EAGER: An Exaflop-hour simulation in AWS to advance Multi-messenger Astrophysics with IceCube
EAGER: An Exaflop-hour simulation in AWS to advance Multi-messenger Astrophysics with IceCube
批准号:
1941481
负责人:
Frank Wuerthwein
金额:
$29.5万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-10-01 至 2021-09-30
中文摘要
点击翻译按钮获取中文摘要
英文摘要
Exascale High Throughput Computing (HTC) demonstrates burst capability to advance multi-messenger astrophysics (MMA) with the IceCube detector. At peak, the equivalent of 1.2 Exaflops of 32 bit floating-point compute power is used. This is equivalent to approximately 3 times the scale of the #1 in the Top500 Supercomputer listing as of June 2019. In one hour, roughly 125 terabytes of input data is used to produce 250 terabytes of simulated data that is stored at the University of Wisconsin, Madison to be used to advance IceCube science. This data amounts to about 5% of the annual simulation data produced by the IceCube collaboration in 2018.This demonstration tests and evaluates the ability of HTC-focused applications to effectively utilize availability bursts of Exascale-class resources to produce scientifically valuable output and explores the first 32-bit floating point Exaflop science application. The application concerns IceCube simulations of photon propagation through the ice at its South Pole detector. IceCube is the pre-eminent neutrino experiment for the detection of cosmic neutrinos, and thus an essential part of the MMA program listed among the NSF's 10 Big Ideas.The simulation capacity of the IceCube collaboration is significantly enhanced by efficiently harnessing the power of short-notice Exascale processing capacity at leadership class High Performance Computing systems and commercial clouds. Investigating these capabilities is important to facilitate time-critical follow-up studies in MMA, as well as increasing the overall annual capacity in aggregate by exploiting opportunities for short bursts.The demonstration is powered primarily by Amazon Web Services (AWS) and takes place in the Fall of 2019 during the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC19) in Denver, Colorado. It is a collaboration between the IceCube Maintenance & Operations program and a diverse set of Cyberinfrastructure projects, including the Pacific Research Platform, the Open Science Grid, and HTCondor. By further collaborating with Internet2 and AWS, the experimental project also explores more generally, large high-bandwidth data flows in and out of AWS. The outcomes of this project will thus have broad applicability across a wide range of domains sciences, and scales, ranging from small colleges to national and international scale facilities.This project is supported by the Office of Advanced Cyberinfrastructure in the Directorate for Computer & Information Science & Engineering and the Division of Physics in the Directorate of Mathematical and Physical Sciences.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(4)
专著(0)
科研奖励(0)
会议论文
登录
查看更多内容
Demonstrating 100 Gbps in and out of the public Clouds
演示公有云内外的 100 Gbps
DOI:
10.1145/3311790.3399612
发表时间:
2020
期刊:
Practice and Experience in Advanced Research Computing (PEARC20
影响因子:
--
作者:
[Sfiligoi, Igor]
通讯作者:
Sfiligoi, Igor
Pushing the Cloud Limits in Support of IceCube Science
突破云极限以支持 IceCube Science
DOI:
10.1109/mic.2020.3045209
发表时间:
2021
期刊:
IEEE Internet Computing
影响因子:
3.2
作者:
[Sfiligoi, Igor, Schultz, David, Wurthwein, Frank, Riedel, Benedikt, Deelman, Ewa]
通讯作者:
Deelman, Ewa
DOI:
10.1007/978-3-030-50743-5_2
发表时间:
2020-05-22
期刊:
High Performance Computing
影响因子:
--
作者:
[Sfiligoi I, Würthwein F, Riedel B, Schultz D]
通讯作者:
Schultz D
Demonstrating a Pre-Exascale, Cost-Effective Multi-Cloud Environment for Scientific Computing: Producing a fp32 ExaFLOP hour worth of IceCube simulation data in a single workday
演示用于科学计算的前百亿亿次规模、经济高效的多云环境:在单个工作日内生成 fp32 ExaFLOP 小时的 IceCube 模拟数据
DOI:
10.1145/3311790.3396625
发表时间:
2020
期刊:
PEARC '20: Practice and Experience in Advanced Research Computing
影响因子:
--
作者:
[Sfiligoi, Igor, Schultz, David, Riedel, Benedikt, Wuerthwein, Frank, Barnet, Steve, Brik, Vladimir]
通讯作者:
Brik, Vladimir
Category II: A Prototype National Research Platform
-
批准号:2112167
-
项目类别:Cooperative Agreement
-
资助金额:$500.0万
-
财政年份:2021
-
负责人:Frank Wuerthwein
-
依托单位:
Collaborative Research: Data Infrastructure for Open Science in Support of LIGO and IceCube
-
批准号:1841530
-
项目类别:Standard Grant
-
资助金额:$69.61万
-
财政年份:2018
-
负责人:Frank Wuerthwein
-
依托单位:
Collaborative Research: Any Data, Anytime, Anywhere
-
批准号:1104549
-
项目类别:Standard Grant
-
资助金额:$81.44万
-
财政年份:2011
-
负责人:Frank Wuerthwein
-
依托单位:
海外基金