Galactos: computing the anisotropic 3-point correlation function for 2 billion galaxies

SC17: International Conference for High Performance Computing, Networking, Storage and Analysis(2017)

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摘要
The nature of dark energy and the complete theory of gravity are two central questions currently facing cosmology. A vital tool for addressing them is the 3-point correlation function (3PCF), which probes deviations from a spatially random distribution of galaxies. However, the 3PCF's formidable computational expense has prevented its application to astronomical surveys comprising millions to billions of galaxies. We present Galactos, a high-performance implementation of a novel, O(N2) algorithm that uses a load-balanced k-d tree and spherical harmonic expansions to compute the anisotropic 3PCF. Our implementation is optimized for the Intel Xeon Phi architecture, exploiting SIMD parallelism, instruction and thread concurrency, and significant L1 and L2 cache reuse, reaching 39% of peak performance on a single node. Galactos scales to the full Cori system, achieving 9.8 PF (peak) and 5.06 PF (sustained) across 9636 nodes, making the 3PCF easily computable for all galaxies in the observable universe.
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关键词
anisotropic 3-point correlation function,dark energy,spatially random distribution,3PCF's formidable computational expense,astronomical surveys,high-performance implementation,load-balanced k-d tree,spherical harmonic expansions,anisotropic 3PCF,Intel Xeon Phi architecture,L2 cache reuse,Galactos scales,SIMD parallelism
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