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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.
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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/jmbi.1990.9999openalex-snapshot
Basic Local Alignment Search Tool
inferredcites →https://doi.org/10.1007/978-3-642-18206-8_1openalex-snapshot
Transaction Processing Performance Council (TPC): State of the Council 2010
inferredcites →https://doi.org/10.1093/jamia/ocv047openalex-snapshot
The NIH BD2K center for big data in translational genomics
inferredcites →https://doi.org/10.1109/bigdata.2015.7363840openalex-snapshot
Scientific computing meets big data technology: An astronomy use case
inferredcites →https://doi.org/10.1109/cloudcom.2014.75openalex-snapshot
Towards Understanding the Usage Behavior of Google Cloud Users: The Mice and Elephants Phenomenon
inferredcites →https://doi.org/10.1109/cnsm.2010.5691343openalex-snapshot
PRESS: PRedictive Elastic ReSource Scaling for cloud systems
inferredcites →https://doi.org/10.1109/iiswc.2007.4362193openalex-snapshot
Workload Analysis and Demand Prediction of Enterprise Data Center Applications
inferredcites →https://doi.org/10.1109/isca.2008.7openalex-snapshot
Parallelism-Aware Batch Scheduling: Enhancing both Performance and Fairness of Shared DRAM Systems
inferredcites →https://doi.org/10.1109/mascots.2010.12openalex-snapshot
PAC: Pattern-driven Application Consolidation for Efficient Cloud Computing
inferredcites →https://doi.org/10.1109/micro.2007.40openalex-snapshot
Process Variation Tolerant 3T1D-Based Cache Architectures
inferredcites →https://doi.org/10.1109/micro.2014.53openalex-snapshot
SMiTe: Precise QoS Prediction on Real-System SMT Processors to Improve Utilization in Warehouse Scale Computers
inferredcites →https://doi.org/10.1109/msst.2014.6855538openalex-snapshot
Jericho: Achieving scalability through optimal data placement on multicore systems
inferredcites →https://doi.org/10.1109/rtas.2013.6531079openalex-snapshot
MemGuard: Memory bandwidth reservation system for efficient performance isolation in multi-core platforms
inferredcites →https://doi.org/10.1109/tpami.2008.128openalex-snapshot
80 Million Tiny Images: A Large Data Set for Nonparametric Object and Scene Recognition
inferredcites →https://doi.org/10.1145/1254882.1254886openalex-snapshot
QoS policies and architecture for cache/memory in CMP platforms
inferredcites →https://doi.org/10.1145/1394608.1382128openalex-snapshot
Parallelism-Aware Batch Scheduling
inferredcites →https://doi.org/10.1145/1542275.1542342openalex-snapshot
Rate-based QoS techniques for cache/memory in CMP platforms
inferredcites →https://doi.org/10.1145/1735970.1736058openalex-snapshot
Fairness via source throttling
inferredcites →https://doi.org/10.1145/1736020.1736058openalex-snapshot
Fairness via source throttling
inferredcites →https://doi.org/10.1145/1773394.1773400openalex-snapshot
Towards characterizing cloud backend workloads
inferredcites →https://doi.org/10.1145/2391229.2391236openalex-snapshot
Heterogeneity and dynamicity of clouds at scale
inferredcites →https://doi.org/10.1145/2485922.2485949openalex-snapshot
A hardware evaluation of cache partitioning to improve utilization and energy-efficiency while preserving responsiveness
inferredcites →https://doi.org/10.1145/2901318.2901354openalex-snapshot
Efficient queue management for cluster scheduling
inferredcites →https://doi.org/10.14778/2367502.2367519openalex-snapshot
Interactive analytical processing in big data systems
inferredcites →https://doi.org/10.5555/1972457.1972488openalex-snapshot
Mesos: a platform for fine-grained resource sharing in the data center
inferredcites →https://doi.org/10.5555/3026877.3026884openalex-snapshot
Altruistic scheduling in multi-resource clusters
inferredcites →https://doi.org/10.7551/mitpress/8996.003.0015openalex-snapshot
The Tradeoffs of Large-Scale Learning
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/cpe.6666openalex-snapshot
ScaleReactor: A graceful performance isolation agent with interference detection and investigation for container‐based scale‐out workloads
inferred← citeshttps://doi.org/10.1007/978-3-030-95391-1_44openalex-snapshot
PFA: Performance and Fairness-Aware LLC Partitioning Method
inferred← citeshttps://doi.org/10.1016/j.future.2019.11.016openalex-snapshot
dCCPI-predictor: A state-aware approach for effectively predicting cross-core performance interference
inferred← citeshttps://doi.org/10.1109/access.2022.3180788openalex-snapshot
Object Detection in Driving Datasets Using a High-Performance Computing Platform: A Benchmark Study
inferred← citeshttps://doi.org/10.1109/asp-dac66049.2026.11420662openalex-snapshot
SARA: A Stall-Aware Memory Allocation Strategy for Mixed-Criticality Systems
inferred← citeshttps://doi.org/10.1109/ccgrid51090.2021.00027openalex-snapshot
Perph: A Workload Co-location Agent with Online Performance Prediction and Resource Inference
inferred← citeshttps://doi.org/10.1109/cloud49709.2020.00091openalex-snapshot
TOPOSCH: Latency-Aware Scheduling Based on Critical Path Analysis on Shared YARN Clusters
inferred← citeshttps://doi.org/10.1109/cloud53861.2021.00069openalex-snapshot
Skynet: Performance-driven Resource Management for Dynamic Workloads
inferred← citeshttps://doi.org/10.1109/hpcc-smartcity-dss50907.2020.00002openalex-snapshot
DiHi: Distributed and Hierarchical Performance Modeling of Multi-VM Cloud Running Applications
inferred← citeshttps://doi.org/10.1109/icpads51040.2020.00071openalex-snapshot
DyRAC: Cost-aware Resource Assignment and Provider Selection for Dynamic Cloud Workloads
inferred← citeshttps://doi.org/10.1109/isads56919.2023.10092039openalex-snapshot
An Approach to Workload Generation for Cloud Benchmarking: a View from Alibaba Trace
inferred← citeshttps://doi.org/10.1109/tc.2026.3715803openalex-snapshot
G1Stack : A Learning-Assisted Scheduler Framework for Interactive and Batch Workload Co-Location With High Resource Efficiency
inferred← citeshttps://doi.org/10.1109/tcc.2021.3078690openalex-snapshot
Online Performance Modeling and Prediction for Single-VM Applications in Multi-Tenant Clouds
inferred← citeshttps://doi.org/10.1109/tpds.2020.3013948openalex-snapshot
Rusty: Runtime Interference-Aware Predictive Monitoring for Modern Multi-Tenant Systems
inferred← citeshttps://doi.org/10.1109/tpds.2022.3202493openalex-snapshot
QoS-Aware Co-Scheduling for Distributed Long-Running Applications on Shared Clusters
inferred← citeshttps://doi.org/10.1145/3369383openalex-snapshot
A Metric-Guided Method for Discovering Impactful Features and Architectural Insights for Skylake-Based Processors
inferred← citeshttps://doi.org/10.1186/s40537-021-00437-7openalex-snapshot
DV-DVFS: merging data variety and DVFS technique to manage the energy consumption of big data processing
inferred← citeshttps://doi.org/10.23919/date54114.2022.9774698openalex-snapshot
EVOLVE: Towards Converging Big-Data, High-Performance and Cloud-Computing Worlds
inferred← citeshttps://doi.org/10.23919/date69613.2026.11539408openalex-snapshot
Multi-Partner Project: dAIEDGE - A Network of Excellence for Distributed, Trustworthy, Efficient and Scalable AI at the Edge
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