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DeepSpotCloud: Leveraging Cross-Region GPU Spot Instances for Deep Learning
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1016/j.future.2012.06.012openalex-snapshot
Characterizing spot price dynamics in public cloud environments
inferredcites →https://doi.org/10.1109/cloud.2010.35openalex-snapshot
Reducing Costs of Spot Instances via Checkpointing in the Amazon Elastic Compute Cloud
inferredcites →https://doi.org/10.1109/ucc.2014.25openalex-snapshot
Design and Implementation of Middleware for Cloud Disaster Recovery via Virtual Machine Migration Management
inferredcites →https://doi.org/10.1145/2509413.2509416openalex-snapshot
Deconstructing Amazon EC2 Spot Instance Pricing
inferredcites →https://doi.org/10.1145/2640087.2644155openalex-snapshot
Scaling Distributed Machine Learning with the Parameter Server
inferredcites →https://doi.org/10.1145/2749246.2749275openalex-snapshot
Cutting the Cost of Hosting Online Services Using Cloud Spot Markets
inferredcites →https://doi.org/10.1145/2886107.2886110openalex-snapshot
Resilient Distributed Datasets
inferredcites →https://doi.org/10.25080/majora-92bf1922-003openalex-snapshot
Theano: A CPU and GPU Math Compiler in Python
inferredcites →https://doi.org/10.48550/arxiv.1408.5093openalex-snapshot
Caffe: Convolutional Architecture for Fast Feature Embedding
inferredcites →https://doi.org/10.48550/arxiv.1512.06216openalex-snapshot
Poseidon: A System Architecture for Efficient GPU-based Deep Learning on Multiple Machines
inferredcites →https://doi.org/10.48550/arxiv.1605.08695openalex-snapshot
TensorFlow: A system for large-scale machine learning
inferredcites →https://doi.org/10.5555/1855741.1855744openalex-snapshot
Improving MapReduce performance in heterogeneous environments
inferredcites →https://doi.org/10.5555/2685048.2685095openalex-snapshot
Scaling distributed machine learning with the parameter server
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-030-85665-6_20openalex-snapshot
A Fault Tolerant and Deadline Constrained Sequence Alignment Application on Cloud-Based Spot GPU Instances
inferred← citeshttps://doi.org/10.1007/978-3-031-29769-4_10openalex-snapshot
Ensuring Application Continuity with Fault Tolerance Techniques
inferred← citeshttps://doi.org/10.1007/978-3-031-29769-4_9openalex-snapshot
Harnessing Low-Cost Virtual Machines on the Spot
inferred← citeshttps://doi.org/10.1007/978-3-319-94289-6_12openalex-snapshot
Accelerating Training for Distributed Deep Neural Networks in MapReduce
inferred← citeshttps://doi.org/10.1007/978-3-319-94295-7_6openalex-snapshot
A Prediction Approach to Define Checkpoint Intervals in Spot Instances
inferred← citeshttps://doi.org/10.1007/978-981-10-6520-0_23openalex-snapshot
Time-Series Analysis for Price Prediction of Opportunistic Cloud Computing Resources
inferred← citeshttps://doi.org/10.1007/978-981-97-3242-5_30openalex-snapshot
Maximizing Cloud Resource Utility: Region-Adaptive Optimization via Machine Learning-Informed Spot Price Predictions
inferred← citeshttps://doi.org/10.1007/s10586-026-06447-5openalex-snapshot
Predicting CNN training latency on cloud GPUs without disclosing model architecture
inferred← citeshttps://doi.org/10.1007/s11227-018-2375-9openalex-snapshot
A hybrid GPU cluster and volunteer computing platform for scalable deep learning
inferred← citeshttps://doi.org/10.1016/j.dss.2022.113815openalex-snapshot
Spot instance similarity and substitution effect in cloud spot market
inferred← citeshttps://doi.org/10.1016/j.ins.2018.04.053openalex-snapshot
A multi-factor monitoring fault tolerance model based on a GPU cluster for big data processing
inferred← citeshttps://doi.org/10.1016/j.sysarc.2019.101651openalex-snapshot
MULTS: A multi-cloud fault-tolerant architecture to manage transient servers in cloud computing
inferred← citeshttps://doi.org/10.1109/access.2022.3184692openalex-snapshot
Scale-Train: A Scalable DNN Training Framework for a Heterogeneous GPU Cloud
inferred← citeshttps://doi.org/10.1109/aixset65682.2025.00030openalex-snapshot
Industrial Case Study: Cost-Efficient Use of Cloud Spot Instances for Distributed DNN Training
inferred← citeshttps://doi.org/10.1109/bigdata55660.2022.10020212openalex-snapshot
PROFET: PROFiling-based CNN Training Latency ProphET for GPU Cloud Instances
inferred← citeshttps://doi.org/10.1109/bracis.2018.00069openalex-snapshot
An Agent-Based Fog Computing Architecture for Resilience on Amazon EC2 Spot Instances
inferred← citeshttps://doi.org/10.1109/cahpc.2018.8645859openalex-snapshot
A Fault-Tolerant Agent-Based Architecture for Transient Servers in Fog Computing
inferred← citeshttps://doi.org/10.1109/ccgrid59990.2024.00029openalex-snapshot
Workload-Aware Live Migratable Cloud Instance Detector
inferred← citeshttps://doi.org/10.1109/ccgrid59990.2024.00034openalex-snapshot
DeepVM: Integrating Spot and On-Demand VMs for Cost-Efficient Deep Learning Clusters in the Cloud
inferred← citeshttps://doi.org/10.1109/cloud72782.2026.00022openalex-snapshot
SpotWhisk: Transferring the Spot Instances Cost-Efficiency to Serverless Data Analytics Pipelines
inferred← citeshttps://doi.org/10.1109/cloudcom2018.2018.00050openalex-snapshot
A Resilient Agent-Based Architecture for Efficient Usage of Transient Servers in Cloud Computing
inferred← citeshttps://doi.org/10.1109/hpca68181.2026.11408557openalex-snapshot
SpotCC: Facilitating Coded Computation for Prediction Serving Systems on Spot Instances
inferred← citeshttps://doi.org/10.1109/icac.2019.00024openalex-snapshot
Speeding up Deep Learning with Transient Servers
inferred← citeshttps://doi.org/10.1109/icacce.2018.8441719openalex-snapshot
K-mean Clustering in Web Service Quality Datasets Using AWS and RapidMiner
inferred← citeshttps://doi.org/10.1109/icdabi51230.2020.9325662openalex-snapshot
A Survey On Cloud-Based Distributed Computing System Frameworks
inferred← citeshttps://doi.org/10.1109/icra55743.2025.11127588openalex-snapshot
FogROS2-PLR: Probabilistic Latency-Reliability for Cloud Robotics
inferred← citeshttps://doi.org/10.1109/iiswc55918.2022.00029openalex-snapshot
SpotLake: Diverse Spot Instance Dataset Archive Service
inferred← citeshttps://doi.org/10.1109/infocom41043.2020.9155448openalex-snapshot
Machine Learning on Volatile Instances
inferred← citeshttps://doi.org/10.1109/iros58592.2024.10802613openalex-snapshot
FogROS2-FT: Fault Tolerant Cloud Robotics
inferred← citeshttps://doi.org/10.1109/ispa-bdcloud-sustaincom-socialcom48970.2019.00204openalex-snapshot
An Optimizing Algorithm for Deadline Constrained Scheduling of Scientific Workflows in IaaS Clouds Using Spot Instances
inferred← citeshttps://doi.org/10.1109/tcc.2026.3672402openalex-snapshot
Pygration : Workload-Aware Live Migratable Cloud Instance Detector for Python Runtime
inferred← citeshttps://doi.org/10.1109/tencon50793.2020.9293906openalex-snapshot
Implementation of Automated Annotation through Mask RCNN Object Detection model in CVAT using AWS EC2 Instance
inferred← citeshttps://doi.org/10.1109/tnet.2021.3112082openalex-snapshot
Machine Learning on Volatile Instances: Convergence, Runtime, and Cost Tradeoffs
inferred← citeshttps://doi.org/10.1145/3472716.3472842openalex-snapshot
Cost-effective data analytics across multiple cloud regions
inferred← citeshttps://doi.org/10.1145/3543873.3587314openalex-snapshot
Public Spot Instance Dataset Archive Service
inferred← citeshttps://doi.org/10.1145/3589334.3645548openalex-snapshot
Making Cloud Spot Instance Interruption Events Visible
inferred← citeshttps://doi.org/10.1145/3642970.3655843openalex-snapshot
ML Training with Cloud GPU Shortages
inferred← citeshttps://doi.org/10.1145/3652892.3700750openalex-snapshot
SpotVerse: Optimizing Bioinformatics Workflows with Multi-Region Spot Instances in Galaxy and Beyond
inferred← citeshttps://doi.org/10.1145/3731545.3735122openalex-snapshot
Multi-Node Spot Instances Availability Score Collection System
inferred← citeshttps://doi.org/10.1145/3731569.3764839openalex-snapshot
Sailor: Automating Distributed Training over Dynamic, Heterogeneous, and Geo-distributed Clusters
inferred← citeshttps://doi.org/10.1145/3760250.3762231openalex-snapshot
GFS: A Preemption-aware Scheduling Framework for GPU Clusters with Predictive Spot Instance Management
inferred← citeshttps://doi.org/10.12785/ijcds/0906021openalex-snapshot
Spot Hopping: Increasing Reliability and Reducing Cost
inferred← citeshttps://doi.org/10.14778/3648160.3648165openalex-snapshot
How Can We Train Deep Learning Models Across Clouds and Continents? An Experimental Study
inferred← citeshttps://doi.org/10.24200/sci.2022.58049.5537openalex-snapshot
Deep Learning Based Convolutional Neural Network Structured New Image Classification Approach for Eye Disease Identification
inferred← citeshttps://doi.org/10.31590/ejosat.804599openalex-snapshot
İnsansız Su Altı Araçlarında Derin Öğrenme Yöntemleri
inferred← citeshttps://doi.org/10.3233/mgs-190312openalex-snapshot
Towards increasing reliability of Amazon EC2 spot instances with a fault-tolerant multi-agent architecture
inferred← citeshttps://doi.org/10.3390/electronics10080952openalex-snapshot
GPU-Based Embedded Intelligence Architectures and Applications
inferred← citeshttps://doi.org/10.3390/s19071673openalex-snapshot
On the Combination of Multi-Cloud and Network Coding for Cost-Efficient Storage in Industrial Applications
inferred← citeshttps://doi.org/10.5753/eradsp.2019.13588openalex-snapshot
A cost-benefit analysis of GPU-based EC2 instances for a deep learning algorithm
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