Dr Aydın Buluç29 April 2021 Solving systems of linear equations have traditionally driven the research in sparse matrix computation for decades. Direct and iterative solvers, together with finite element computations, still account for the primary use case for sparse matrix data structures and algorithms. These sparse “solvers” often serve as the workhorse of many algorithms in spectral graph theory […]
Hans Vandierendonck
36 posts
Scheduling or distributing the computational workload over multiple threads is a critical and repeatedly performed activity in graph processing workloads. In a recent paper “Reducing the burden of parallel loop schedulers for many‐core processors” published in Concurrency & Computation: Practice & Experience, we investigated the overhead introduced by scheduling. This […]
Dr Jeremy Singer, University of Glasgow25 February 2021 Abstract:Love ’em or hate ’em, interactive computational notebooks are here to stay as a mainstream code development medium. In particular, the Jupyter system is widely used by the data science community. This presentation explores some use cases for programmatic introspection of a Jupyter notebook […]
Dr Giorgis Georgakoudis, Lawrence Livermore National Laboratory18 February 2021 Abstract: This talk will present an overview of research on different areas of open problems in HPC. On fault tolerance, Giorgis will present the Reinit solution for fault tolerance in large scale MPI applications. Reinit improves the recovery time of checkpointed […]
Dr Julian Shun, Massachusetts Institute of Technology 14 January 2021 Abstract: This talk presents new parallel algorithms for density-basedspatial clustering (DBSCAN) on point sets and structural clustering(SCAN) on graphs, two problems that have received significantattention due to their applicability in a variety of data analysistasks. Existing parallel algorithms for DBSCAN […]
https://doi.org/10.1109/HPEC43674.2020.9286179 Mixed-precision computation has been proposed as a means to accelerate iterative algorithms as it can reduce the memory bandwidth and cache effectiveness. This paper aims for further memory traffic reduction via introducing new half-precision (16 bit) data formats customized for PageRank. We develop two formats. A first format builds […]
https://doi.org/10.1145/3392717.3392753 Vectorization seeks to accelerate computation through data-level parallelism. Vectorization has been applied to graph processing, where the graph is traversed either in a push style or a pull style. As it is not well understood which style will perform better, there is a need for both vectorized push and […]
https://doi.org/10.1145/3293883.3295703 This work proposes Vertex- and Edge-Balanced Ordering (VEBO): balance the number of edges and the number of unique destinations of those edges. VEBO balances edges and vertices for graphs with a power-law degree distribution, and ensures an equal degree distribution between partitions. Experimental evaluation on three shared-memory graph processing […]
https://manycore.org.uk/summerschool.html The Manycore Summer School gives researchers an opportunity to learn theory and practice in a range of emerging manycore technologies, from seven world-leading academic and industrial researchers. Participants engaged with cutting-edge material in lectures, hands-on labs, and interactive poster sessions. The Manycore Summer School was held from Monday 16th to Friday 20th […]