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CALCioM: Mitigating I/O Interference in HPC Systems through Cross-Application Coordination
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1006/jpdc.2000.1733openalex-snapshot
Evaluation of Collective I/O Implementations on Parallel Architectures
inferredcites →https://doi.org/10.1007/978-3-540-88871-0_61openalex-snapshot
Towards a High Performance Implementation of MPI-IO on the Lustre File System
inferredcites →https://doi.org/10.1007/s00450-009-0073-9openalex-snapshot
A Novel network request scheduler for a large scale storage system
inferredcites →https://doi.org/10.1109/ccgrid.2009.71openalex-snapshot
Improving Parallel Write by Node-Level Request Scheduling
inferredcites →https://doi.org/10.1109/cloud.2010.65openalex-snapshot
Understanding Performance Interference of I/O Workload in Virtualized Cloud Environments
inferredcites →https://doi.org/10.1109/cluster.2012.26openalex-snapshot
Damaris: How to Efficiently Leverage Multicore Parallelism to Achieve Scalable, Jitter-free I/O
inferredcites →https://doi.org/10.1109/clustr.2002.1137773openalex-snapshot
Noncontiguous I/O through PVFS
inferredcites →https://doi.org/10.1109/clustr.2006.311854openalex-snapshot
I/O Scheduling Service for Multi-Application Clusters
inferredcites →https://doi.org/10.1109/fmpc.1999.750599openalex-snapshot
Data sieving and collective I/O in ROMIO
inferredcites →https://doi.org/10.1109/hipc.2009.5433218openalex-snapshot
Fast checkpointing by Write Aggregation with Dynamic Buffer and Interleaving on multicore architecture
inferredcites →https://doi.org/10.1109/icdcs.2011.33openalex-snapshot
Provisioning a Multi-tiered Data Staging Area for Extreme-Scale Machines
inferredcites →https://doi.org/10.1109/iiswc.2005.1526010openalex-snapshot
Understanding the causes of performance variability in HPC workloads
inferredcites →https://doi.org/10.1109/ipdps.2010.5470424openalex-snapshot
Parallel I/O performance: From events to ensembles
inferredcites →https://doi.org/10.1109/ipdps.2012.39openalex-snapshot
Opportunistic Data-driven Execution of Parallel Programs for Efficient I/O Services
inferredcites →https://doi.org/10.1109/sc.2008.5214358openalex-snapshot
Scaling parallel I/O performance through I/O delegate and caching system
inferredcites →https://doi.org/10.1109/sc.2010.18openalex-snapshot
Design, Modeling, and Evaluation of a Scalable Multi-level Checkpointing System
inferredcites →https://doi.org/10.1109/sc.2010.28openalex-snapshot
Functional Partitioning to Optimize End-to-End Performance on Many-core Architectures
inferredcites →https://doi.org/10.1109/sc.2010.30openalex-snapshot
IOrchestrator: Improving the Performance of Multi-node I/O Systems via Inter-Server Coordination
inferredcites →https://doi.org/10.1109/sc.2010.32openalex-snapshot
Managing Variability in the IO Performance of Petascale Storage Systems
inferredcites →https://doi.org/10.1109/sc.companion.2012.203openalex-snapshot
Abstract: Reservation-Based I/O Performance Guarantee for MPI-IO Applications Using Shared Storage Systems
inferredcites →https://doi.org/10.1109/sc.companion.2012.204openalex-snapshot
Poster: Reservation-Based I/O Performance Guarantee for MPI-IO Applications Using Shared Storage Systems
inferredcites →https://doi.org/10.1109/tpds.2006.36openalex-snapshot
High-level buffering for hiding periodic output cost in scientific simulations
inferredcites →https://doi.org/10.1145/1654059.1654100openalex-snapshot
I/O performance challenges at leadership scale
inferredcites →https://doi.org/10.1145/2063384.2063407openalex-snapshot
Server-side I/O coordination for parallel file systems
inferredcites →https://doi.org/10.1145/2063384.2063408openalex-snapshot
QoS support for end users of I/O-intensive applications using shared storage systems
inferredcites →https://doi.org/10.1145/2318916.2318919openalex-snapshot
I/O threads to reduce checkpoint blocking for an electromagnetics solver on Blue Gene/P and Cray XK6
inferredcites →https://doi.org/10.1145/2488551.2488556openalex-snapshot
Using MPI in high-performance computing services
inferredcites →https://doi.org/10.1145/582034.582051openalex-snapshot
MPI-IO/GPFS, an optimized implementation of MPI-IO on top of GPFS
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Automatic I/O scheduling algorithm selection for parallel file systems
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Cross‐layer coordination in the I/O software stack of extreme‐scale systems
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Probabilistic scheduling of dynamic I/O requests via application clustering for burst‐buffers equipped high‐performance computing
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Research Characterization on I/O Improvements of Storage Environments
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ADA-FS—Advanced Data Placement via Ad hoc File Systems at Extreme Scales
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Proctor: A Semi-Supervised Performance Anomaly Diagnosis Framework for Production HPC Systems
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E2EWatch: An End-to-End Anomaly Diagnosis Framework for Production HPC Systems
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DICE: Generic Data Abstraction for Enhancing the Convergence of HPC and Big Data
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Rule-Based Thermal Anomaly Detection for Tier-0 HPC Systems
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Scheduling Distributed I/O Resources in HPC Systems
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Introducing the Metric Proxy for Holistic I/O Measurements
inferred← citeshttps://doi.org/10.1007/978-3-032-07612-0_32openalex-snapshot
Accelerating I/O in Scientific Workflows with the Impact of Apache Ignite’s In-Memory File System
inferred← citeshttps://doi.org/10.1007/978-3-319-58667-0_17openalex-snapshot
Alleviating I/O Interference Through Workload-Aware Striping and Load-Balancing on Parallel File Systems
inferred← citeshttps://doi.org/10.1007/978-3-319-58667-0_19openalex-snapshot
Diagnosing Performance Variations in HPC Applications Using Machine Learning
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On the Performance of Spark on HPC Systems: Towards a Complete Picture
inferred← citeshttps://doi.org/10.1007/978-3-319-72971-8_3openalex-snapshot
Periodic I/O Scheduling for Super-Computers
inferred← citeshttps://doi.org/10.1007/978-3-319-92040-5_10openalex-snapshot
Machine Learning Based Parallel I/O Predictive Modeling: A Case Study on Lustre File Systems
inferred← citeshttps://doi.org/10.1007/978-981-99-7872-4_6openalex-snapshot
CLMS: Configurable and Lightweight Metadata Service for Parallel File Systems on NVMe SSDs
inferred← citeshttps://doi.org/10.1007/s10586-022-03640-0openalex-snapshot
Design and implementation of dynamic I/O control scheme for large scale distributed file systems
inferred← citeshttps://doi.org/10.1007/s10951-021-00685-8openalex-snapshot
Scheduling periodic I/O access with bi-colored chains: models and algorithms
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Reducing I/O variability using dynamic I/O path characterization in petascale storage systems
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GekkoFS — A Temporary Burst Buffer File System for HPC Applications
inferred← citeshttps://doi.org/10.1007/s42514-019-00005-9openalex-snapshot
Software-defined QoS for I/O in exascale computing
inferred← citeshttps://doi.org/10.1016/j.future.2018.03.029openalex-snapshot
Improving the Effectiveness of Burst Buffers for Big Data Processing in HPC Systems with Eley
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A multivariate and quantitative model for predicting cross-application interference in virtual environments
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Combining malleability and I/O control mechanisms to enhance the execution of multiple applications
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I/O-aware bandwidth allocation for petascale computing systems
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Client-side straggler-aware I/O scheduler for object-based parallel file systems
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Improved probabilistic I/O scheduling for limited-size Burst-Buffers deployed HPC
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StoreRush: An Application-Level Approach to Harvesting Idle Storage in a Best Effort Environment
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Design and Implementation of Burst Buffer Over-Subscription Scheme for HPC Storage Systems
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CLARISSE: A Middleware for Data-Staging Coordination and Control on Large-Scale HPC Platforms
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Pufferscale: Rescaling HPC Data Services for High Energy Physics Applications
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BBOS: Efficient HPC Storage Management via Burst Buffer Over-Subscription
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Taming Metadata-intensive HPC Jobs Through Dynamic, Application-agnostic QoS Control
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TRIO: Burst Buffer Based I/O Orchestration
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I/O-Aware Batch Scheduling for Petascale Computing Systems
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Modeling I/O Performance Variability Using Conditional Variational Autoencoders
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Harmonia: An Interference-Aware Dynamic I/O Scheduler for Shared Non-volatile Burst Buffers
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GekkoFS - A Temporary Distributed File System for HPC Applications
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IOMiner: Large-Scale Analytics Framework for Gaining Knowledge from I/O Logs
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Leveraging burst buffer coordination to prevent I/O interference
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Managing I/O Interference in a Shared Burst Buffer System
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Characterizing and Mitigating the I/O Scalability Challenges for Serverless Applications
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Scheduling the I/O of HPC Applications Under Congestion
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Controlled Contention: Balancing Contention and Reservation in Multicore Application Scheduling
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On the Root Causes of Cross-Application I/O Interference in HPC Storage Systems
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Understanding and Predicting Cross-Application I/O Interference in HPC Storage Systems
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Performance Characterization and Provenance of Distributed Task-based Workflows on HPC Platforms
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Can I/O Variability Be Reduced on QoS-Less HPC Storage Systems?
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Investigating Machine Learning Algorithms for Modeling SSD I/O Performance for Container-Based Virtualization
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Using Formal Grammars to Predict I/O Behaviors in HPC: The Omnisc'IO Approach
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Trends in Data Locality Abstractions for HPC Systems
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Harnessing Data Movement in Virtual Clusters for In-Situ Execution
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Checkpoint Scheduling for Shared Usage of Burst-Buffers in Supercomputers
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Revisiting I/O behavior in large-scale storage systems
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HARNESS: Holistic Resource Management for Diversely Scaled Edge Cloud Systems
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How File-access Patterns Influence the Degree of I/O Interference between Cluster Applications
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Checkpointing Strategies for Shared High-Performance Computing Platforms
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Adaptively Periodic I/O Scheduling for Concurrent HPC Applications
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Periodic I/O scheduling for super-computers
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Server-side log data analytics for I/O workload characterization and coordination on large shared storage systems
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AI4IO: a suite of AI-based tools for IO-aware HPC resource management
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Enhanced clustering analysis pipeline for performance analysis of parallel applications
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