© 2012 IBM Corporation

IBM Big Data Projectswith Ontario Universities

July 16, 2014

1

2

Institution #Projects

McMaster University 4 (all Agile)

University of Ottawa 3 (1 Agile)

Queen’s University 4 (0 Agile)

University of Ontario 3 (0 Agile)

University of Toronto 12 (3 Agile)

University of Waterloo 6 (1 Agile)

Western University (1 IBM lead Mining) 9 (4 Agile)

Carleton University (IBM Lead) 1 (0 Agile)

TOTAL 42

Focus Area #Project

Health 20

Energy (* new Mining) 8

Water 5

Cities 4

Agile 5 + 6 multi = 13

Platform #Project

Blue Gene/Q 15

Cloud 13

Agile 13

Multi-Platform 6 (1 non SOSCIP)

Phase Focus #Project SME

Phase1 FastStart 7 30%

Phase2 Academic-led 24 70%

Phase3 Industry and Academic-led

11 90%

* 2 projects deferred pending Sustainability plan + resources** 1 project on hold pending UofT/UHN/IBM IP agreement

Status: 25 running/initiated, 13 scheduled 3Q, 2 Q114, 2 TBD*

NANOPHOTONIC DEVICES FOR EARLY DISEASE DETECTIONCreate a computational model of nanophotonic devices that could improve the early detection of disease at a cellular level.PANDEMIC MODELING, PREDICTION, AND CONTROLBased on citizen behaviors and local GTA health care policies, create models to help decision makers control a pandemic outbreak of a contagious disease.INFECTIOUS DISEASE MODELING SOFTWAREDevelop a software package that enables easier mathematical modeling of certain factors of infectious disease, such as infection rates, incubation periods, and initial conditions for a new infection.COMMON SIGNATURES IN LUNG DISEASEDesign an algorithm to identify common signatures in lung cancer patients, advancing diagnosis, prognosis and treatment capabilities. INTEGRATED RADIOLOGY AND PATHOLOGY Leverage cloud-based smart platform solutions to integrate medical imaging from radiology, pathology, and oncology departments, providing a patient-centred, holistic approach to the diagnosis and treatment of cancer.DETECTING RADIATION EXPOSUREDevelop software that will enable rapid, accurate detection of radiation exposure for mass numbers of people.REAL TIME ANALYSIS OF HUMAN BRAIN NETWORKSApply stream analytics to functional MRI data to analyze brain activity in near real time to improve patient experience and reduce medical costs and timelines.ARTEMIS EXPANSIONBuild a cloud-based service using streaming analytics to predict the health status of individuals, particularly premature children. Bring sophistication of urban teaching hospitals to remote communities and extend early detection of infections to adult ICU.BUILDING AND CERTIFYING SAFE AND SECURE INSULIN PUMPSBuild a toolkit for software certification. First application will target medical devices.DATA PRIVACY AND SHARING MEDICAL DATADevelop new healthcare privacy and security framework to address both patient care and medical studiesANALYTICS AS A SERVICEDevelop new toolkit to support ultra large scale services for big data analytics. Initial target is health applications but toolkit will be applicable to other domains.

HEA

LTH

3

RENEWABLE SOLAR ENERGYDevelop a new, low-cost, paint-on, solar cell-based renewable energy.

COMBUSTION SYSTEM SIMULATIONDevelop a high-performance computing algorithm that simulates combustion systems to improve the design of gas-turbine engines in transportation and power-generation applications.

CREATING SUSTAINABLE ENERGY FROM ARTIFICIAL PHOTOSYNTHESIS Examine artificial photosynthesis and water-splitting at a nanoscale level to better understand the chemical and physical properties of these processes. This level of understanding will contribute to the development of clean, renewable, and sustainable sources of energy in Ontario.

SMART METER DATA ANALYTICSDevelop software for small/medium enterprises which will help to identify smart ways to reduce energy consumption.

WIND-FORECASTING MODELDevelop a wind-forecasting model to enable renewable wind energy generation in Ontario to be more proactive and operationally cost effective.

A MODEL FOR SHORT AND LONG TERM ENERGY PLANNINGImprove models for power distribution reliability building on IBM’s weather forecast model. EN

ERG

Y

4

REAL-TIME, REMOTE SENSOR, WATER SHED DATA ANALYSIS Design communications software that will transmit real-time data from remote sensors in the Grand River Watershed. The data will improve both the understanding of water behavior, as well as water management tactics.

CLIMATE CHANGE IMPACT ON WATER RESOURCES Develop a 3D hydrological model that represents the impact of the climate-change forecast on the quality and quantity of the surface and subsurface water resources in the Grand River Watershed.

WATER QUALITY MONITORINGCreate a low-cost, easy-to-use, real-time sensor system for water quality monitoring, including biological and chemical contamination detection.

MISSION CRITICAL INFRASTRUCTURE MONITORINGCreate disaster management response systems which have a clear understanding of interdependencies of all aspects of risk mitigation, disasterpreparedness and post disaster planning. Develop reliable monitoring systems for the real-time detection of mission-critical infrastructure failures.

REAL-TIME DRINKING WATER MANAGEMENT/MONITORINGCreate a real-time water data processing system to aid in water contamination alerts, ensuring enough water is supplied to the public, and to control residential water use.

WAT

ER

5

SMART URBAN SYSTEM DESIGN

Research into transportation and urban activity systems in the Greater Toronto Area (GTA), improving the decision-making ability of urban planning designers in Ontario.

AUTOMATIC DETECTION OF MAN-MADE OBJECTS FROM IMAGE DATA

Develop a cloud-based tool that will automatically identify features (buildings, roads, forest types, etc.) from high-resolution image data for use in areas like urban planning or forest management.

CLIMATE MODEL

Create new detailed climate projection and drive hydrological models to assess impact of global warming using dynamic downscaling specific to the Grand River watershed.

CITI

ES

6

MAKING HIGH-PERFORMANCE COMPUTING ACCESSIBLE Design a program that enables software application developers, with minimal hardware skills, to leverage agile, high-performance computing, resulting in faster development cycles.

ASTRONOMICAL DATA MINING Leverage agile, high-performance computing to boost the processing capability of data obtained from Ontario’s world-leading astronomical radio telescope at the Algonquin Radio Observatory.

REAL-TIME NETWORK CAPACITY ADJUSTMENTLeverage agile computing to develop an accelerated ray-tracing algorithm, allowing network operators to adjust network capacity in real-time based on changes in network state and improving quality of service.

IMPROVING SMART GRID DATA EXCHANGEImprove the security and efficiency of handling massive data exchanges in smart grid infrastructures through hardware accelerated computing.

DESIGN PATTERNS FOR HETEROGENEOUS COMPUTINGDevelop a set of design patterns that will make high performance computing more accessible to software developers creating complex applications.

HARDWARE ACCELERATION THROUGH AGILE COMPUTINGUsing agile computing, develop a hardware-based system that will accelerate the ability of the IT industry to solve optimization problems, such as routing and scheduling of airplanes and urban transportation systems. AG

ILE

7

PATIENT-CENTRED UNIVERSAL HEALTH RECORDS

Develop a cloud-based solution to aggregate, analyze, and standardize patient health records.

WEATHER PROJECTIONS FOR SMART CITIES

Integrate high resolution weather projections with cities infrastructure (buildings, transportation networks, etc.) to improve their design, sustainability, and resiliency.

PREDICTING LEUKEMIA INHIBITORS

Develop a tool that simulates molecular behaviour to accelerate the selection of drugs for the treatment of leukemia.SM

E Le

ad

8

IN SILICO PROTEIN SYNTHESIZER

Perform genetic analysis to sequence proteins that aid in drug design. This will help to better understand diseases and treatments.

ANALYZING GEOSPATIAL PATTERNS IN THE CLOUD: APPLICATION TO MINERAL EXPLORATION AND MINING IN CANADA

Aggregate and perform statistical analysis, data-mining, scoring and ranking, using Monte Carlo methods and Bayesian statistics to identify areas of promise with requiring extraction of new core samples.

IBM

Lea

d

9

CYTOGENETIC DECISION-SUPPORT TOOL

Design and implement a decision-support tool to assist cytogeneticists in the selection of appropriate probes to improve speed and accuracy of DNA microarray testing for the diagnosis and treatment of chromosome/cell related disorders.

PHOTODYNAMIC CANCER THERAPY

Develop new, minimally invasive, photodynamic therapy for the treatment of head and neck cancers.

MISSION-CRITICAL INFRASTRUCTURE MONITORING

Develop real-time detection of mission critical infrastructure failures, such as loss of energy supply, water contamination, dam failure, or the collapse of structures such as buildings or bridges.

NEW

PR

OJE

CTS

PREDICTIVE CARDIOTOXICITY USING MACHINE LEARNED MODELING FROM SIMPLE BIOLOGICAL INPUTSUse techniques that identify novel ECG patterns via advanced mathematical techniques that assess dynamicalterations in cardiac conduction and repolarization along with alterations in vascular and autonomic function.

CHARACTERIZATION OF PROTEIN-DRUG INTERACTION NETWORKS FOR RARE-DISEASE REPURPOSING (FDA)Structural alignment of test sets of millions of compounds, molecular dynamics simulations of involving tens or hundreds of proteins from the FDA’s Rare Disease Repurposing Database.

QUANTIFIED PSYCHIATRY: TIME SERIES PREDICTIVE MODELING IN MENTAL HEALTH DIAGNOSTICS

Perform analysis of pharmaceutical clinical trial data for antidepressant medications and gather behavioural markers to segment psychopathology. Analysis will generate insight into patterns underlying patient behaviour, and understand placebo response in the context of these trials.

NEW

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© 2012 IBM Corporation

FPGAs and Big Data

Direct data injest Network Storage

Dimensions of Parallelism

Enabling Technologies

Lime

POWER8 CAPI

I/O attachment, orCoherent attachment via CAPI

to Host CPUMultiple pipelines

PipelineParallelism

Multiple kernels/functions

CPU GPU FPGA0

50100150200250300350400

Power Consumption

Po

we

r (W

)

CPU GPU FPGA0

1000

2000

3000

4000

5000

6000

7000

0510152025303540

Floating Point Performance

(single-precision fused-multiple-add)

GF

LO

PS

GF

LO

PS

/W~2×

Performance

© 2012 IBM Corporation

Real-time fMRI Brain Analytics

The problem: brain activity scans take days to analyze

The solution: a real-time analytics engine

Mark Daley, Western University (London, ON)

FPGA replaces 48 x86 cores and implements superior motion correction

algorithm

IBM InfoSphere Streams on Power 7 constructs graphs of brain networks 40x

faster than single process on x86

Results in seconds instead of days!

Graph updates every 0.6-0.8s

Planning replacement of CPU-based graph analytics with Power 8 and CAPI-attached FPGA accelerator