Comparison of Parallel Computing Methods for Fast Cone-Beam Reconstruction with Similar Optimization Strategies

2014 ◽  
Vol 519-520 ◽  
pp. 85-89
Author(s):  
Xiang Zhang ◽  
Bin Yan ◽  
Lei Li ◽  
Feng Zhang ◽  
Xiao Qi Xi ◽  
...  
Keyword(s):  
Parallel Computing ◽  
High Performance Computing ◽  
High Performance ◽  
Computing Methods ◽  
Experimental Results ◽  
Cone Beam ◽  
Cone Beam Reconstruction ◽  
Fdk Algorithm ◽  
Performance Computing

To investigate the performance of acceleration technologies for FDK algorithm, two of the most common high-performance computing hardware, multi-core CPU and GPU, are involved in our experiment. Both runtime and accuracy are regarded as the standards to evaluate the performance of four different programming methods: OpenMP, GLSL, CUDA and OpenCL. All the methods are estimated with comparable optimization strategies. The experimental results show that GPU has higher efficiency than multi-core CPU for fast cone-beam reconstruction, meanwhile CUDA is the best choice for programming on the multi-processor featured GPU.

scholarly journals METHODS AND ALGORITHMS FOR PARALLEL CALCULATIONS USING VIRTUALIZATION TECHNOLOGIES IN MATERIALS SCIENCE PROBLEMS

2021 ◽  
Author(s):  
Vadim Kondrashev ◽  
Sergey Denisov
Keyword(s):  
Parallel Computing ◽  
High Performance Computing ◽  
Material Science ◽  
High Performance ◽  
Applied Research ◽  
Materials Science ◽  
Parallel Calculations ◽  
Computing Technologies ◽  
Integrated Software ◽  
Performance Computing

The paper discusses methods and algorithms for the provision of high-performance computing resources in multicomputer systems in a shared mode for fundamental and applied research in the field of materials science. Approaches are proposed for the application of applied integrated software environments (frameworks) designed to solve material science problems using virtualization and parallel computing technologies.

Large Scale Mosaic Using Parallel Computing for Remote Sensed Images

2014 ◽  
Vol 556-562 ◽  
pp. 4746-4749
Author(s):  
Bin Chu ◽  
Da Lin Jiang ◽  
Bo Cheng
Keyword(s):  
Parallel Computing ◽  
High Performance Computing ◽  
High Performance ◽  
Large Scale ◽  
Computing System ◽  
Physical Relationship ◽  
High Performance Computing System ◽  
Performance Computing

This paper concerns about Large-scale mosaic for remote sensed images. Base on High Performance Computing system, we offer a method to decompose the problem and integrate them with logical and physical relationship. The mosaic of Large-scale remote sensed images has been improved both at performance and effectiveness.

scholarly journals galapagos-c: analysis of galaxy morphologies using high-performance computing methods

2014 ◽  
Vol 444 (4) ◽  
pp. 3089-3117 ◽  
Author(s):  
Andreas Hiemer ◽  
Marco Barden ◽  
Lee S. Kelvin ◽  
Boris Häußler ◽  
Sabine Schindler
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
Computing Methods ◽  
Performance Computing

scholarly journals Computational experiment in era of HPC

2019 ◽  
Vol 27 (3) ◽  
pp. 263-267
Author(s):  
Alexander S. Ayriyan
Keyword(s):  
Parallel Computing ◽  
Life Cycle ◽  
High Performance Computing ◽  
High Performance ◽  
Computational Experiment ◽  
Computing Systems ◽  
The Impact ◽  
Performance Computing

In this note we discuss the impact of development of architecture and technology of parallel computing on the typical life-cycle of the computational experiment. In particular, it is argued that development and installation of high-performance computing systems is indeed important itself regardless of specific scientific tasks, since the presence of cutting-age HPC systems within an academic infrastructure gives wide possibilities and stimulates new researches.

scholarly journals Computational experiment in era of HPC

2019 ◽  
Vol 27 (3) ◽  
pp. 263-267
Author(s):  
Alexander S. Ayriyan
Keyword(s):  
Parallel Computing ◽  
Life Cycle ◽  
High Performance Computing ◽  
High Performance ◽  
Computational Experiment ◽  
Computing Systems ◽  
The Impact ◽  
Performance Computing

In this note we discuss the impact of development of architecture and technology of parallel computing on the typical life-cycle of the computational experiment. In particular, it is argued that development and installation of high-performance computing systems is indeed important itself regardless of specific scientific tasks, since the presence of cutting-age HPC systems within an academic infrastructure gives wide possibilities and stimulates new researches.

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