (2023)

Kub: Enabling Elastic HPC Workloads on Containerized Environments
by: Medeiros, Daniel, et al.
Published: (2024)

Data Management System Analysis for Distributed Computing Workloads
by: Hsu, Kuan-Chieh, et al.
Published: (2025)

SYMPHONY: Improving Memory Management for LLM Inference Workloads
by: Agarwal, Saurabh, et al.
Published: (2024)

Workload Intelligence: Punching Holes Through the Cloud Abstraction
by: Huang, Lexiang, et al.
Published: (2024)

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

Inter-APU Communication on AMD MI300A Systems via Infinity Fabric: a Deep Dive
by: Schieffer, Gabin, et al.
Published: (2025)

Evaluating Container Orchestration for Neuromorphic Workloads in Virtual Edge Environments
by: Pham, Huyen, et al.
Published: (2026)

LLMSched: Uncertainty-Aware Workload Scheduling for Compound LLM Applications
by: Zhu, Botao, et al.
Published: (2025)