ANSYS and Penguin on Demand - Cloud HPC for ......Simulation result files, on the o\ her hand, are...

$: ANSYS and Penguin on Demand - Cloud HPC for ......Simulation result files, on the o\ her hand, are huge – GB’s of data – and will take hours to download. So the best practice$
1 © 2014 ANSYS, Inc. May 12, 2015 ANSYS Confidential

ANSYS and Penguin on Demand - Cloud HPC for Engineering Simulation

Barbara Hutchings ([email protected]) Director, Strategic Partnerships

Presenter

Presentation Notes

Welcome. Barb Hutchings, work out of the NH office, came to ANSYS in 2006 as part of the Fluent acquisition. Manage the team that looks out for partnerships, HPC and (starting this year) EKM product management / marketing strategy. Going to take you through our customer-facing thought leadership about trends we see in HPC deployment and related issues about data management in enterprise accounts – and our solution capability, which includes our collaboration platform EKM.

mailto:[email protected]

2 © 2014 ANSYS, Inc. May 12, 2015 ANSYS Confidential *BusinessWeek, FORTUNE

ANSYS, Inc.

FOCUSED Engineering simulation is all we do. Leading product technologies in all physics areas Largest development team focused on simulation

CAPABLE 2,600+

75

40

employees

locations

countries

TRUSTED FORTUNE 500 Industrials 96 of the top 100

ISO 9001 and NQA-1 certified

PROVEN Recognized as one of the world’s MOST INNOVATIVE AND FASTEST-GROWING COMPANIES*

INDEPENDENT Long-term financial stability

CAD agnostic

Presenter

Presentation Notes

Main Points Simulation is our only focus We are leaders in many areas of our business Our consistent leadership and independence in the industry ensure that we will be around to focus exclusively on our customer’s simulation needs for the long run.


Value Proposition - HPC for Engineering

Increase product integrity • Consider more design variants • Find the ‘optimal’ design • Ensure performance across a range of

conditions

Innovate with confidence • More detailed and accurate models • Real-world physics • From single component to system

behavior HPC high-fidelity simulations

HPC robust design methods

Presenter

Presentation Notes

We clearly observe 3 major engineering trends driving HPC innovations: The first is the need to increase product performance and product integrity in less time. This is clearly related to the need to shorten the time to market with new product introductions. It is also because of competitive pressures to differentiate products with better quality and reliability. For that matter, there is the need to evaluate more design ideas, and reach an optimal design that works across a range of operating conditions. This improves customer’s engineering process by making people more productive but also by ensuring that the right decisions are made which will then drive the project toward a successful outcome. In order to handle this increased workload, the usage of HPC is required to be able to do it within a reasonable amount of time. The second is related to increased product complexity. Needless to say but products today are increasingly instrumented with highly interconnected sub-systems that span multiple physics. Products are getting smarter. There is more electronics to increase smart product functionality. The number of functions for each product increases significantly, and each product have more and more devices. The challenge is to go from single component innovations to system innovations. HPC allows you to do bigger, more challenging complex simulations – solve the unsolveable. This will allow you to get higher-fidelity insight into how your design is going to work in the real world. The 3rd trend will be addressed at the next slide.


HPC infrastructure and data is evolving to centralized and consolidated resources, with users remote, global, and mobile

Driven by: • Scaled up demand for high performance computing (HPC)

to support higher fidelity simulation results • Operational efficiency and asset optimization, CAPEX vs OPEX (cloud) • Need for collaboration and data sharing across

geographically distributed users • Increasing focus on simulation IP protection and process traceability

Globalization And HPC Scale-up Are Driving A Paradigm Shift In The Deployment Of Simulation

HPC, Cloud & Collaboration

Presenter

Presentation Notes

Start by putting cloud in the context of a larger trend of moving from the desktop to the datacenter. ANSYS sees a fundamental shift happening in how our leading customers are deploying engineering simulation. Specifically, we are seeing a return to centralized / consolidated resources – with both hardware and data in the datacenter, and users distributed and remote. The graphic here shows how this is just the latest in a constantly evolving landscape – with the evolution today away from local departmental resources, “back” to supercomputing in the datacenter, which we now call “cloud” and some still call “grid”. This shift to centralization is driven by a few key factors: More demand for HPC, impossible to build the scale users want in every office where users are located. Better to centralize, for more efficient operations (on the IT side) and in order to effectively share resources (HW and licenses). For some organizations, there is also a push to move the IT costs to OPEX (cloud) vs. CAPEX. Also better to centralize, in order to support global engineering objectives. Centralizing data, in particular, is key to effective collaboration and re-use of IP and finally centralization is the ‘answer’ for more effective IP protection (access control, backup, disaster recovery) and visibility of how/where simulation is being used (process traceability).


Best Practice 1 Don’t Move the Data (More Than You Have To)

Simulation Data – Cloud Best Practice

Customer Premise Small Input Files

“Huge” Output Files

• Upload of CAD file (~20MB) takes less than 1 min. over a typical connection • Download of result files (each ~2GB typical) may take too long

o Several hours over a typical connection (~4 hours for 20GB at 20Mbps) • Cloud backend should enable secure WIP storage and backup

o Even if eventual archive is on-premise

Presenter

Presentation Notes

So today, we’d like to focus on a handful of specific key practices and share our emerging understanding of ‘best practice’ for use of ANSYS on an external cloud backend. The first practice relates to data storage – and the idea of minimizing the transfer of data back and forth between the cloud backend and the end-user. Clearly, some data motion will be needed: the end-user may be doing CAD on the desktop and will need to move that CAD file up to the simulation center on the cloud. Luckily, these input files are relatively small – measured in MBs, and typically less than a minute to transfer. Simulation result files, on the other hand, are huge – GB’s of data – and will take hours to download. So the best practice is not to download the data – make sure that the cloud is both a compute and storage solution, at least for WIP data. That means you need data security on the cloud (we’ll come back to that) and you need backup/disaster recovery for that data. Download speed calculator http://www.numion.com/calculators/time.html Global broadband data (http://www.netindex.com/download/2,1/United-States/): Avg. download speed: ~20Mbps Avg. upload speed ~10Mbps


Best Practice 2 Graphics & GUI Capability for End-to-End Simulation

Remote Graphics & GUI – Cloud Best Practice

End-User Machine

Remote Graphics High Memory Graphics Server (up to 256GB)

High Memory Application Server

Remote Rendering Graphics Server

• Application-Tested Accelerated OpenGL Remote Graphics • Full remote desktop, with file edit access o Logs, journals, user add-ins o Report apps and video editing

• Low end-to-end network latency o Lower the better (target 100msec or less, but depends)

• Graphics-capable hardware – with sufficient memory!

Presenter

Presentation Notes

The second practice follows from the idea of leaving your data on the cloud: End-users will need to perform full end-to-end simulation on the cloud, meaning not just batch solves but also interactive GUI processes and graphical post-processing. Most simulation workloads involve 3D graphics, so you will need a remote graphics software tool with server-side acceleration and good performance over the network – and reasonable network latency. And you’ll want full remote desktop access to that server (not just the application in a window) so that you can edit and manage files, maybe compile add-in routines, etc. All this implies a graphics server on the cloud, which needs sufficient memory to load and display large simulation models. One of the issues we have seen is that not all cloud backends support this, and the slide (build) is showing a solution architecture that we have been demonstrating in conjunction with our partners Nice and AWS – using a high memory server instance to run the application, with Nice DCV handling graphics via remote rendering on a lower memory graphics server. We’ve found that this can be a robust and economical way to enable large model graphics on the cloud, without large investment in multiple high memory graphics servers.


Scyld Cloud Workstation


Customer Premise

ANSYS License Manager

#2

ANSYS License Manager #1 (Lease & Paid-Up Licenses)

Cloud

Reported Use to ANSYS $/Hour Pay-Per-Use

Pre-Paid

Elastic capacity license file

Job Execution On Premise

Job Execution On Cloud

Best Practice 3 Flexible Licensing Architecture

• Re-Use On-Premise licenses o Easy if Site-to-Site VPN in place o Point-to-point firewall rules can also be used

• And/or add a license manager on the cloud • Traditional lease or elastic capacity

License Checkout

Presenter

Presentation Notes

Add (verbally) that either license manager instance could be on-premise or on-STC (location doesn’t really matter). Add (verbally) that the Pay-Per-Use could be pre-paid or (possibly) post-paid. ALSO that this is a premium model – like on-demand hardware vs. reserved instances. ALSO that it might be a subset of products, to simplify reporting and license configuration.


As an ANSYS Cloud Host, POD gets technical and business support from ANSYS • ANSYS licenses for dev/test/support; benchmarking kits • Installation, licensing, and deployment support from

ANSYS • Side-by-side sales engagement

Customers get: • Fully managed HPC, from POD • Application support, from ANSYS • Support for systems issues, from POD (and ANSYS) • Full licensing flexibility (with BYOL business model)

POD is an ANSYS Cloud Hosting Partner


Using Penguin-on-Demand Medimmune Case Study

Medimmune is a leader in biopharmaceutical product development

Challenge • Expand the use of simulation in order to deliver consistent, reliable products

POD Solution • Rapid deployment to support a new project • CFD simulations on 128 core, leading to 4-5 hour turnaround • Throughput enabling parametric sweep of the design space

Result

.

Penguin on Demand gave Medimmune the agility to start up and execute a challenging new product, leading to insights that will contribute to product quality and consistency.

ANSYS and Penguin on Demand - Cloud HPC for ......Simulation result files, on the o\ her hand, are...

Documents

Transcript of ANSYS and Penguin on Demand - Cloud HPC for ......Simulation result files, on the o\ her hand, are...