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Aug23 [Slides]: HPC on Azure in the Financial Services Industry by Darko Mocelj

Aug23 [Slides]: HPC on Azure in the Financial Services Industry by Darko Mocelj

In this session, Darko will provide us with an overview about HPC on the Azure Cloud and provide some insights into how HPC is used by customers in the financial services industry today.

About Darko:

As part of the EMEA Global Blackbelt (GBB) Team, I will continue supporting digital transformation in Financial Services and Life Sciences. Digital Transformation can occur on various levels across the organisation. In this role I will focus on supporting cloud transformation of advanced high-performance compute workloads for both - classical compute- and ML/AI driven workloads.

My background as a technical consultant, paired with experience working in the Financial Services sector, gives me the unique opportunity to bridge the (still separate) worlds of technology and business, paired with the possibility and work with customers across EMEA on latest technology developments.

LinkedIn: https://www.linkedin.com/in/darko-mocelj/

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August 22, 2023
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  1. Classified as Microsoft Confidential
    Zürich Meetup
    Azure High Performance Computing
    Dr. Darko Mocelj
    Simplify and optimize HPC deployments with Microsoft Azure

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  2. © Copyright Microsoft Corporation. All rights reserved.
    Classified as Microsoft Confidential
    HPC in a nutshell

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  3. Classified as Microsoft Confidential
    © Microsoft Corporation
    High Performance Computing (HPC) is a platform for
    groundbreaking scientific discoveries and game-changing innovation.
    Why HPC matters
    Drives innovation across
    nearly every industry to
    solve scientific and real-life
    problems such as fluid
    dynamics, finite element
    analysis, weather modelling,
    gene research, financial risk
    and more
    Furnishes fast
    computation power and
    large-scale parallel
    processing for accurately
    processing large volumes
    of data
    Provides deep insights
    into business data for
    driving smarter simulations
    and empowering
    intelligent decision making
    Saves time and money
    by delivering faster results

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  4. Classified as Microsoft Confidential
    Materials
    Science
    Clinical Trial
    Simulation
    Rocket
    Design
    Self-driving
    Cars
    Seismic and
    Reservoir
    modelling
    Materials
    Science
    Fundamental
    Science
    Architecture
    &
    Engineering
    Entertainment
    Genomics
    Drug Design
    Environment
    Impact
    Computational
    Chemistry
    Quantum
    computing
    Cancer
    Research
    Circuit
    Design
    Risk
    Management
    Diagnostics
    Crash Testing
    Machine Learning
    Product Design &
    Safety Security/
    Encryption
    Logistics
    Data
    Science

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  5. Classified as Microsoft Confidential
    HPC
    Automotive
    Oil & Gas
    Ship engineering
    Banking
    Insurance
    Energy
    Defense &
    Aerospace
    Pharmaceutical
    Healthcare
    Life Science
    Weather forecasting
    Chemical
    engineering
    Engineering &
    construction
    Graphics &
    rendering
    Fluid
    dynamics
    Structural
    simulations
    Crash
    Simulations
    Deep
    Learning
    Genomics
    Molecular
    Modelling
    Risk
    Simulations
    High Performance Computing Solutions
    Electronic
    Design

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  6. © Copyright Microsoft Corporation. All rights reserved.
    Classified as Microsoft Confidential
    Solutions for various workloads
    Loosely coupled
    Large-scale, compute-intensive
    workloads, which can be run in
    parallel, taking advantage of the
    scale and flexibility of the cloud
    (FSI, Genomics, Physics…)
    Tightly coupled
    Solving the underlying
    mathematical model of a dynamic
    physical system in a highly iterative
    and closely coupled fashion
    (Seismic/Reservoir, Engineering,
    Weather,…..)
    Hybrid and cloud bursting
    Optimizing application
    workflows to benefit from
    both on- and off-premises
    resources
    (FSI, Engineering, Auto, …)

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  7. © Copyright Microsoft Corporation. All rights reserved.
    Classified as Microsoft Confidential
    ©Microsoft Corporation
    General-purpose VMs
    D: Standard workloads
    E: High memory
    F: Compute-bound
    Solve any HPC, AI workload—at any scale
    Small scale MPI
    (Handful of cores)
    Extreme scale MPI
    (100k+ cores)
    High memory VMs
    L: High SSD & IOPS
    M: Extreme memory
    A/B series VMs
    Burstable virtual
    machines (VMs)
    D/E/F
    Cray in Azure
    Managed custom
    bare-metal server
    Large to extreme-scale
    HPC infrastructure
    Azure network integration
    Specialized VMs
    H: High memory
    HB: Memory bandwidth
    HC: Compute-bound
    NC: GP-GPU compute
    ND: Deep learning
    NV: Graphics applications
    NP: Programmable FPGA
    L/M
    H/N
    A/B
    Infiniband network interconnected
    (up to 400GB/s)

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  8. © Copyright Microsoft Corporation. All rights reserved.
    Classified as Microsoft Confidential
    Purpose-built HPC A full range of CPU and GPU capabilities
    that help applications scale to 80K+ cores
    Fast, secure
    networking
    Fast InfiniBand inter-connects as well
    as edge-to-cloud connectivity​
    High performing
    storage
    A range of storage capabilities to support
    simple-to-complex storage needs
    Workload
    orchestration
    End-to-end workflow agility using known,
    familiar tools and processes
    Intelligence
    services
    AI, machine learning, and deep learning
    at supercomputer scale​
    Achieve more with Microsoft Azure HPC

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  9. © Copyright Microsoft Corporation. All rights reserved.
    Classified as Microsoft Confidential
    HPC FinOps – FSI Focus

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  10. © Copyright Microsoft Corporation. All rights reserved.
    Classified as Microsoft Confidential
    Fixed cost
    (on-premises)
    Variable cost
    (cloud)
    Reduce infrastructure costs
    and use capacity on demand
    Respond in an agile way to
    new business demands
    Improve operations
    Manage bursts due to
    external events quickly and
    seamlessly
    Data processing demand
    Azure HPC Cost Optimization Strategies
    Mix &
    Match

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  11. © Copyright Microsoft Corporation. All rights reserved.
    Classified as Microsoft Confidential
    Azure HPC Cost Optimization Strategies
    Mix &
    Match
    Leverage autoscaling to
    adjust consumed compute
    capacity
    Average e uest E ecution time
    um er o e uests
    s s s s seconds minutes hours
    Understand utilizations
    patterns (refer to Azure
    Advisor) and cover the base
    utilization with Reserved
    Instances
    Compute instances can be evicted
    any time – engineer for flexibility
    and portability.
    Flexibility in selecting different
    VM families
    HBv3 Dasv5 Easv3
    F- D- E-Series
    Portability* to
    different Azure
    Regions with Spot
    instances
    availability

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  12. © Copyright Microsoft Corporation. All rights reserved.
    Classified as Microsoft Confidential
    Azure Cost Optimization Strategies (FSI Focus)
    Workload
    Examples
    • Predictable demand, e.g., opening
    of new trading books
    • Increase Accuracy in risk models
    (replace approximations, increase
    Monte-Carlo paths, etc.)
    • Increased computational demand
    imposed by regulations (FRTB, XVA)
    Spot:
    • Grid workloads with mature
    cloud customers leveraging
    regional and compute flexibility
    • Dev / Test workloads
    • One-Off Regression Test
    • Try-Out of new architectures
    (GPU / CPU)
    • Full Flexibility
    • React quickly to volatile markets
    and adjust computational capacity
    accordingly

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  13. © Copyright Microsoft Corporation. All rights reserved.
    Classified as Microsoft Confidential
    HPC – Know your environmental impact

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  14. © Copyright Microsoft Corporation. All rights reserved.
    Classified as Microsoft Confidential
    Carbon-aware computing – impact on HPC operations
    https://news.microsoft.com/de-ch/2023/01/10/carbon-aware-computing-whitepaper/
    Measure carbon intensity of
    - past workloads
    - Predict future workloads and
    Minimize carbon footprint of your workloads
    Measuring the Carbon Intensity of AI in Cloud Instances (arxiv.org) https://github.com/Green-Software-Foundation/carbon-aware-sdk

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  15. © Copyright Microsoft Corporation. All rights reserved.
    Classified as Microsoft Confidential
    Azure HPC Services

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  16. © Copyright Microsoft Corporation. All rights reserved.
    Classified as Microsoft Confidential
    © Microsoft Corporation
    Azure Batch
    • HPC-as-a-Service Model
    • All HPC resources are cloud-based
    Services for HPC Workload Management – Azure Batch focus of the Demo
    Cloud-native job scheduling
    • Support for third party schedulers
    • Traditional HPC scaling methodology, but using Azure
    Azure CycleCloud
    Traditional cluster scheduler orchestration
    HPC App, Head node
    and on prem compute
    VM
    Resource
    Pool
    Azure
    CycleCloud
    HPC Application on
    client workstation
    VM Resource
    Pool
    Azure
    CycleCloud
    Head
    Node
    Hybrid / cloud bursting model Cloud native model
    HPC Application on
    client workstation
    VM Resource
    Pool
    Azure
    Batch

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  17. © Copyright Microsoft Corporation. All rights reserved.
    Classified as Microsoft Confidential
    Developer access
    SaaS platform for cloud-
    enabling workflows
    .NET, Java, Node.js, Python,
    REST
    + Common languages and
    frameworks
    Job scheduling
    Easiest way to run batch
    jobs at scale in Azure
    Detect and retry failed tasks
    Task dependencies
    Job prep and cleanup tasks
    Monitoring
    VM monitoring and auto-
    recover
    Metrics and logs available via
    Portal and API
    Azure Batch Capabilities
    Autoscale
    Native VM orchestration
    Automatically scale
    environments up as down as
    jobs require
    Choice of VMs
    Windows or Linux
    Standard or custom images
    Windows pool can use AHUB
    Can use low-priority & Spot VMs

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  18. © Copyright Microsoft Corporation. All rights reserved.
    Classified as Microsoft Confidential
    © Microsoft Corporation
    • Configure and create VMs to cater for any scale: tens to
    thousands
    • Automatically scale the number of VMs to maximize utilization
    • Easy low-priority and VM sizing, suited to your application
    Batch jobs and tasks
    • Task is a unit of execution; task = application command line
    (EXE, BAT, CMD, PS1, etc.)
    • Jobs are created and tasks are submitted to a pool. Next, tasks
    are queued and assigned to VMs
    • Any application, any execution time; run applications
    unchanged
    • Automatic detection and retry of frozen or failing tasks
    Batch pools
    Azure Batch (example of a cloud native HPC service)

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  19. © Copyright Microsoft Corporation. All rights reserved.
    Classified as Microsoft Confidential
    Example of a Azure HPC Deployment (following Microsoft Cloud Adoption Framework for Azure)
    HPC
    Microsoft Cloud Adoption Framework for Azure - Cloud Adoption Framework | Microsoft Learn What is an Azure landing zone? - Cloud Adoption Framework | Microsoft Learn
    Connectivity /
    Shared Services
    HPC Workload
    Container
    Registry Subnet
    Container
    Registry

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  20. © Copyright Microsoft Corporation. All rights reserved.
    Classified as Microsoft Confidential
    You have questions? Let’s stay in touch.

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