Uploaded October 2025 | Updated September 2026, 1 week ago
Computation on networks and graphs at very large scale is important in applications as diverse as social networks, biology, infrastructure, finance, and cybersecurity. Much current work on high-performance graph analysis leans heavily on numerical linear algebra, both for mathematical foundations and for some 50 years of experience with high-performance sparse matrix computation.
*This minisymposium will present a variety of perspectives relating high-performance computation on graphs and on matrices, focusing on practical tools and applications.* The first talk highlights the use of distributed “hypersparse' matrices at very large scale in an application to cybersecurity. This is followed by a talk describing the SuiteSparse implementation of the GraphBLAS standard, which underpins that project among others. The final two talks focus respectively on matrices and on graphs: The third describes new work on the Sparse BLAS software API standard, and the fourth presents Arachne, an interactive system for large-scale graph analysis.
Join us for these 4 talks:
* 00:00 *Modeling Large-Scale Network Traffic with Anonymized Hypersparse Matrices* with Jeremy Kepner, Vijay Gadepally, and Hayden Jananthan or Massachusetts Institute of Technology, U.S.
* 24:00 *Suitesparse:Graphblas: Graph Algorithms in the Language of Linear Algebra* with Timothy A. Davis, Texas A&M University, U.S.
* 51:03 *Sparseblas: The New Interface to Sparse Linear Algebra Operations* with Piotr Luszczek, Massachusetts Institute of Technology, U.S.
* 1:19:03 *Arachne: An Open-Source Interactive Graph Analytics Framework for Real-World Problems* with David A. Bader, Oliver Alvarado Rodriguez, Zhihui Du, Fuhuan Li, and Mohammad Dindoost, New Jersey Institute of Technology, U.S.
* 1:41:50 *Q&A*
Learn more about SIAM siam.org
Join SIAM siam.org/membership/individual-membership
Attend a SIAM Conference siam.org/conferences-events
Computation on networks and graphs at very large scale is important in applications as diverse as social networks, biology, infrastructure, finance, and cybersecurity. Much current work on high-performance graph analysis leans heavily on numerical linear algebra, both for mathematical foundations and for some 50 years of experience with high-performance sparse matrix computation.
*This minisymposium will present a variety of perspectives relating high-performance computation on graphs and on matrices, focusing on practical tools and applications.* The first talk highlights the use of distributed “hypersparse' matrices at very large scale in an application to cybersecurity. This is followed by a talk describing the SuiteSparse implementation of the GraphBLAS standard, which underpins that project among others. The final two talks focus respectively on matrices and on graphs: The third describes new work on the Sparse BLAS software API standard, and the fourth presents Arachne, an interactive system for large-scale graph analysis.
Join us for these 4 talks:
* 00:00 *Modeling Large-Scale Network Traffic with Anonymized Hypersparse Matrices* with Jeremy Kepner, Vijay Gadepally, and Hayden Jananthan or Massachusetts Institute of Technology, U.S.
* 24:00 *Suitesparse:Graphblas: Graph Algorithms in the Language of Linear Algebra* with Timothy A. Davis, Texas A&M University, U.S.
* 51:03 *Sparseblas: The New Interface to Sparse Linear Algebra Operations* with Piotr Luszczek, Massachusetts Institute of Technology, U.S.
* 1:19:03 *Arachne: An Open-Source Interactive Graph Analytics Framework for Real-World Problems* with David A. Bader, Oliver Alvarado Rodriguez, Zhihui Du, Fuhuan Li, and Mohammad Dindoost, New Jersey Institute of Technology, U.S.
* 1:41:50 *Q&A*
Learn more about SIAM siam.org
Join SIAM siam.org/membership/individual-membership
Attend a SIAM Conference siam.org/conferences-events
