Jan-Philipp Weiss - Böcker

The proceedings at hand are the outcome of the conference for young sci- tists titled Facing the Multicore-Challenge held at the Heidelberger Akademie der Wissenschaften, March 17-19, 2010. The conference focused on topics - lated to the impact of multicore and coprocessor technologies in science and for large-scale applications in an interdisciplinary environment. The conference was funded by the Heidelberger Akademie der Wissenschaften and placed emphasis on the support and advancement of young scientists. The aim of the conference was to bring together leading experts as well as motivated young researchers in order to discuss, recent developments, the present status of the ?eld, and its future prospects the exchange of ideas, in a pleasant atmosphere that stimulates. It was the designated goal to address current issues including mathematical modeling, design of parallel algorithms, aspects of microprocessor architecture, parallel programming languages, c- pilers, hardware-aware computing, heterogeneous platforms, emerging archit- tures, tools, performance tuning, and requirements for large-scale applications. Thisbroadrangeofissuesisre?ectedbythepresentconferenceproceedings.The results of the presented research papers clearly show the potential of emerging technologiesintheareaofmulticoreandmanycoreprocessorsthatarepavingthe way towards personal supercomputing.However, many issues related to parallel programmingenvironments, developmentof portable and future-proof concepts, and the design of scalable and manycore-ready algorithms still need to be - dressed in future research. Some of these points are the subject of the presented papers.

This state-of-the-art survey features topics related to the impact of multicore, manycore, and coprocessor technologies in science and for large-scale applications in an interdisciplinary environment. The paperscover issues of current research in mathematical modeling, design of parallel algorithms, aspects of microprocessor architecture, parallel programming languages, hardware-aware computing, heterogeneous platforms, manycore technologies, performance tuning, and requirements for large-scale applications. The contributions presented in this volume offer a survey on the state of the art, the concepts and perspectives for future developments. They are an outcome of an inspiring conference conceived and organized by theeditors at the Karlsruhe Institute Technology (KIT) in September 2011. The twelve revised full papers presented together with two contributed papers focus on combination of new aspects of microprocessor technologies, parallel applications, numerical simulation, and software development; thus they clearly show the potential of emerging technologies in the area of multicore and manycore processors that are paving the way towards personal supercomputing and very likely towards exascale computing.

This state-of-the-art survey features topics related to the impact of multicore, manycore, and coprocessor technologies in science and large-scale applications in an interdisciplinary environment. The papers included in this survey cover research in mathematical modeling, design of parallel algorithms, aspects of microprocessor architecture, parallel programming languages, hardware-aware computing, heterogeneous platforms, manycore technologies, performance tuning, and requirements for large-scale applications. The contributions presented in this volume are an outcome of an inspiring conference conceived and organized by the editors at the University of Applied Sciences (HfT) in Stuttgart, Germany, in September 2012. The 10 revised full papers selected from 21 submissions are presented together with the twelve poster abstracts and focus on combination of new aspects of microprocessor technologies, parallel applications, numerical simulation, and software development; thus they clearly show the potential of emerging technologies in the area of multicore and manycore processors that are paving the way towards personal supercomputing and very likely towards exascale computing.