一句话：综述高能物理实验计算需求，重点讨论HL-LHC对分布式基础设施提出的10–100倍扩展挑战与R&D方向。
粒子对撞机上的高能物理实验需要复杂计算基础设施，以从所收集的大规模数据集中提取知识；目前实验已存储超过1 EB数据。CERN大型强子对撞机（LHC）的计算需求曾推动2000年代大规模GRID研发与部署，事后证明足以支撑LHC数据处理。即将升级的高亮度LHC（HL-LHC）预计需要增加10倍至100倍的算力资源，现有分布式基础设施的可扩展性预计无法满足。文章介绍并讨论当前多条R&D路线，并指出SKA、CTA、Dune等具有类似计算复杂度的大科学项目，可能使这些方案适用于高能物理之外的领域。
The High Energy Physics (HEP) Experiments at Particle Colliders need complex computing infrastructures in order to extract knowledge from the large datasets collected, with over 1 Exabyte of data stored by the experiments by now. The computing needs from the top world machine, the Large Hadron Collider (LHC) at CERN/Geneva, have seeded the realisation of the large scale GRID R&D and deployment efforts during the first decade of 2000, a posteriori proven to be adequate for the LHC data processing. The upcoming upgrade of the LHC collider, called High Luminosity LHC (HL-LHC) is foreseen to require an increase in computing resources by a factor between 10x and 100x, currently expected to be beyond the scalability of the existing distributed infrastructure. Current lines of R&D are presented and discussed. With the start of big scientific endeavours with a computing complexity similar to HL-LHC (SKA, CTA, Dune, ...) they are expected to be valid for science fields outside HEP.
DOI 原文 ·
@inproceedings{paperbot5459,
title = {Current and Projected Needs for High Energy Physics Experiments (with a Particular Eye on CERN LHC)},
author = {Tommaso Boccali},
booktitle = {ASPLOS},
year = {2020},
doi = {10.1145/3373376.3380612}
}