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Scaling Irregular Applications through Data Aggregation and Software Multithreading
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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.1994.1104openalex-snapshot
Communication Optimizations for Irregular Scientific Computations on Distributed Memory Architectures
inferredcites →https://doi.org/10.1109/icpp.2006.34openalex-snapshot
Designing Multithreaded Algorithms for Breadth-First Search and st-connectivity on the Cray MTA-2
inferredcites →https://doi.org/10.1109/ipdps.2007.370484openalex-snapshot
ParalleX: A Study of A New Parallel Computation Model
inferredcites →https://doi.org/10.1109/ipdps.2011.104openalex-snapshot
Implementation and Performance Evaluation of the HPC Challenge Benchmarks in Coarray Fortran 2.0
inferredcites →https://doi.org/10.1109/ipdps.2011.360openalex-snapshot
Distributed-Memory Parallel Algorithms for Matching and Coloring
inferredcites →https://doi.org/10.1109/mc.2012.193openalex-snapshot
Designing Next-Generation Massively Multithreaded Architectures for Irregular Applications
inferredcites →https://doi.org/10.1145/1080399.1080400openalex-snapshot
Co-arrays in the next Fortran Standard
inferredcites →https://doi.org/10.1145/155332.155350openalex-snapshot
Implementing an irregular application on a distributed memory multiprocessor
inferredcites →https://doi.org/10.1145/156668.156680openalex-snapshot
Programming models for irregular applications
inferredcites →https://doi.org/10.1145/1809961.1809979openalex-snapshot
Fast PGAS connected components algorithms
inferredcites →https://doi.org/10.1177/1094342006064503openalex-snapshot
Advances, Applications and Performance of the Global Arrays Shared Memory Programming Toolkit
inferredcites →https://doi.org/10.1177/1094342006064504openalex-snapshot
High Performance Remote Memory Access Communication: The Armci Approach
inferredcites →https://doi.org/10.1177/1094342007078442openalex-snapshot
Parallel Programmability and the Chapel Language
inferredcites →https://doi.org/10.1177/1094342007078449openalex-snapshot
Parallel Languages and Compilers: Perspective From the Titanium Experience
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Extending OpenSHMEM with Aggregation Support for Improved Message Rate Performance
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Scaling RDF Triple Stores in Size and Performance
inferred← citeshttps://doi.org/10.1016/j.parco.2014.08.002openalex-snapshot
Toward a data scalable solution for facilitating discovery of science resources
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A parallel min-cut algorithm using iteratively reweighted least squares targeting at problems with floating-point edge weights
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Acceleration of Graph Neural Network-Based Prediction Models in Chemistry via Co-Design Optimization on Intelligence Processing Units
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Custom Accessors: Enabling Scalable Data Ingestion, (Re-)Organization, and Analysis on Distributed Systems
inferred← citeshttps://doi.org/10.1109/ccgrid.2018.00071openalex-snapshot
SHAD: The Scalable High-Performance Algorithms and Data-Structures Library
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High-Performance, Distributed Dictionary Encoding of RDF Datasets
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Distributed Work Stealing at Scale via Matchmaking
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Adaptive Runtime Features for Distributed Graph Algorithms
inferred← citeshttps://doi.org/10.1109/icpp.2015.71openalex-snapshot
Software-Based Lightweight Multithreading to Overlap Memory-Access Latencies of Commodity Processors
inferred← citeshttps://doi.org/10.1109/ipdps.2017.121openalex-snapshot
Exploring DataVortex Systems for Irregular Applications
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/ipdpsw.2017.70openalex-snapshot
High-Performance Data Analytics Beyond the Relational and Graph Data Models with GEMS
inferred← citeshttps://doi.org/10.1109/ipdpsw71298.2026.00009openalex-snapshot
Accelerating HPC Applications on Heterogeneous Distributed Systems with Standard C++
inferred← citeshttps://doi.org/10.1109/ipdrm49579.2019.00006openalex-snapshot
Advert: An Asynchronous Runtime for Fine-Grained Network Systems
inferred← citeshttps://doi.org/10.1109/mc.2015.74openalex-snapshot
In-Memory Graph Databases for Web-Scale Data
inferred← citeshttps://doi.org/10.1109/pgas.2015.10openalex-snapshot
Caching Puts and Gets in a PGAS Language Runtime
inferred← citeshttps://doi.org/10.1109/tpds.2014.2345073openalex-snapshot
Exploring Efficient Hardware Support for Applications with Irregular Memory Patterns on Multinode Manycore Architectures
inferred← citeshttps://doi.org/10.1109/tpds.2015.2453978openalex-snapshot
Graphine: Programming Graph-Parallel Computation of Large Natural Graphs for Multicore Clusters
inferred← citeshttps://doi.org/10.1145/3369583.3392680openalex-snapshot
Practical Distributed Programming in C++
inferred← citeshttps://doi.org/10.1145/3528416.3530784openalex-snapshot
Towards superior software portability with SHAD and HPX C++ libraries
inferred← citeshttps://doi.org/10.1145/3581784.3607049openalex-snapshot
Itoyori: Reconciling Global Address Space and Global Fork-Join Task Parallelism
inferred← citeshttps://doi.org/10.1145/3626203.3670566openalex-snapshot
Exploring Architectural-Aware Affinity Policies in Modern HPC Runtimes
inferred← citeshttps://doi.org/10.1145/3663479openalex-snapshot
Asynchronous Memory Access Unit: Exploiting Massive Parallelism for Far Memory Access
inferred← citeshttps://doi.org/10.23919/date.2019.8715196openalex-snapshot
A Parallel Graph Environment for Real-World Data Analytics Workflows
inferred← citeshttps://doi.org/10.31390/gradschool_dissertations.5781openalex-snapshot
Performance Analysis and Improvement for Scalable and Distributed Applications Based on Asynchronous Many-Task Systems
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