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site/data/cloud-edge/papers/SC-2024-digest.yaml
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site/data/cloud-edge/papers/SC-2024-digest.yaml
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venue: SC
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year: 2024
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papers:
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- title: "Pushing the Limit of Quantum Mechanical Simulation to the Raman Spectra of\
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\ a Biological System with 100 Million Atoms"
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authors:
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- Honghui Shang
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- Ying Liu 0055
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- Zhikun Wu
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- Zhenchuan Chen
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- Jinfeng Liu 0004
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- Meiyue Shao
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- Yingzhou Li
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- Bowen Kan
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- Huimin Cui
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- Xiaobing Feng 0002
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- Yunquan Zhang
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- Donald G. Truhlar
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- Hong An
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- Xiao He 0004
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- Jinlong Yang 0003
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reason: "Gordon Bell-class result scaling ab initio Raman spectroscopy to 100 million atoms, pushing quantum-chemical simulation well beyond prior limits."
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- title: "Breaking the Molecular Dynamics Timescale Barrier Using a Wafer-Scale System"
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authors:
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- Kylee Santos
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- Stan G. Moore
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- Tomas Oppelstrup
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- Amirali Sharifian
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- Ilya Sharapov
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- Aidan P. Thompson
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- Delyan Z. Kalchev
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- Danny Perez
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- Robert Schreiber
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- Scott Pakin
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- Edgar A. Leon
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- James H. Laros III
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- Michael James 0002
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- Sivasankaran Rajamanickam
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reason: "Demonstrates how a Cerebras wafer-scale engine shatters the classical MD timescale barrier, enabling microsecond-regime atomistic simulation at unprecedented speed."
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- title: "Scaling Molecular Dynamics with ab initio Accuracy to 149 Nanoseconds per\
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\ Day"
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authors:
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- Jianxiong Li
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- Boyang Li
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- Zhuoqiang Guo
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- Mingzhen Li 0001
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- Enji Li
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- Lijun Liu
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- Guojun Yuan
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- Zhan Wang 0003
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- Guangming Tan
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- Weile Jia
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reason: "Achieves 149 ns/day for large-scale deep-potential MD, combining neural-network potentials and HPC engineering to approach DFT accuracy at AIMD-like scale."
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- title: "Breaking the Million-Electron and 1 EFLOP/s Barriers: Biomolecular-Scale\
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\ Ab Initio Molecular Dynamics Using MP2 Potentials"
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authors:
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- Ryan Stocks
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- Jorge L. Galvez Vallejo
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- Fiona C. Y. Yu
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- Calum Snowdon
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- Elise Palethorpe
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- Jakub Kurzak
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- Dmytro Bykov
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- Giuseppe M. J. Barca
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reason: "First demonstration of MP2-level AIMD at the million-electron and exaFLOP/s scale, a landmark in quantum chemistry on supercomputers."
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- title: "Fire-Flyer AI-HPC: A Cost-Effective Software-Hardware Co-Design for Deep\
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\ Learning"
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authors:
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- Wei An
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- Xiao Bi
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- Guanting Chen 0002
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- Shanhuang Chen
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- Chengqi Deng
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- Honghui Ding
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- Kai Dong 0003
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- Qiushi Du
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- Wenjun Gao
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- Kang Guan
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- Jianzhong Guo
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- Yongqiang Guo
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- Zhe Fu 0009
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- Ying He 0018
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- Panpan Huang
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- Jiashi Li
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- Wenfeng Liang
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- Xiaodong Liu 0021
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- Xin Liu 0126
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- Yiyuan Liu
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- Yuxuan Liu 0019
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- Shanghao Lu
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- Xuan Lu
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- Xiaotao Nie
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- Tian Pei
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- Junjie Qiu
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- Hui Qu
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- Zehui Ren
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- Zhangli Sha
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- Xuecheng Su
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- Xiaowen Sun
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- Yixuan Tan
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- Minghui Tang
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- Shiyu Wang
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- Yaohui Wang
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- Yongji Wang
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- Ziwei Xie
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- Yiliang Xiong
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- Yanhong Xu
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- Shengfeng Ye
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- Shuiping Yu
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- Yukun Zha
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- Liyue Zhang
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- Haowei Zhang
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- Mingchuan Zhang
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- Wentao Zhang
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- Yichao Zhang 0004
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- Chenggang Zhao
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- Yao Zhao 0005
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- Shangyan Zhou
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- Shunfeng Zhou
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- Yuheng Zou
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reason: "Full system co-design report from DeepSeek's AI-HPC cluster showing 40% cost reduction vs. NVIDIA DGX through network/software optimizations, with production evidence at scale."
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- title: "MProt-DPO: Breaking the ExaFLOPS Barrier for Multimodal Protein Design Workflows\
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\ with Direct Preference Optimization"
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authors:
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- Gautham Dharuman
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- Kyle Hippe
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- Alexander Brace
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- Sam Foreman
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- Väinö Hatanpää
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- Varuni Katti Sastry
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- Huihuo Zheng
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- Logan T. Ward
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- Servesh Muralidharan
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- Archit Vasan
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- Bharat Kale
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- Carla M. Mann
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- Heng Ma
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- Yun-Hsuan Cheng
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- Yuliana Zamora
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- Shengchao Liu
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- Chaowei Xiao
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- Murali Emani
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- Tom Gibbs
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- Mahidhar Tatineni
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- Deepak Canchi
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- Jerome Mitchell
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- Koichi Yamada
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- Maria Garzaran 0001
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- Michael E. Papka
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- Ian T. Foster
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- Rick Stevens
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- Anima Anandkumar
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- Venkatram Vishwanath
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- Arvind Ramanathan
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reason: "First exaFLOP/s AI science workflow, integrating multimodal protein design with DPO alignment at supercomputing scale across Frontier and Aurora."
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- title: "ORBIT: Oak Ridge Base Foundation Model for Earth System Predictability"
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authors:
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- Xiao Wang 0004
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- Siyan Liu
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- Aristeidis Tsaris
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- Jong-Youl Choi
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- Ashwin M. Aji
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- Ming Fan
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- Wei Zhang 0261
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- Junqi Yin
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- Moetasim Ashfaq
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- Dan Lu 0001
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- Prasanna Balaprakash
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reason: "Introduces a large foundation model for Earth system prediction trained on Frontier, demonstrating how exascale AI infrastructure enables climate-scale spatiotemporal modeling."
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- title: "Democratizing AI: Open-source Scalable LLM Training on GPU-based Supercomputers"
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authors:
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- Siddharth Singh
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- Prajwal Singhania
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- Aditya K. Ranjan
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- John Kirchenbauer
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- Jonas Geiping
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- Yuxin Wen
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- Neel Jain
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- Abhimanyu Hans
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- Manli Shu
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- Aditya Tomar
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- Tom Goldstein
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- Abhinav Bhatele
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reason: "Presents an open-source framework for LLM training at thousands-of-GPU scale, systematically analyzing throughput, memory, and communication trade-offs on leadership supercomputers."
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- title: "Exploring GPU-to-GPU Communication: Insights into Supercomputer Interconnects"
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authors:
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- Daniele De Sensi
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- Lorenzo Pichetti
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- Flavio Vella
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- Tiziano De Matteis
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- Zebin Ren
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- Luigi Fusco
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- Matteo Turisini
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- Daniele Cesarini
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- Kurt Lust
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- Animesh Trivedi
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- Duncan Roweth
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- Filippo Spiga
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- Salvatore Di Girolamo
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- Torsten Hoefler
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reason: "Comprehensive empirical study of GPU-to-GPU communication across six major supercomputers, revealing bottlenecks and bandwidth characteristics relevant to all distributed AI/HPC workloads."
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- title: "Network-Offloaded Bandwidth-Optimal Broadcast and Allgather for Distributed\
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\ AI"
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authors:
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- Mikhail Khalilov
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- Salvatore Di Girolamo
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- Marcin Chrapek
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- Rami Nudelman
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- Gil Bloch
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- Torsten Hoefler
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reason: "Achieves bandwidth-optimal collective communication by offloading broadcast and allgather to SmartNICs, directly benefiting large-scale distributed deep learning."
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- title: "A Workflow Roofline Model for End-to-End Workflow Performance Analysis"
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authors:
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- Nan Ding 0006
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- Brian Austin
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- Yang Liu 0179
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- Neil Mehta
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- Steven Farrell
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- Johannes P. Blaschke
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- Leonid Oliker
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- Hai Ah Nam
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- Nicholas J. Wright
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- Samuel Williams 0001
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reason: "Extends the Roofline model to full end-to-end HPC workflows, enabling systematic performance diagnosis across compute, I/O, and data movement stages."
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- title: "GVARP: Detecting Performance Variance on Large-Scale Heterogeneous Systems"
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authors:
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- Xin You 0001
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- Zhibo Xuan
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- Hailong Yang 0002
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- Zhongzhi Luan
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- Yi Liu 0013
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- Depei Qian 0002
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reason: "Identifies and diagnoses GPU performance variance at scale on heterogeneous supercomputers, an increasingly critical issue for reproducibility and efficiency."
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- title: "A Digital Twin Framework for Liquid-cooled Supercomputers as Demonstrated\
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\ at Exascale"
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authors:
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- Wesley Brewer
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- Matthias Maiterth
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- Vineet Kumar
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- Rafal P. Wojda
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- Sedrick Bouknight
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- Jesse Hines
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- Woong Shin
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- Scott Greenwood
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- David Grant
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- Wesley Williams
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- Feiyi Wang
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reason: "First deployment of a digital twin for a liquid-cooled exascale system (Frontier), enabling real-time thermal and power management with validated empirical results."
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- title: "Doubling Graph Traversal Efficiency to 198 TeraTEPS on the Supercomputer\
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\ Fugaku"
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authors:
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- Junya Arai
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- Masahiro Nakao
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- Yuto Inoue
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- Kanto Teranishi
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- Koji Ueno
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- Keiichiro Yamamura
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- Mitsuhisa Sato
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- Katsuki Fujisawa
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reason: "Sets a new world record for graph traversal at 198 TTEPS on Fugaku through novel communication and load-balancing techniques, a landmark Graph500 result."
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- title: "MegaMmap: Blurring the Boundary Between Memory and Storage for Data-Intensive\
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\ Workloads"
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authors:
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- Luke Logan
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- Anthony Kougkas
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- Xian-He Sun
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reason: "Novel storage abstraction that transparently tiered memory and storage hierarchies, delivering near-DRAM performance for data-intensive HPC and AI workloads."
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