PCIM 2017 - Minisymposium on High Performance Computing Interval Methods

Interval methods are a class of algorithms that are precise and even allow to obtain a guaranteed result. They also provide a useful and appropriate tool to describe the uncertainty of parameters, discretization inaccuracy and numerical errors. Nevertheless, they are usually time consuming and memory demanding.
Hence, all attempts to increase their efficiency are required and valuable: parallel implementations, use of new data structures, improved algorithms.
The Minisymposium is going to provide a forum for interval researchers to share their experiences and present possible improvements to the algorithms and successful applications.
Topics of interest include (but are not limited to):
parallelization of interval methods, in particular on multi-core architectures, supercomputers, grids or clouds
the use of GPU computing for interval analysis,
the use of BLAS, LAPACK, novel data formats and data structures for interval computations
auto-tuning of interval algorithms
global optimization/equations solving methods
linear systems with interval parameters
ordinary and partial differential equations
practical applications of interval scientific computing algorithms