On the public citation graph

Characterizing Output Bottlenecks of a Production Supercomputer

https://doi.org/10.1145/3335205
0 signed · 36 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/cpe.3125openalex-snapshot
Hello ADIOS: the challenges and lessons of developing leadership class I/O frameworks
inferredcites →https://doi.org/10.1007/978-3-319-20119-1_19openalex-snapshot
Predicting Performance of Non-contiguous I/O with Machine Learning
inferredcites →https://doi.org/10.1007/978-3-319-67630-2_11openalex-snapshot
HPC I/O in the Data Center Workshop (HPC-IODC)
inferredcites →https://doi.org/10.1007/s11227-014-1321-8openalex-snapshot
Understanding I/O workload characteristics of a Peta-scale storage system
inferredcites →https://doi.org/10.1016/j.cpc.2004.08.005openalex-snapshot
A non-staggered, conservative, , finite-volume scheme for 3D implicit extended magnetohydrodynamics in curvilinear geometries
inferredcites →https://doi.org/10.1063/1.2937116openalex-snapshot
Spontaneous rotation sources in a quiescent tokamak edge plasma
inferredcites →https://doi.org/10.1088/1742-6596/46/1/012openalex-snapshot
Gyrokinetic particle simulation of neoclassical transport in the pedestal/scrape-off region of a tokamak plasma
inferredcites →https://doi.org/10.1088/1749-4699/2/1/015001openalex-snapshot
Terascale direct numerical simulations of turbulent combustion using S3D
inferredcites →https://doi.org/10.1109/cluster.2011.18openalex-snapshot
EDO: Improving Read Performance for Scientific Applications through Elastic Data Organization
inferredcites →https://doi.org/10.1109/cluster.2016.58openalex-snapshot
Machine Learning Predictions of Runtime and IO Traffic on High-End Clusters
inferredcites →https://doi.org/10.1109/clustr.2009.5289150openalex-snapshot
24/7 Characterization of petascale I/O workloads
inferredcites →https://doi.org/10.1109/ipdps.2009.5161052openalex-snapshot
Adaptable, metadata rich IO methods for portable high performance IO
inferredcites →https://doi.org/10.1109/ipdps.2010.5470424openalex-snapshot
Parallel I/O performance: From events to ensembles
inferredcites →https://doi.org/10.1109/pccc.2011.6108062openalex-snapshot
Enhancing I/O throughput via efficient routing and placement for large-scale parallel file systems
inferredcites →https://doi.org/10.1109/sc.2008.5222721openalex-snapshot
Characterizing and predicting the I/O performance of HPC applications using a parameterized synthetic benchmark
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.2014.56openalex-snapshot
Omnisc'IO: A Grammar-Based Approach to Spatial and Temporal I/O Patterns Prediction
inferredcites →https://doi.org/10.1145/1060289openalex-snapshot
Proceedings of the 5th symposium on Operating systems design and implementation - OSDI '02
inferredcites →https://doi.org/10.1145/2027066.2027068openalex-snapshot
Understanding and Improving Computational Science Storage Access through Continuous Characterization
inferredcites →https://doi.org/10.1145/2043556.2043562openalex-snapshot
Design implications for enterprise storage systems via multi-dimensional trace analysis
inferredcites →https://doi.org/10.1145/214419.214421openalex-snapshot
VAXcluster
inferredcites →https://doi.org/10.1145/2749246.2749269openalex-snapshot
A Multiplatform Study of I/O Behavior on Petascale Supercomputers
inferredcites →https://doi.org/10.1145/3078597.3078614openalex-snapshot
Predicting Output Performance of a Petascale Supercomputer
inferredcites →https://doi.org/10.5555/1855511.1855522openalex-snapshot
Efficient object storage journaling in a distributed parallel file system

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/s11227-025-08015-xopenalex-snapshot
Improving I/O performance in HPC environments using the Expand Ad-Hoc file system
inferred← citeshttps://doi.org/10.1007/s11227-025-08106-9openalex-snapshot
An efficient lossy compression framework for density partitioning in AMR applications
inferred← citeshttps://doi.org/10.1109/ccgrid51090.2021.00015openalex-snapshot
Battle of the Defaults: Extracting Performance Characteristics of HDF5 under Production Load
inferred← citeshttps://doi.org/10.1109/escience51609.2021.00032openalex-snapshot
An Empirical Study of Package Dependencies and Lifetimes in Binder Python Containers
inferred← citeshttps://doi.org/10.1109/ipdps49936.2021.00064openalex-snapshot
Interpreting Write Performance of Supercomputer I/O Systems with Regression Models
inferred← citeshttps://doi.org/10.1109/ipdps65963.2026.00090openalex-snapshot
Locality-Aware Distributed Allocators for High-Performance Global Data Structures
inferred← citeshttps://doi.org/10.1109/pdsw49588.2019.00008openalex-snapshot
Applying Machine Learning to Understand Write Performance of Large-scale Parallel Filesystems
inferred← citeshttps://doi.org/10.1109/pdsw54622.2021.00010openalex-snapshot
SCTuner: An Autotuner Addressing Dynamic I/O Needs on Supercomputer I/O Subsystems
inferred← citeshttps://doi.org/10.1109/sc41405.2020.00006openalex-snapshot
Processing Full-Scale Square Kilometre Array Data on the Summit Supercomputer
inferred← citeshttps://doi.org/10.1109/tc.2023.3297442openalex-snapshot
LAMP: Improving Compression Ratio for AMR Applications via Level Associated Mapping-Based Preconditioning
inferred← citeshttps://doi.org/10.1145/3422575.3422791openalex-snapshot
The Need for Precise and Efficient Memory Capacity Budgeting
inferred← citeshttps://doi.org/10.1145/3700838.3700865openalex-snapshot
User-based I/O Profiling for Leadership Scale HPC Workloads
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.