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Visual Analytics, HPC, Simulations & AI Tomasz Bednarz (CSIRO Data61, UNSW Art & Design) and John Taylor (CSIRO Data61, DSTG)

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Page 1: Visual Analytics, HPC, Simulations & AI...fake examples, the energy-based function aims to evaluate the traffic efficiency of a transport network using a traffic simulation model

Visual Analytics,HPC, Simulations & AI

Tomasz Bednarz (CSIRO Data61, UNSW Art & Design)and

John Taylor (CSIRO Data61, DSTG)

Page 2: Visual Analytics, HPC, Simulations & AI...fake examples, the energy-based function aims to evaluate the traffic efficiency of a transport network using a traffic simulation model

CONFERENCE 17-20 November 2019 - EXHIBITION 18-20 November 2019 - BCEC, Brisbane, AUSTRALIASA2019.SIGGRAPH.ORG

About Tomasz• Director and Head of Visualisation at the Expanded

Perception and Interaction Centre (EPICentre), UNSW Art & Design.

• Team Leader (Visual Analytics) at the CSIRO Data61. • Adjunct Associate Professor at the Queensland University of

Technology, Applied and Computational Mathematics. • Individual Member at the Khronos Group.• SIGGRAPH Asia 2019 Conference Chair.

[email protected] | @tomaszbednarz

Page 3: Visual Analytics, HPC, Simulations & AI...fake examples, the energy-based function aims to evaluate the traffic efficiency of a transport network using a traffic simulation model

About John

• Group Leader (Computational Platforms) at the CSIRO/Data61

• Program Leader, HPC and Computational Science at the Defence Science and Technology

• Adjunct Professor, School of Computer Science, Australian National University

Page 4: Visual Analytics, HPC, Simulations & AI...fake examples, the energy-based function aims to evaluate the traffic efficiency of a transport network using a traffic simulation model
Presenter
Presentation Notes
THE SOLUTION: DATA61 network AUSTRALIA’S DIGITAL INNOVATION POWERHOUSE Data61 is the only company with sufficient scale and reach to effect the change needed in the next 3-5 years to help Australia realise its digital, data-driven potential. We have a team of 1,146 staff, which includes 419 resident PhD students (plus summer scholars, visiting researchers and interns). We work with 31 Government partners, 91 Corporate partners, and 38 University partners. We are currently working on 193 data-driven projects, and we own 172 patents. Data61 is world leading in the domain of data-centric R&D and the early stages of commercialising data-centric solutions. And we are well placed to capture 0.1% of the Global R&D spend, across public and private sector, for both individual companies and industry sectors.
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CSIROBracewell GPU Cluster

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CSIRO Bracewell GPU ClusterThe most powerful supercomputer in Australia

CSIRO Bracewell GPU Cluster6 |

• Bracewell consists of 114 PowerEdge C4130 servers hooked together with EDR InfiniBand.

• Aggregate memory across the entire system is 29 TB.

• Each server is equipped with four NVIDA P100 GPUs and two Intel Xeon 14-core CPUs.

• The GPUs alone represent over 2.4 petaflops of peak performance.

• Bracewell was installed over a period of just five days spanning the end of May and beginning of June 2017.

• The system came online in early July 2017

Page 7: Visual Analytics, HPC, Simulations & AI...fake examples, the energy-based function aims to evaluate the traffic efficiency of a transport network using a traffic simulation model

CSIRO Bracewell GPU Cluster

7 |

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Bragg Cluser Usage• During 27 April – 27 May

• 50 users running GPU jobs• 30,348 GPU jobs run

– Computational modelling– Image processing– Virtual nanoscience– Molecular modelling– Environmental modelling– Physiological modelling– Bioinformatics– Machine learning

CSIRO Bragg GPU Cluster Usage8 |

Source: CSIRO IMT Ahmed Arefin & Steve McMahon

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SNAP – Simulated Nanostructure Assembly using Proto-particles

SNAP9 |

Allows creation of user-defined nanoparticles, and subsequent Molecular Dynamics simulation to study aggregation.Nanoparticles are represented using a surface mesh, enabling researchers to define complex combinations of sizes, shape and facet combinations, each with specifically defined interactions.

GPU enabled to allow scaling to > 50,000 complex zonohedrons.

Includes tools for generating nanoparticle surface meshes and post simulation analysis.

https://research.csiro.au/mmm/snap/

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Materials Informatics & Data-driven Discovery

Contact: Monolo Per, CSIRO Data6110 |

• Analysis of High-Throughput Computation• Data representation, Machine- and Deep-Learning approaches

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• Developing HPC capability to support defence research

• Pilot system has been acquired that includes V100 GPUs

• Strong interest in application of AI and deep learning to Defence

• Full system will be in the top 50 of the TOP500 supercomputers

• Legacy codes including commercial applications, eg CFD applications will need significant work to run efficiently on GPUs.

Presentation title | Presenter name

Defence Science and Technology

11 |

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Protecting Consumers by Legal/Ethical Means

“We address this issue by proposing a formal framework that can instantiate in agents’ dialogues moral/rational criteria, such as the maximin principle and impartiality, …e.g., by John Rawls’ theory or rule utilitarianism”.

digital-legislation.net

ML/AI technologies being ethical/legal Compliant-by-Design

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EPICENTRE LABS

EPICYLINDER

DOME LAB

XR LAB

AVIE-SC

SUPER COMPUTERS

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EPICYLIDNER

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GENOMICS VIEWER

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DRUG DISCOVERY

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MASSIVE NETWORKS

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MASSIVE NETWORKS

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CREATIVE MATH

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BLOOD

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Automatic Site Selection of Cultural Venues• A cGAN outputs zones from urban data as a constraint prior to a

stochastic optimisation of site locations of cultural venues.

Tian Feng & Tomasz Bednarz21 |

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Automatic Site Selection of Cultural Venues• As cGANs can estimate appropriate zones for construction, the

search space is downsized and the optimiser quickly resolves issues like centralisation and lack of public access.

22 | Tian Feng & Tomasz Bednarz

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Transport Network Synthesis• A cGAN is modified by replacing the binary classification function of the

discriminator with an energy-based function, and outputs functional transport networks from elevations and densities.

23 | Tian Feng & Tomasz Bednarz

Page 24: Visual Analytics, HPC, Simulations & AI...fake examples, the energy-based function aims to evaluate the traffic efficiency of a transport network using a traffic simulation model

Transport Network Synthesis• Instead of merely distinguishing real and fake examples, the energy-based

function aims to evaluate the traffic efficiency of a transport network using a traffic simulation model.

24 |

Standard cGANEnergy-based cGAN

Tian Feng & Tomasz Bednarz

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Transport Network Synthesis• Synthesised examples. • Light red pixels stand for railways and dark red pixels for roads.

25 |

Synthesis Ground Truth Synthesis Ground Truth

Case 1 Case 2

Tian Feng & Tomasz Bednarz

Page 26: Visual Analytics, HPC, Simulations & AI...fake examples, the energy-based function aims to evaluate the traffic efficiency of a transport network using a traffic simulation model

Simulations - SpecificationsType Model Speed Sensor WeaponAEW&C E-7A Wedgetail 955 km/h MESA

400 kmN/A

Jet EA-18G Growler 1,960 km/h AN/APG-79 AESA150 km

AIM-9 35.4 km

AIM-120105 km

AGM-8875 km

GBAD NASAMS 100 km/h AN/MPQ-64 F175 km

AIM-12075 km

Tank M1 Abrams 60 km/h AN/TPQ-4810.2 km

M256 SBC8 km

Humvee Bushmaster 100 km/h AN/TPQ-4810.2 km

M2403.725 km

* Weapon specifications were collected from ADF websites and Wikipedia.

Modelling Complex Warfighting Symposium

Presenter
Presentation Notes
NetLogo-based simulation model takes five different weapons, respectively AEW&C (airborne early warning and control), jet (fighter), GBAD (ground based air defence), tank and Humvee. We collected specifications of main battle weapons used by ADF and thus applied them to NetLogo simulations.
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Simulations - Properties• Weapon• Type (AEW&C, GBAD, Humvee, Jet, Tank), ID (e.g., 0, 1, 2), Colour (Blue, Red)• Coordinates (longitude, latitude, altitude), Heading, Speed• Number of sub-weapons (e.g., AGM88 for jets, AIM120 for jets and GBADs)• OnStation (only for AEW&Cs and jets), Target (only for jets)• Track• Tracker & trackee• Corresponding sensor and weapon ranges• Combat Network Adjacent Matrix• Perron-Febonius Eigenvalue (PFE)1

1. J.R. Cares, An Information Age Combat Model

Modelling Complex Warfighting Symposium

Presenter
Presentation Notes
Netlogo simulation outputs weapon properties, track information, and Perron-Febonius Eigenvalue per simulation tick. Perron-Febonius Eigenvalue (PFE) is calculated from the adjacent matrix from the real-time combat network of the simulation. It depicts the operational effectiveness (OE) of the target force. Generally speaking, larger the PFE, higher the OE. Operational effectiveness (OE) means performing similar activities better than rivals perform them. Operational effectiveness includes but is not limited to efficiency. It refers to any number of practices that allow a company to better utilise its inputs by, for example, reducing defects in products or developing better products faster. In contrast, strategic positioning means performing different activities from rivals’ or performing similar activities in different ways.” 
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Sensitivity Analysis• Regression Estimation2 of PFE and Win Probability

• y1 = PFE of Blue force, y2 = PFE of Red force, y3 = Win Probability of Blue force • x1 = no. of jets, x2 = no. of GBADs, x3 = no. of tanks and Humvees

2. J.P.C. Kleijnen, Sensitivity Analysis and Related Analyses

Modelling Complex Warfighting Symposium

Presenter
Presentation Notes
By running NetLogo simulation for over 2000 times under various parameter settings, we trained a regression model to estimate PFE and Win Probablity.
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Concept Demonstrator

Modelling Complex Warfighting Symposium

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X, Y, Altitude coordinates

Number of alive turtles

Total number of turtles

Sensor and weapon range

PFE values of Blue and Red force at

runtime Win probability of Blue force at the end

of the battle at runtime

Tracks from Blue and Red jet

Simulation runtime

Modelling Complex Warfighting Symposium

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Visualisation PoC

Winner

Mean and STD of PFEs of Blue Force

Mean and STD of PFEs of Red Force

Modelling Complex Warfighting Symposium

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Modelling Complex Warfighting Symposium

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Modelling Complex Warfighting Symposium

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Saving Jaguars – VR, Gaming, GPUs, Stats

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Saving Jaguars

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sa2019.siggraph.org

CG in Australasia Tomasz Bednarz

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CONFERENCE 17-20 November 2019 - EXHIBITION 18-20 November 2019 - BCEC, Brisbane, AUSTRALIASA2019.SIGGRAPH.ORG

KangarooImage courtesy Tourism Australia

Lady Elliot Island, QueenslandImage courtesy Tourism Australia

Koala

Great Barrier Reef, Queensland

Unique Nature

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CONFERENCE 17-20 November 2019 - EXHIBITION 18-20 November 2019 - BCEC, Brisbane, AUSTRALIASA2019.SIGGRAPH.ORG

CONNECTED CITY

Enjoy taking in the Brisbane river and city sights on a free CityHopper ferry of City Loop bus.

Brisbane River

BRISBANE – AUSTRALIA’s NEW WORLD CITY

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CONFERENCE 17-20 November 2019 - EXHIBITION 18-20 November 2019 - BCEC, Brisbane, AUSTRALIASA2019.SIGGRAPH.ORG

World’s best convention centreBCEC was awarded the world’s best convention centre in 2016

Presenter
Presentation Notes
BCEC Located in idyllic riverside South Bank Parklands Precinct Won world’s best convention centre in 2016 (AIPC) Host of G20 Leaders Summit in 2014
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CONFERENCE 17-20 November 2019 - EXHIBITION 18-20 November 2019 - BCEC, Brisbane, AUSTRALIASA2019.SIGGRAPH.ORG

Presenter
Presentation Notes
Global Connections Connections to major international travel hubs in one stop
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CONFERENCE 17-20 November 2019 - EXHIBITION 18-20 November 2019 - BCEC, Brisbane, AUSTRALIASA2019.SIGGRAPH.ORG

Conference Program• Technical Papers • Courses• Art Gallery• Computer Animation Festival• Emerging Technologies• Virtual & Augmented Reality• Real-time Live!

• Technical Briefs & Posters • Birds of a Feather • Featured Sessions• SA2019 Demoscene• Studio

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www.data61.csiro.au

CSIRO Data61 & EPICentreTomasz BednarzTeam Leader / Director of Vist +61 459 855 376e [email protected] data61.csiro.auw epicentre.matters.today

CSIRO Data61 & DSTJohn TaylorGroup Leader / Program Leadert +61 400 997 446e [email protected] data61.csiro.au

Thank you