Towards a Digital Human Kathy Yelick EECS Department
- Slides: 8
Towards a Digital Human Kathy Yelick EECS Department U. C. Berkeley
Simulation: The Third Pillar of Science • Traditional scientific and engineering paradigm: 1) Do theory or paper design. 2) Perform experiments or build system. • Limitations: – – • Too Too difficult -- build large wind tunnels. expensive -- build a throw-away passenger jet. slow -- wait for climate or galactic evolution. dangerous -- drug design. Computational science paradigm: 3) Use high performance computer systems to simulate the phenomenon.
Economics of Large Scale Simulation • Automotive design: – Crash and aerodynamics simulation (500+ CPUs). – Savings: approx. $1 billion per company per year. • Semiconductor industry: – Device simulation and logic validation (500+ CPUs). – Savings: approx. $1 billion per company per year. • Airlines: – Logistics optimization on parallel system. – Savings: approx. $100 million per airline per year. • Securities industry: – Home mortgage investment and risk analysis. – Savings: approx. $15 billion per year. • What about health care, which is 20% of GNP? Source: David Bailey, LBNL
From Visible Human to Digital Human Building 3 D Models from images Source: John Sullivan et al, WPI Source: www. madsci. org
Heart Simulation Calculation Developed by Peskin and Mc. Queen at NYU – Done on a Cray C 90: 1 heart-beat in 100 hours – Used for evaluating artificial heart valves – Scalable parallel version done here • Implemented in a high performance Java dialect – Model also used for: • • • Inner ear Blood clotting Embryo growth Insect flight Paper making
Simulation of a Heart
Simulation and Medicine • Imagine a “digital body double” – 3 D image-based medical record – Includes diagnostic, pathologic, and other information • Used for: – Diagnosis – Less invasive surgery-by-robot – Experimental treatments Where are we today?
Digital Human Roadmap 1 organ 1 model 1 organ multiple models multiple organs organ system improved programmability 3 D model construction scalable implementations 1995 2000 2005 better algorithms 100 x effective performance 2010 coupled models
