会议论文详细信息
20th International Conference on Computing in High Energy and Nuclear Physics
Vectorising the detector geometry to optimise particle transport
物理学;计算机科学
Apostolakis, John^1 ; Brun, René^1 ; Carminati, Federico^1 ; Gheata, Andrei^1 ; Wenzel, Sandro^1
European Organisation for Nuclear Research (CERN), Geneva, Switzerland^1
关键词: Critical discussions;    Elementary function;    Elementary geometry;    Geometry algorithms;    Instruction set extension;    Navigation algorithms;    Performance benefits;    Performance enhancements;   
Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/513/5/052038/pdf
DOI  :  10.1088/1742-6596/513/5/052038
学科分类:计算机科学(综合)
来源: IOP
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【 摘 要 】

Among the components contributing to particle transport, geometry navigation is an important consumer of CPU cycles. The tasks performed to get answers to «basic» queries such as locating a point within a geometry hierarchy or computing accurately the distance to the next boundary can become very computing intensive for complex detector setups. So far, the existing geometry algorithms employ mainly scalar optimisation strategies (voxelisation, caching) to reduce their CPU consumption. In this paper, we would like to take a different approach and investigate how geometry navigation can benefit from the vector instruction set extensions that are one of the primary source of performance enhancements on current and future hardware. While on paper, this form of microparallelism promises increasing performance opportunities, applying this technology to the highly hierarchical and multiply branched geometry code is a difficult challenge. We refer to the current work done to vectorise an important part of the critical navigation algorithms in the ROOT geometry library. Starting from a short critical discussion about the programming model, we present the current status and first benchmark results of the vectorisation of some elementary geometry shape algorithms. On the path towards a full vector-based geometry navigator, we also investigate the performance benefits in connecting these elementary functions together to develop algorithms which are entirely based on the flow of vector-data. To this end, we discuss core components of a simple vector navigator that is tested and evaluated on a toy detector setup.

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