In this paper we study new algorithmic structures with Douglas-Rachford (DR) operators to solve convex feasibility problems. We propose to embed the basic two-set-DR algorithmic operator into the string-averaging proj...
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In this paper we study new algorithmic structures with Douglas-Rachford (DR) operators to solve convex feasibility problems. We propose to embed the basic two-set-DR algorithmic operator into the string-averaging projections and into the block-iterative projection algorithmic structures, thereby creating new DR algorithmic schemes that include the recently proposed cyclic DR algorithm and the averaged DR algorithm as special cases. We further propose and investigate a new multiple-set-DR algorithmic operator. Convergence of all these algorithmic schemes is studied by using properties of strongly quasi-nonexpansive operators and firmly nonexpansive operators.
One of the most critical challenges for high-performance computing (HPC) scientific visualization is execution on massively threaded processors. Of the many fundamental changes we are seeing in HPC systems, one of the...
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One of the most critical challenges for high-performance computing (HPC) scientific visualization is execution on massively threaded processors. Of the many fundamental changes we are seeing in HPC systems, one of the most profound is a reliance on new processor types optimized for execution bandwidth over latency hiding. Our current production scientific visualization software is not designed for these new types of architectures. To address this issue, the VTK-m framework serves as a container for algorithms, provides flexible data representation, and simplifies the design of visualization algorithms on new and future computer architecture.
作者：
Milkova, EvaUniv Hradec Kralove
Fac Informat & Management Dept Informat & Quantitat Methods Rokitanskeho 62 Hradec Kralove 50003 Czech Republic
At the faculties preparing students in the area of computer science, the creation of algorithms forms an inseparable part of the students' basic skills. Students must be able to think algorithmically, to create va...
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At the faculties preparing students in the area of computer science, the creation of algorithms forms an inseparable part of the students' basic skills. Students must be able to think algorithmically, to create various algorithms, solving given problems, starting with easy ones and consecutively increasing their algorithmic knowledge and shifts during studies, to the level where they deeply understand much more complex algorithms. Several years ago, secondary-school-students were taught how to create basic algorithms and write them into a program language, e.g., Basic or Pascal. But recently the situation in our country has changed rapidly. The user's approach by students has been increasing, but the algorithmic approach is almost unknown to them. This was the reason why our faculty decided to change the curricula with regard to accepted students who have been coming to the faculty without any previous algorithmic knowledge. In the paper we introduce our approach to the development of the students' algorithmic thinking.
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