Using Cloud HPC to Save Lives

High Performance Computing can be a force for good. Stanford researchers are using Cloud HPC to help develop better drugs.
HPC Advisory Council – Stanford Conference Stanford University, February 2018
Living Heart Project: Using High Performance Computing in the Cloud to Save Lives
Burak Yenier & Francisco Sahli

https://www.theubercloud.com/cloud-hpc

Transcript

1. Living Heart Project: Using High Performance Computing in the Cloud to Save Lives Burak Yenier & Francisco Sahli HPC Advisory Council – Stanford Conference Stanford University, February 2018
3. 2012 2013 2014 2016 Start Cloud Experiments (200 so far) 2015 HPC Container Development CAE software containers Online Marketplace (45+ stores) How did we get here? 2017 Hybrid HPC Living Heart Project Intel/UberCloud/LLNL LLNL multi-container multi-node project
4. Lessons We’ve Learned What we learnt from 200 cloud experiments and 80 case studies Security Performance Usability Software
5. Hybrid HPC Approach Right-Sized Infrastructure 1 End User in Control 3 Enables New Capabilities 4 Faster Time to Solution 2
6. Example: UberCloud ANSYS Container
7. UberCloud ANSYS Container
8. Bare Metal Performance
9. Hybrid Cloud Micro Focus Cloud Service Automation Micro Focus Operations Orchestrator HPE CMU HPC Automated Life Cycle Management Layer HPE UberCloud Stack
10. Hybrid HPC Workflow •  Service Signup •  Contact HPE and sign up for the Hybrid HPC service •  An HPE Partner creates administrator account for Cloud Service Automation and define service levels, security parameters •  User and Offer Setup •  PointNext creates user accounts for Cloud Service Automation •  PointNext and UberCloud create the various HPC software offers •  Self-Service Hybrid HPC •  Users gain access to on-demand Hybrid HPC offers through Cloud Service Automation and manage the life cycle.
11. HPE UberCloud Security Layers HTTPS/VPN Access* OS Firewall OS PKI Login Network & Storage Segmentation Dedicated Servers in High Security Data Centers Single tenant, bare metal servers (not shared between customers). These servers reside in professionally managed, highly secured data centers. Network and Storage tiers are segmented automatically. Each customer gets a private HPE CMU, a private IP range, and a private storage volume Admin access is protected by Public Key Encryption (vs passwords, which can be guessed) Servers are protected with firewalls. Only necessary ports are turned on to reduce attacks Connection to our servers are protected by strong encryption techniques such as HTTPS and VPN (HTTPS/VPN access and Disk Encryption are optional)
12. Case Study: The Living Heart Project Studying Drug-induced Arrhythmias of a Human Heart with Abaqus 2017 in the Cloud
13. The Living Heart Project • Leading cardiovascular researchers, educators, medical device developers, regulatory agencies, and practicing cardiologists • Shared mission to develop and validate highly accurate personalized digital human heart models (DHHM). • Models establish a unified foundation for cardiovascular in silico medicine • Models serve as a common technology base for education and training, medical device design, testing, clinical diagnosis and regulatory science • Rapidly translating current and future cutting-edge innovations directly into improved patient care.
14. Motivation Cisapride in the market Stockbridge et. al (2013)! New regulation introduced • Gastrointestinal purposes • 80 fatalities associated with Cisapride-induced arrhythmias •  The average cost to develop a new drug is $2.5 billion •  Only 12% of all the drugs that make it into a clinical trial will eventually get approval •  The time to market for a new drug is more than 10 years •  Many drugs, not just cardiac drugs have serious side effects on the heart, which could result in sudden cardiac death •  300,000 sudden cardiac deaths occur each year in the US, but it is unclear how many of those are caused by drugs
15. Multi-scale model to simulate drug-induced arrhythmias ~7,000,000 elements, 250,000,000 internal variables, 1,000,000 time steps
16. HPCaaS Environment and Simulations Advania / HPE / Intel / UberCloud •  Advania’s HPC as a Service (HPCaaS) hardware configuration •  Built upon HPE ProLiant servers XL230 Gen9 •  Each with 2x Intel Broadwell E5-2683 v4 with Intel OmniPath interconnect •  UberCloud HPC software containers hosting Stanford’s workflow •  Dassault SIMULIA for advanced electro- physiological modelling •  LHP model scaled well up to 240 compute cores •  42 simulations each 40 hours on 5-node (160- core) subsystem 0 5 10 15 20 25 0 50 100 150 200 250 300 0 50 100 150 200 250 300 350 400 450 500 speed up wall time [hours] number of CPUs Scalability of drug simulations using Abaqus 2017 wall time (hours) linear speed up speed up Sahli Costabal F, Yao J, Kuhl E. Predicting drug-induced arrhythmias by multiscale modeling. Int J Num Meth Biomed Eng. 2018; doi:10.1002/cnm.2964
17. Multi-scale model - baseline
18. Multi-scale model - low risk drug
19. Multi-scale model - high risk drug
20. Take Aways •  UberCloud is part of the HPE’s HPCaaS offering “Hybrid HPC” •  UberCloud Containers give us a way to solve software management problems without performance issues •  Able to manage and run the most complex engineering workflows •  Providing SaaS-like user experience and desktop level ease of use