In the modern world of billions connected things and exponentially growing data, search in multidimensional spaces and optimisation of multidimensional tasks will become a daily need for variety of technologies and scientific fields. Resolving multidimensional tasks with thousands parameters and more require time, energy and other resources and seems to be an embarrassing challenge for modern computational systems in terms of software abilities and hardware capacity. Presented study focuses on evaluation and comparison of thousands dimensional heterogeneous real-value numerical optimisation tests on two enhanced performance computer systems. The aim is to extend the knowledge on multidimensional search and identification of acceptable solutions with non-zero probability on heterogeneous tasks. It aims also to study computational limitations, energy consumptions and time. Use of energy and time are measured and analysed. Experimental results are presented and can be used for further research and evaluation of other methods.
|Title of host publication||Large-Scale Scientific Computing. LSSC 2017. Lecture Notes in Computer Science|
|Editors||Ivan Lirkov, Svetozar Margenov|
|Number of pages||9|
|Publication status||Published - 1 Jan 2018|