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High-performance computing (HPC) is evolving rapidly, enabling breakthroughs in complex simulations. Modern clusters, with high-speed interconnects and increasing core counts, now support models exceeding 50 million degrees of freedom, demanding advanced computational solutions.

To meet these challenges, new distributed memory parallel (DMP) eigensolvers have been developed, optimized for hybrid parallelism to scale efficiently across nodes and cores.

In this seminar, we’ll introduce cutting-edge DMP eigensolvers, including:

• New DMP Lanczos Eigensolver

• New DMP Subspace Iteration Eigensolver

• Eigensolvers Characteristics Comparison & Best Performance Ranges

Learn how these innovations accelerate workflows, optimize solver strategies, and maximize HPC investments for large-scale simulations. Join us to explore the future of computational modeling.