With the ability to reduce “time to insight” and accelerate research breakthroughs by providing immense computational power, high performance computing is becoming increasingly important in the marketplace. Meanwhile, cognitive technology has risen to prominence, similarly accelerating new insight, but through a very different approach - by analyzing previously ignored unstructured data, which accounts for 80% of new data created today. By combining the powerful computing power of the HPC market, along with the machine learning, natural language processing, and even computer vision techniques found within cognitive technology, there is a huge opportunity to accelerate breakthroughs and enable better decision making than ever before. Watch the replay of the webinar: https://www.youtube.com/watch?v=Hxgieboj3W0

1. High Performance Computing and the
Opportunity with Cognitive
Technology
IBM Watson

2. Sridhar Sudarsan
CTO and Chief Architect
IBM Watson Ecosystem
Our Expert:

3. Agenda:
• What is cognitive?
• How cognitive technology is being used today
• Cognitive in HPC
• How you can get started

4. Computing Eras
A new era of cognitive computing will forever change the way people interact with
computing systems. Cognitive systems will help people extend their expertise
across any domain of knowledge and make complex decisions involving
extraordinary volumes of information.

5. What is Cognitive Technology?
Understands
and converses
in natural
language
Weighs evidence
to provide “best”
possible
outcome
Interacts and
maintains context
Adapts to new
domains by
reasoning
Applies statistical
learning
techniques as
opposed to rule
based techniques
Learns by
experience or
via instructions
by humans

6. Questions, Answers and Natural Language Processing
• Watson used deep Natural Language
Processing in Jeopardy! to answer questions
and beat the Grand Masters of the game
– Deep analysis of language
– Hypothesis generation
– Measuring inferences to candidate
answers
– Operating on a massive scale
– 200 Million pages of literature
– Working at incredible speed
– responding in ~ 3 seconds

7. In healthcare and many other industries, the input
(question) is even more complex
Evidence
Profile
for
UTI
Diagnosis
A 58-­year-­old woman presented to her primary care physician after several days of dizziness, anorexia, dry mouth, increased thirst, and frequent
urination. She had also had a fever and reported that food would “get stuck” when she was swallowing. She reported no pain in her abdomen,
back, or flank and no cough, shortness of breath, diarrhea, or dysuria. Her family history included oral and bladder cancer in her mother, Graves'
disease in two sisters, hemochromatosis in one sister, and idiopathic thrombocytopenic purpura in one sister. Her history was notable for
cutaneous lupus, hyperlipidemia, osteoporosis, frequent urinary tract infections, three uncomplicated cesarean sections, a left oophorectomy for a
benign cyst, and primary hypothyroidism, which had been diagnosed a year earlier. Her medications were levothyroxine, hydroxychloroquine,
pravastatin, and alendronate. A urine dipstick was positive for leukocyte esterase and nitrites. The patient was given a prescription for
ciprofloxacin for a urinary tract infection and was advised to drink plenty of fluids. On a follow-­up visit with her physician 3 days later, her fever had
resolved, but she reported continued weakness and dizziness despite drinking a lot of fluids. She felt better when lying down. Her supine blood
pressure was 120/80 mm Hg, and her pulse was 88 beats per minute;; on standing, her systolic blood pressure was 84 mm Hg, and her pulse was
92 beats per minute. A urine specimen obtained at her initial presentation had been cultured and grew more than 100,000 colonies of Escherichia
coli, which is sensitive to ciprofloxacin.

8. Capabilities of a Cognitive System

9. Watson as a Cognitive Platform

10. Watson Ecosystem Partners
A leader in the deployment of Natural Language
Generation technologies in data analytics and
information delivery allows you to ask free form
questions around the regulations that are relevant
per the report on compliance legislation.
A company that helps healthcare professionals offers
physicians a patient-facing clinical decision-making
mobile platform that physicians can use to make
contextual queries against vast volumes of medical
research.
A software solution that spans a number of key
workflows and tasks to help find, engage and
collaborate with both external innovators and
colleagues to better understand global science and
technology resources.
Cognitive Security Insights (CSI) is a cloud based
solution that delivers an incredibly powerful cyber
threat assessment and research platform by assessing
the threat and providing context-based research and
remediation options.

11. Ø The world is awash in data – sensor, modeling, social
Ø The vast majority of data is collected but unanalyzed
Ø Organizations are experiencing data challenges as the focus
on insight
Oil
and
Gas
•15
PBs
of
survey
data
•10+
months
to
process
new
survey
data
once
acquired
•100x
compute
needed
for
deep
water
imaging
•Network
and
high
bandwidth
storage
intensive
•Long
term
storage
needs
•Multi-­‐TB
datasets
for
visualization
•1
TB
per
field
per
day,
2
TB
per
rig
per
day
Genomics
and
Life
Sciences
• NGS
data
doubling
every
5
months
• Some
leading
institutions
@
>100PB
in
1-­‐2
years
• Projects
increasingly
National
scale
(UK,
China,
UAE,
US)
• Large
cluster,
Large
SMP
needs
• High
performance
file
system
and
scalable
storage
• Multi-­‐stage
workflow
process
for
personalized
treatment
The HPC Industry
Opportunities
Challenges
Ø How do I bring new approaches to computation?
Ø How do I gain more insight from the computational work I
am running?
Examples

12. Disruptive Trends in the O&G industry
Data recognized as key to drive value. New methods required for new unconventional
exploration, seismic technologies and data overload
80,000 sensors
In a single modern platform
94% of production in 1,500 oil Fields (65,000+)
1-­2 TB/day One major O&G company only
300,000
Publications / year
American Petroleum Institute, SPE,
AAPG, SGE, etc
Drilling companies report collecting
2TB / day
Only 5% gets to the shore
95% is not used
Data overload and
reliance on traditional,
non-­scalable methods
Workforce transition and
shortage of skills
IoT, data-­ and
computationally intensive
technologies
Declining giant fields,
slow reserve replacement
rates
Challenges and risks in
new E&P frontiers

13. Cognitive computing re-­defines workflows across the whole O&G value chain
New ventures &
appraisals
Exploration Field development Production and
Operations
Asset
Optimization
Bringing together real-­
time, unstructured data
from a myriad of
sources to assess
geopolitical risks, local
and economic trends,
past production history
for dynamic decision-­
making environments
Transform seismic
interpretation workflow
by automated
recognition of
prospects using
cognitive visual
analytics contextual
knowledge of drilling
sites
Benchmark with
respect to large-­scale
historical data from
similar projects,
lessons learned from
unstructured data,
reports from past
projects
Assimilation of large
amount of continuous
spatial-­temporal data
using machine learnt
model blending of
physical and data-­
driven models
Analytics
augmentation
leveraging industrial
knowledge graphs for
classes of equipment,
augmented reality to
reduce unplanned
downtime
Portfolio simulations,
(static) correlations /
clusters
Drilling cost/efficiency
Equipment utilization
well placement
Analyze Project Data
Time, Cost, Quality, HSE
predict based on history
Maximize production
efficiency, min operation
costs, well productivity,
outlier warnings
Asset monitoring /
management, fault
identification, failure
prediction
Traditional analytics
New cognitive-­enabled end-­to-­end transformations

14. Cognitive Computing for Life Sciences: tranSMART
Challenge: Translational medicine requires sequencing data ingress, data analysis, and secondary
analysis. It’s not just the processing algorithm.
Solution: Infrastructure biased overwhelmingly towards storage. Elastic Storage Server, Spectrum
Scale, Mellanox Fabric, and Power Systems S822LC.
Results: Clients have runtime expectations of hours for this workflow. IBM delivers
data ingress in <4 min; data analysis in ~20 min. Practitioners focus on achieving insight.
Planned Cognitive Enhancement: Watson Text Analytics

15. What will you do with Watson?
Start building for free on the Watson Developer Cloud:
ibm.biz/watson_services

16. Questions?
Sridhar Sudarsan
CTO and Chief Architect
IBM Watson Ecosystem
Sumit Gupta
VP and HPC Business Line
Executive, OpenPOWER

17. Join our Watson Developers Labs at the
GTC2016/OpenPOWER Summit on April 7th in San Jose, CA:
ibm.biz/WatsonLabGTC2016
Join us at our next event!