The California Institute for Telecommunications and Information
Technology
Using Supercomputers and Gene Sequencers to Discover Your Inner
MicrobiomeKeynote TalkInternational Conference on Computational
ScienceSan Diego, CAJune 6, 2016Dr. Larry SmarrDirector, California
Institute for Telecommunications and Information TechnologyHarry E.
Gruber Professor, Dept. of Computer Science and EngineeringJacobs
School of Engineering, UCSDhttp://lsmarr.calit2.net1
1
AbstractThe human body is host to 100 trillion microorganisms,
ten times the number of DNA-bearing cells in the human body, and
these microbes contain 300 times the number of DNA genes that our
human DNA does. The microbial component of our "superorganism" is
comprised of hundreds of species with immense biodiversity. To put
a more personal face on the "patient of the future," I have been
collecting massive amounts of data from my own body over the last
seven years, which reveals detailed examples of the episodic
evolution of this coupled immune-microbial system. Collaborating
with the UC San Diego Knight Lab, we have genetically sequenced a
time series of my gut microbiome, as well as single moments from 50
patients with autoimmune disease. An elaborate software pipeline,
running on high performance computers, reveals the details of the
microbial ecology and its genetic components, in health as well as
in disease. Not only can we compare a person with a disease to a
healthy population, but we can also follow the dynamics of the
diseased patient. We can look forward to revolutionary changes in
medical practice over the next decade.
Forty Years of Computing Gravitational Waves From Colliding
Black Holes
1977L. Smarr and K. EppleyGravitational Radiation Computed from
an Axisymmetric Black Hole Collision
2016LIGO ConsortiumSpiral Black Hole Collision
40 Years
Complexity of Computing First Gut Microbiome DynamicsVersus
First Dynamics of Colliding Black HolesMy 1975 PhD
DissertationSolving Einsteins Equations of General Relativity for
Colliding Black Holes and Grav WavesCDC 6600 Megaflop/sHundreds of
Hours
Rob Knight and Smarr Gut Microbiome MapMapping From Illumina
Sequencing to Taxonomy and Gene Abundance DynamicsComet Petaflop/s
Comet Core is 40,000x CDC6600 SpeedMillion Core-Hours10,000x
Supercomputer Time
Gut Microbiome Takes ~ Billion Times the Compute Power of Early
Solutions of Dynamic General Relativity
As a Model for the Precision Medicine Initiative, I Have Tracked
My Internal Biomarkers To Understand My Bodys Dynamics
My Quarterly Blood DrawCalit2 64 Megapixel VROOM
Only One of My Blood Measurements Was Far Out of
Range--Indicating Chronic InflammationNormal Range
