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Proceedings of the 17th ACM SIGPLAN symposium on Principles and Practice of Parallel Programming
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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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Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/cpe.3033openalex-snapshot
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Fast and Efficient Total Exchange on Two Clusters
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Static Detection of Race Conditions in Erlang
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MilkyWay-2 supercomputer: system and application
inferred← citeshttps://doi.org/10.1016/b978-0-12-803738-6.00007-0openalex-snapshot
Graph algorithms on GPUs
inferred← citeshttps://doi.org/10.1016/bs.adcom.2016.09.005openalex-snapshot
Data Flow Computing in Geoscience Applications
inferred← citeshttps://doi.org/10.1016/j.future.2019.09.052openalex-snapshot
WolfGraph: The edge-centric graph processing on GPU
inferred← citeshttps://doi.org/10.1016/j.ipl.2016.03.009openalex-snapshot
MMH⁎ with arbitrary modulus is always almost-universal
inferred← citeshttps://doi.org/10.1016/j.jcss.2014.06.021openalex-snapshot
Heterogeneous programming with Single Operation Multiple Data
inferred← citeshttps://doi.org/10.1016/j.jpdc.2014.03.006openalex-snapshot
Online auto-tuning for the time-step-based parallel solution of ODEs on shared-memory systems
inferred← citeshttps://doi.org/10.1016/j.jpdc.2014.09.013openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.jpdc.2015.12.001openalex-snapshot
Optimizing memory transactions for large-scale programs
inferred← citeshttps://doi.org/10.1016/j.jpdc.2017.04.002openalex-snapshot
A quantitative roofline model for GPU kernel performance estimation using micro-benchmarks and hardware metric profiling
inferred← citeshttps://doi.org/10.1016/j.jpdc.2017.11.007openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.jpdc.2019.03.016openalex-snapshot
Node aware sparse matrix–vector multiplication
inferred← citeshttps://doi.org/10.1016/j.jpdc.2021.02.008openalex-snapshot
Performance Analysis and Optimization Opportunities for NVIDIA Automotive GPUs
inferred← citeshttps://doi.org/10.1016/j.jpdc.2022.04.006openalex-snapshot
Using skip graphs for increased NUMA locality
inferred← citeshttps://doi.org/10.1016/j.jpdc.2023.104790openalex-snapshot
GPU-accelerated transportation simplex algorithm
inferred← citeshttps://doi.org/10.1016/j.jpdc.2025.105135openalex-snapshot
Towards efficient program execution on edge-cloud computing platforms
inferred← citeshttps://doi.org/10.1016/j.jss.2016.07.032openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.micpro.2022.104707openalex-snapshot
NDP-RANK: Prediction and ranking of NDP systems performance using machine learning
inferred← citeshttps://doi.org/10.1016/j.parco.2016.05.012openalex-snapshot
GPU-accelerated Hungarian algorithms for the Linear Assignment Problem
inferred← citeshttps://doi.org/10.1016/j.parco.2022.102942openalex-snapshot
Performance and accuracy predictions of approximation methods for shortest-path algorithms on GPUs
inferred← citeshttps://doi.org/10.1016/j.parco.2023.103061openalex-snapshot
Program partitioning and deadlock analysis for MPI based on logical clocks
inferred← citeshttps://doi.org/10.1016/j.scico.2016.05.002openalex-snapshot
Process-aware web programming with Jolie
inferred← citeshttps://doi.org/10.1016/j.scico.2017.09.005openalex-snapshot
ESBMC-GPU A context-bounded model checking tool to verify CUDA programs
inferred← citeshttps://doi.org/10.1016/j.simpat.2018.12.003openalex-snapshot
Analyzing data locality in GPU kernels using memory footprint analysis
inferred← citeshttps://doi.org/10.1016/j.sysarc.2016.04.010openalex-snapshot
A comprehensive reconfigurable computing approach to memory wall problem of large graph computation
inferred← citeshttps://doi.org/10.1016/j.techsoc.2024.102556openalex-snapshot
Supercomputers and quantum computing on the axis of cyber security
inferred← citeshttps://doi.org/10.1089/big.2017.0025openalex-snapshot
DISCRN: A Distributed Storytelling Framework for Intelligence Analysis
inferred← citeshttps://doi.org/10.1145/273011.273014openalex-snapshot
Performance evaluation of the Orca shared-object system
inferred← citeshttps://doi.org/10.1145/291889.291900openalex-snapshot
Constraint-based array dependence analysis
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Alleviating Irregularity in Graph Analytics Acceleration
inferred← citeshttps://doi.org/10.1145/3462206openalex-snapshot
Safe-by-default Concurrency for Modern Programming Languages
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Simmer: Rate proportional scheduling to reduce packet drops in vGPU based NF chains
inferred← citeshttps://doi.org/10.1145/3555819.3555857openalex-snapshot
Efficient Process Arrival Pattern Aware Collective Communication for Deep Learning
inferred← citeshttps://doi.org/10.1145/3640537.3641566openalex-snapshot
YFlows: Systematic Dataflow Exploration and Code Generation for Efficient Neural Network Inference using SIMD Architectures on CPUs
inferred← citeshttps://doi.org/10.1145/3652586.3663313openalex-snapshot
Work Assisting: Linking Task-Parallel Work Stealing with Data-Parallel Self Scheduling
inferred← citeshttps://doi.org/10.1145/3744904openalex-snapshot
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inferred← citeshttps://doi.org/10.1177/0037549709102918openalex-snapshot
Secure Referee Selection for Fair and Responsive Peer-to-Peer Gaming
inferred← citeshttps://doi.org/10.1177/1094342005051521openalex-snapshot
Optimization of Collective Communication Operations in MPICH
inferred← citeshttps://doi.org/10.1177/1094342014522573openalex-snapshot
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inferred← citeshttps://doi.org/10.14778/3611479.3611502openalex-snapshot
BP-Tree: Overcoming the Point-Range Operation Tradeoff for In-Memory B-Trees
inferred← citeshttps://doi.org/10.14778/3665844.3665852openalex-snapshot
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inferred← citeshttps://doi.org/10.14778/3665844.3665859openalex-snapshot
BYO: A Unified Framework for Benchmarking Large-Scale Graph Containers
inferred← citeshttps://doi.org/10.3389/fninf.2019.00019openalex-snapshot
Communication Sparsity in Distributed Spiking Neural Network Simulations to Improve Scalability
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