HEALPix地图的gpu加速查看器

IF 16.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
A.V. Frolov
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引用次数: 0

摘要

Górskiet al.(2005)的HEALPix是宇宙微波背景(CMB)数据存储和分析的事实上的标准,并广泛用于当前和即将进行的CMB实验。几乎所有的微波背景数据分析遗留档案(LAMBDA)中的数据集都使用HEALPix作为选择的格式。可视化数据在研究中扮演着重要的角色,并且为HEALPix地图开发了一些工具集,其中最著名的是原始的Fortran工具和与healpy的Python集成。在GPU性能的当前状态下,现在可以在笔记本电脑或平板电脑上实时可视化超大地图。这里描述的HEALPix Viewer是为macOS开发的,并充分利用GPU加速来实时处理超大数据集。它在Intel和Arm64架构上本地编译,并使用Metal框架进行高性能GPU计算。这个项目的目的是减少交互式数据探索所需的工作量,以及减少制作出版质量地图的时间开销。与Keynote和Powerpoint的拖放集成使创建演示文稿变得容易。主代码库是用Swift编写的,这是一种现代高效的编译语言,高性能的计算部分完全委托给GPU,并且在C语言中插入了一些与cfisio库接口的I/O。图形用户界面是用SwiftUI编写的,SwiftUI是一个新的基于Swift的声明式UI框架。大多数常见的球形投影和颜色映射都是开箱即用的,可用的源代码使定制应用程序和添加新特性变得容易。在M1 Max笔记本电脑上,可以实时处理nside=8192张地图,并以60fps的全分辨率渲染几何效果,对机器没有明显的负载。主要面向用户的延迟限于cpu限制的cfisio加载时间,排序需要构造用于统计分析的累积分布函数(CDF)估计器(隐藏在后台队列中)。总体性能在当前Python软件堆栈上提高了3 - 180倍,具体取决于手头的任务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A GPU-accelerated viewer for HEALPix maps

HEALPix by Górskiet al. (2005) is a de-facto standard for Cosmic Microwave Background (CMB) data storage and analysis, and is widely used in current and upcoming CMB experiments. Almost all the datasets in Legacy Archive for Microwave Background Data Analysis (LAMBDA) use HEALPix as a format of choice. Visualizing the data plays important role in research, and several toolsets were developed to do that for HEALPix maps, most notably original Fortran facilities and Python integration with healpy. With the current state of GPU performance, it is now possible to visualize extremely large maps in real time on a laptop or a tablet. HEALPix Viewer described here is developed for macOS, and takes full advantage of GPU acceleration to handle extremely large datasets in real time. It compiles natively on Intel and Arm64 architectures, and uses Metal framework for high-performance GPU computations. The aim of this project is to reduce the effort required for interactive data exploration, as well as time overhead for producing publication-quality maps. Drag and drop integration with Keynote and Powerpoint makes creating presentations easy. The main codebase is written in Swift, a modern and efficient compiled language, with high-performance computing parts delegated entirely to GPU, and a few inserts in C interfacing to cfitsio library for I/O. Graphical user interface is written in SwiftUI, a new declarative UI framework based on Swift. Most common spherical projections and colormaps are supported out of the box, and the available source code makes it easy to customize the application and to add new features if desired. On a M1 Max laptop, an nside=8192 maps are processed in real time, with geometry effects rendered at 60fps in full resolution with no appreciable load to the machine. Main user-facing delays are limited to CPU-bound cfitsio load times, and sorting needed to construct Cumulative Distribution Function (CDF) estimators for statistical analysis (hidden in background queue). Overall performance improves on the current Python software stack by a factor of 3–180x depending on the task at hand.

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来源期刊
Accounts of Chemical Research
Accounts of Chemical Research 化学-化学综合
CiteScore
31.40
自引率
1.10%
发文量
312
审稿时长
2 months
期刊介绍: Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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