@An automated self-service multi-cloud HPC platform applied to the simulation of cardiac valve disease with machine learning

被引：0

作者：

Gentzsch, Wolfgang ^{[1
]}

Gruber, Daniel ^{[1
]}

Dabiri, Yaghoub ^{[2
]}

Guccione, Julius M. ^{[3
]}

Kassab, Ghassan S. ^{[4
]}

机构：

[1] UberCloud, Munich, Germany

[2] 3DT Holdings, San Francisco, CA USA

[3] Univ Calif San Francisco, San Francisco, CA 94143 USA

[4] Calif Med Innovat Inst, San Diego, CA USA

来源：

2021 IEEE 14TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING (CLOUD 2021) | 2021年

关键词：

HPC; high-performance cloud computing; Azure; Google Cloud; SUSE Rancher; Kubernetes; Container; UberCloud; Living Heart Project; MitraClip; Mitral Regurgitation;

D O I：

10.1109/CLOUD53861.2021.00099

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

The team's Living Heart Abaqus 2020 workflow from Dassault Systemes Simulia has been implemented in UberCloud's HPC containers on the fully automated UberCloud Platform on Google Cloud's c2 instances. The team ran more than 1,500 simulations needed to train the ML algorithm. The whole simulation process took place as a multi-cloud approach, with all computations running on Google GCP, and management, monitoring, and health-checks orchestrated from Azure Cloud performed through SUSE's Kubernetes management platform Rancher implemented in UberCloud's own Azure account.

引用

页码：744 / 746

页数：3

共 3 条

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Calyam, Prasad
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Cheng, Xiyao
Gafurov, Durbek
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Glaser, Noah
Singh, Kanu Priya
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