As we approach the exascale era, large-scale computations and analyses have to be supported by efficient, scalable, and reliable algorithms and implementations. Ultimately, end users will face a range of algorithmic requirements regarding erformance, accuracy, and energy consumption. These requirements may potentially span a range of architectures including CPUs, GPUs, and FPGAs, typically in a heterogeneous environment.

This topic provides a forum to discuss recent developments in the design and implementation of parallel numerical algorithms. We encourage submissions that address algorithmic design, performance analysis, accuracy study, as well as integration of arallel numerical methods in real world/industrial applications.

Focus

• Applications of numerical algorithms in science and engineering
• Numerical methods for large-scale data analysis
• Sparse and dense numerical linear algebra
• Tensor operations, low-rank approximations
• Uncertainty quantification
• Optimization and non-linear problems
• Discrete and combinatorial algorithms
• Partial/ordinary and differential algebraic equations
• Implementation & analysis of parallel numerical algorithms