DOI: 10.1109/BigData66926.2025.11401782 Whereas the literature describes an increasing number of graph algorithms, loading graphs remains a time-consuming component of the end-to-end execution time. Graph frameworks often rely on custom graph storage formats, that are not optimized for efficient loading of large-scale graph datasets. Furthermore, graph loading is often not optimized […]
algorithm design and engineering
20 posts
We’re excited to share that Marco has been awarded the Best Poster Award at the IPDPS 2025 PhD Forum! Marco’s winning poster, titled “Towards Efficient Asynchronous Single-Source Shortest Path”, presents Wasp, a novel algorithm that tackles the fundamental Single-Source Shortest Path problem. His approach addresses a key challenge in parallel […]
Two of our papers were accepted at IPDPS’25. Brian will present his work on improving the scalability of parallel molecular dynamics simulation. He has developed a novel way to reduce the scalability bottleneck that exists in the communication between those processes computing short-range forces vs those computing long-range forces. His […]
PDF versionDOI: 10.48550/arXiv.2507.00716 ParaGrapher is a graph loading API and library that enables graph processing frameworks to load large-scale compressed graphs with minimal overhead. This capability accelerates the design and implementation of new high-performance graph algorithms and their evaluation on a wide range of graphs and across different frameworks. However, […]
PDF versionDOI: 10.48550/arXiv.2404.19735 Comprehensive evaluation is one of the basis of experimental science. In High-Performance Graph Processing, a thorough evaluation of contributions becomes more achievable by supporting common input formats over different frameworks. However, each framework creates its specific format, which may not support reading large-scale real-world graph datasets. This […]
ParaGrapher source code has been integrated to LaganLighter and access to different WebGraph formats are available in LaganLighter: For further details, please refer to – LaganLighter source coder Repository: https://github.com/DIPSA-QUB/LaganLighter, particularly, the graph.c file.– ParaGrapher source code repository: https://github.com/DIPSA-QUB/ParaGrapher particularly, the src/webgraph.c and src/WG*.java files. Read more about ParaGrapher and […]
ParaGrapher source code for accessing WebGraphs have been published. The supported graph types are: ParaGrapher uses its asynchronous and parallel API to implement these graph types. The user needs to implement a callback function that is called by the API upon completion of reading a block of edges. Poplar uses […]
2023 IEEE International Conference on Big Data (BigData’23)December 15-18, 2023, Sorrento, Italia DOI: 10.1109/BigData59044.2023.10386309PDF (Authors Copy) Progress in High-Performance Computing in general, and High-Performance Graph Processing in particular, is highly dependent on the availability of publicly-accessible, relevant, and realistic data sets. To ensure continuation of this progress, we (i) investigate […]
Mohsen Koohi EsfahaniSupervisors: Hans Vandierendonck and Peter Kilpatrick Thesis in PDF formatThesis on QUB Pure Portal Graph algorithms find several usages in industry, science, humanities, and technology. The fast-growing size of graph datasets in the context of the processing model of the current hardware has resulted in different bottlenecks such […]