The Living Heart Project utilizes high-performance computing (HPC) in the cloud to create accurate digital human heart models for cardiovascular medicine. It leverages a hybrid HPC approach to enable efficient drug-induced arrhythmia simulations, improving drug development and patient care while ensuring data security through dedicated infrastructure. The project has involved collaborations among leading researchers and organizations to translate innovative technologies directly into clinical applications.

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
PerformanceUsability
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 CMUHPC 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
speedup
walltime[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