v2 AV4417 RenderingOnTheCloudClassHandout R11

8/13/2019 v2 AV4417 RenderingOnTheCloudClassHandout R11

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Rendering on the Cloud

Ken Pimentel, Director, Media & Entertainment Division, AutodeskShane Griffith, Product Manager, Media & Entertainment Division, Autodesk

AV4417

Learning ObjectivesAt the end of this class, you will be able to:

o Basic understanding of what Autodesk offers for cloud-based rendering

o Economic principles behind cloud-based rendering

o Technology behind cloud-based rendering

o Glimpse of some of Autodesk's research in this area

About the Speakeren !imentel is the director of "isual communication solutions in the Autodesk #edia $ Entertainment %i"ision& e

is responsible for guiding Autodesk( )ds #a*( and other solutions& en holds a B+ in electrical and computer

engineering from the ni"ersity of alifornia at %a"is, and is the co-author of the book, ./irtual 0eality: Through the

1ew 2ooking Glass3&

/isit en4s blog at: http:55area&autodesk&com5ken,Email: ken&pimentel6autodesk&com

+hane Griffith is a !roduct #anager with Autodesk, currently responsible for Autodesk )ds #a* and )ds #a*

%esign& !rior to becoming !# for )ds #a* +hane worked se"eral years within the Autodesk sales team as a

Technical +pecialist for )ds #a* and prior to that he worked in the Games industry as a Technical Art %irector&

/isit +hane4s blog at: http:55area&autodesk&com5shane,Email: shane&griffith6autodesk&com
http://area.autodesk.com/kenhttp://area.autodesk.com/kenmailto:[email protected]://area.autodesk.com/shanehttp://area.autodesk.com/shanemailto:[email protected]:[email protected]://area.autodesk.com/kenmailto:[email protected]://area.autodesk.com/shanemailto:[email protected]


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Rendering on the cloud

Contents2earning 7b8ecti"es&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&& 9

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ontents&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&

;ntroduction&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&& s often the added comple*ity of how to get rendering done on

time and in a cost-effecti"e way& %eciding how much to in"est in time and resources to get a better and

faster rendering solution can be a difficult process for those not familiar with all the "arious techniCues

a"ailable today&

;n this class will discuss the "arious pros and cons to the current distributed rendering solutions pro"ided

with Autodesk software, and e*plore new research for how that could change in the future&

Local Rendering Solutions0endering locally is the most common configuration for rendering& sing a single-workstation a user

simply selects the desired render options and e*ecutes the render action& ;n addition to this basic

rendering workflow there are new interacti"e options in )ds #a* to pre"iew the rendering results as the

artist works on scene setup&

Integrated Renderers

)ds #a* ships with fi"e methods of rendering images or animations:

Default Scanline Renderer

The %efault +canline 0enderer is a "ersatile renderer that renders the scene as a series ofscanlines that are generated from top to bottom& There are limited photorealistic options for

creating high Cuality renderings, but it can be efficient for rendering non-photo real imagery or

matte passes& This is a general-purpose renderer that reCuires you to ha"e a basic understanding

how the interaction between lights, materials and ob8ects works& ;t allows you to .cheat3 in order

to speed up the rendering process&

mental ray Renderer

The 1/;%;A mental ray ( renderer from mental images ( is a general-purpose renderer that can

generate physically correct simulations of lighting effects, including ray-traced reflections and refractions,

caustics, and global illumination&

ompared to the default )ds #a* scanline renderer, the mental ray renderer relie"es you of the need tosimulate comple* lighting effects Lby handL or by generating a radiosity solution& The mental ray renderer

is optimied to use multiple processors and to take ad"antage of incremental changes for efficient

rendering of animations&

nlike the default )ds #a* renderer, which renders scanlines from the top of the image downward, the

mental ray renderer renders rectangular blocks called buckets& Mith distributed bucket rendering, multiple

networked systems can all work on a mental ray rendering of a single frame& Each networked system

processes a bucket, sends it to the master computer and is then assigned another bucket to render&


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Mhile distributed bucket rendering can be used for offline rendering of animation frames, as in standard

network rendering, it's best suited for speeding up the rendering of single images as you work& Especially

when rendering high-resolution still images, you can get much faster results with distributed bucket

rendering&

iray Renderer

The 1/;%;A( iray( renderer creates physically accurate renderings by tracing light paths& ;t

reCuires little setup compared to other renderers&

The principal approach of the iray renderer is time-based: Nou can specify the length of time to

render, the number of iterations to compute, or you can simply launch the rendering for an

indefinite amount of time, and stop it when you are satisfied with the appearance of the result&

Early iterations of the rendered results appear grainier than the results from other renderers& The

graininess becomes less apparent, the more passes you render& The iray renderer is especially

good at rendering reflections, including glossy reflectionsO it is also good at rendering self-

illuminating ob8ects, depth of field and shapes that cannot be rendered with as much precision in

other renderers&

Achie"ing photo-realistic results is rather easy with iray and doesn>t reCuire comple* scene

setups& owe"er, to work more efficiently it does greatly help to ha"e special hardware& A

graphics card with a %A-enabled @ompute nified %e"ice Architecture Graphics !rocessing

nit @G! will dramatically impro"e the performance of the iray renderer& owe"er, don>t

confuse how iray uses the G! with how 7penG2 or %irectP use the G!& Mith iray, the G! is

used to compute the path of photons through space in a physically-correct manner& The only

difference between using the G! for this calculation and the ! is that the performance of the

G! is about


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iray in action w/3DBOXX 8550 Xtreme :Dual Six Core Xeon (4.3G!" # 4 G$%& ('xua)ro 5000* 3x +e&la C,050"

!erformance for iray should scale nearly linearly between the same type of G!s ? as it is across !s&

Therefore the more G!s and !s the faster your rendering results will be& 1/;%;A G!s do "ary in

their compute performance according to the number of %A cores they ha"e, the G!>s clock speed,

and the G!>s architecture& The G! card brand will not impact iray performance beyond these

characteristics& !ut into formulae, G! ray tracing performance looks like this:

@%A oresQ * @lock +peed * @G! Architecture R 0elati"e !erformance&

This means that for a gi"en G! architecture and clock speed, iray performance should scale linearly

with the number of %A cores present on the G!, and for a gi"en architecture and core count iray

should scale linearly with clock speed& The G! family @=uadro, Tesla or Georce does not ha"e

additional influence on how iray uses it&

iray Benchmarks

System Setup:Win 7 Enterprise x64Cubix GPU-Xpander Desktop 4P !6"" Dua# $uad E%%&" '(4"G! ) *'G+*x $uadro %""" &x ,es#a '"%"

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enderer CPUs$uadro %"""

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Nitrous Accelerated Graphics Core

A top priority of the E*calibur @PB0 initiati"e to re"italie )ds #a*, 1itrousis a completely new

"iewport system engineered to pro"ide dramatic impro"ements in performance and "isual Cuality&

1itrousle"erages today's accelerated G!s and multi-core workstations to help iterate faster andhandle larger data sets with limited impact on interacti"ity& 1itrous also pro"ides a render-Cuality

display en"ironmentthat supports unlimited lights, soft shadows, screen-space ambient

occlusion, tone-mapping, and high-Cuality transparency, along with progressi"e refinement of

image Cuality&

;n addition to high-Cuality, realistic display, 1itrous "iewports can also display stylied imagestocreate a "ariety of non-photorealistic effects such as pencil, acrylic, ink, colored pencil, coloredink, graphite, pastel, and technical drawing&

Quicksilver Hardware Renderer

The =uicksil"er hardware renderer accelerates rendering by using both the ! and the G!& ;t

is somewhat like ha"ing a game-engine renderer within )ds #a*& The main role of the ! is totranslate scene data for renderingO this includes compiling shaders for the specific graphic card in

use& Because of this, the first frame you render can take a while, as shaders are compiled& This

needs to happen only once per shader: subseCuent renders are therefore faster& This makes

=uicksil"er an ideal choice for rendering Cuick, high Cuality, animation pre"iews or design

re"iews&

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GPU/CPU Speed ualit! "echnical

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Integrated Renderers Advantages/0isadvantages

The ad"antages and disad"antages of each rendering solution in )ds #a* is not the sub8ect of this

presentation, so some general statements about the integrated renderers will be made instead&

Advantages

#inimal system setup reCuired

!owerful enough for most images

;nteracti"e wofkflows for scene setup

99


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o Acti"e+hade

o ;ray Aci"e+hade

o /ray0T

o 1itrous "iewports

;mmediate feedback for iterati"e test renders

Easy to manage file dependencies and network file paths

rame to frame consistency and reliable results

+ome new rendering solutions, like iray, le"erage G! compute resources to accelerate results

Disadvantages ) minutes of animation 6 9 minute per frame R HIhrs of artist down time

%ifficult to setup a single system to run multiple G!s ? if your rendering solution le"erages them

nless you ha"e a "ery powerful local resource, performance will be limited and there may be

hardware limitations @0A#

!erformance doesn>t scale, not enough resources for animations

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Local &et'ork Rendering

A common problem when rendering on the same workstation used for production work, is that "ery littleelse can be done while the hea"y rendering process is running&

=uick rendering tests are ok, but anything taking more than a

few minutes means loss of producti"ity while you wait&

8-core& all u&y. en row&in1 t2e we i& &low in t2i& ca&e.

To o"ercome that limitation, )ds #a* includes a tool called Autodesk BackburnerU to distribute the

rendering process o"er multiple networked computers, commonly referred to as the render farm& The

Backburner software is responsible for coordinating how 8ob assignments are processed&

Nou can perform network rendering with the +canline, =uicksil"er, iray and mental ray renderers& ;n its

most efficient form, network rendering uses multiple computers, connected o"er a network, to perform

rendering tasksO typically the rendering of animations with hundreds or thousands of frames& E"en a small

network of three or four !s can sa"e substantial rendering time and help you meet deadlines&

owe"er, network rendering can be eCually useful if you ha"e only a single ! and need to render a

number of images& Nou can assign the 8obs that need to be rendered and Backburner can manage therendering of each 8ob while you're away from the computer& ommonly, 8obs are assigned submitted 8ust

before you lea"e the office& Mhen you arri"e the ne*t morning, all your renderings are waiting for you to

re"iew&

or hea"y rendering 8obs, and especially for animations, in"esting in a dedicated in-house render farm

makes a lot of sense if you can keep it busy most of the time& The initial e*pense for hardware, software,

and training can pay off o"er time&

But a busy render farm also means scheduling 8obs, o"ernight rendering monitoring, and often ha"ing to

prioritie your renderings with the ones from other people in your company&

Also, let>s not forget the maintenance and Cuick obsolescence of modern hardware, often dri"en by more

and more demanding software&

)rdparty render ser"ices makes a lot of sense for smaller companies& They a"oid the hardware and

maintenance costs, but might suffer from scheduling conflicts, odd payment plans, unsupported plug-ins

or custom pipelines, and hea"y monitoring to make sure the output is what you want, as redoing

e"erything is going to cost more&

9)


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!ay plans by the hour also need careful consideration before submission& Nou don>t want to start a

process with a wrong parameter that is going to cost you a IV increase in rendering time&

0ender farms also are less helpful when your output is mainly still images& !reparation, uploads, and

freCuency of the submissions could make a )rdparty ser"ice slower than if you were to render locally on

your workstation&

Render 1ar- Re2uire-ents

7ften network rendering is percei"ed as something difficult

or e*pensi"e to setup& ;T departments are either unwilling

or unfamiliar with tools and technology needed and

designers ha"e limited "ocabulary when it comes to

subnets and windows ser"ices& Although this class is not

intended to teach you how to setup a local render farm

hopefully you will be armed with the

ad"antages5disad"antages so that you can at least makethe case for one should you need to&

+etting up a local render farm is a "ery common way to

le"erage e*tra computing resources during idle times&

;ncluded with )ds #a* $ )ds #a* %esign is a complete network rendering and management toolset

called Backburner& Mith as little as three clicks you can begin le"eraging additional hardware resources

during off hours or idle periods& Below is a "ery short description of what you need to start network

rendering:

o The #anager ?the primary controller of all the other render nodes @ser"ers& This is sometimes

referenced as a ser"er in other applications but in Backburner things are a bit backwards and this

machine is called the #anager& The manager machine will distribute the 8ob tasks to the rendernodes and track all progress with the 8obs in the Cueue&

o The +er"ers ? are the machines that do all the rendering& Again it>s a little backwards in the

Backburner world but think of these as the render nodes that are ser"icing the manager& These

machines only handle a single task at a time and when finished the manager will gi"e them

another task until the 8ob is complete&

o The #onitor ? can be run from any machine on the local network& This tool is used to monitor the

progress of the #anager& ;nformation such as: 8ob priorities, errors, ser"er status, frames

complete, render times, etc& can be accessed through the monitor&

ow can you use a render farmW Anytime the processing becomes longer than what you are willing waitfor& E"en if you are only doing a )Imin near final still

render you could 8ust as easily offload that task to

another idle machine while you continue to work at your

workstation, and with no additional cost you could

distribute slices of that single image and get the results

back faster than the original )I minutes& E"en simply

adding a single assist machine will enable the

workstation to remain producti"e while images are being

9D


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processed& !ersonal desk side rendering is certainly the simplest definition of a render farm but also

highly effecti"e, so much so that we are now seeing specialied systems, like the render!07from B7PP

Technologies, being created for this purpose&

There are many use cases where these additional hardware resources could benefit e"en the no"ice

user:

o !rocessing long animation seCuences

o +trip rendering or splitting a single large image into smaller distributed tasks

o ;terati"e pre"iews at a larger resolution and without pausing work while the processing occurs

o %edicated render hardware for intensi"e computation "s graphics acceleration needed for

workstations&

o +haring within the workgroup of this specialied hardware to ma*imie 07; of that eCuipment&

o 0endering multiple "iews o"ernight

!ypes of local network rendering

o sing e*isting workstations during off hours

o %edicated rack mount or ser"er room systems

o !ersonal desk side assist machines

!ypes of network rendering "o#s

%istributed animation frames: each render node renders multiple images in the seCuence

o A common use case for render farms

o igh "olume of tasks but low Cuantity of time per task

o 7ften reCuires similar hardware configurations

o The more machines the more risk for something to go wrong

o +omewhat fail-safe as bad frames can be redistributed

o +cene files and dependencies need to be copied to each render node or made a"ailable"ia network file sharing

o 7ften improper file paths result in failed render 8obs

o 9IX network connections to non-ser"er 7+ machines will result in failures

+plit scan lines: breaking up a single large image into distributed strips

o 1ot well known, but a great way to impro"e turnaround of a single high resolution image

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o 0ender sampling techniCues and antialiasing reCuire rendering strips that o"erlap, whichincreases the computation load, but when distributing to large numbers of machines itusually pays off

o Each machine loads and processes the entire scene data, reCuiring eCual amounts of0A# and other resources per render node&

o +ingle point of failure, one machine goes down you lose the progress of the completeimage

o +cene files and dependencies need to be copied to each render node or made a"ailable"ia network file sharing

o 7ften improper file paths result in failed render 8obs

o 9IX network connections to non-ser"er 7+ machines will result in failures

%istributed bucket rendering: processing small payloads of the single frame>s data

o Efficient data management, only the data reCuired to process a single bucket getsdistributed&

o 1o file path issues

o +ingle point of failure, one machine goes down you lose the progress of the completeimage

o 0eCuires additional licensing and dedicated resources

o 1o resource management

o reates hea"y network traffic and potential switch failures

#ultiple 8obs per each camera "iew: batch processing single image renders per camera "iew

Local &et'ork Rendering Advantages/0isadvantages

Advantages

%istributed rendering for large still images @strips or buckets on a limited number of machines

se e*pensi"e workstations in off hours

Backburner included at no additional cost

Easy to batch multiple "iews and scene setups

nlimited batch license options a"ailable for rendering animations and strip rendering

Disadvantages

2arge upfront e*penses @if you>re building a rendering farm

9


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arder to set-up

o ;T dept gets in"ol"ed

o 0eCuires Mindows +er"er 7+ and A2s for more than 9I machines

o +ubnet, %1+,

+hared resources

o !rioritiing render 8obs with the ones from other people in your company&

o +cheduling 8obs for off hours

o ea"y network traffic can be counterproducti"e

0eCuires spares or @better dedicated machines

#aintenance and Cuick obsolescence of modern hardware

1eed to monitor the rendering process during off-hours to ensure it stays on track

Additional headcount or e*pertise need to manage large farms

!hysical space and cooling, infrastructure costs for dedicated hardware

Cost Considerations

apital

+oftware for rendering

ost of tying up the workstation while rendering

Electricity to power the rendering hardware

ooling rendering hardware

#aintaining rendering hardware and configuration management

9K


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Re-ote Rendering Solutions;ncreasingly there are more and more web ser"ices a"ailable to pro"ide resiable compute capacity "ia

remote networks @the cloud& 7btaining access to large numbers of rendering resources is now more

easily attainable by installing or using preinstalled Lready to runL configurations onAmaon Elastic

ompute loud@Amaon E or le"eraging entire preconfigured render farms with ) rdparty ser"ices

such as 0ebus 0ender arm&

The "irtually unlimited cloud resources enable you to more confidently take on large rendering pro8ects

with no upfront in"estment and by only paying for what you use& Mith ser"ices like Amaon E you e"en

ha"e complete control of the computing resources& Mith "irtualied en"ironments you can in a matter of

minutes boot and deploy new ser"er instances to be used by the render farm, allowing you to Cuickly

scale capacity, both up and down, as your rendering reCuirements change& loud rendering ser"ices also

changes the economics of computing by allowing you to pay only for capacity that you actually use, and

potentially transfer those costs to a billable item on the in"oice rather than a capital e*pense&

"hird(part! Rendering Servicesurrently there are se"eral )rdparty rendering ser"ice pro"iders a"ailable for )ds #a* users& Autodesk

does not officially endorse the use of these render ser"ices, but here is an unofficial list that you can

e*plore for additional information - there>s probably many more than this&

9F
http://www.rebusfarm.com/http://www.rebusfarm.com/


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Although somewhat customiable most rendering ser"ices reCuire that you upload the complete scenedata and file dependencies @such as te*tures to their farm for each render 8ob, from which they

process5render the images, and then you download the data back to your local network& +ome do offer

more integrated solutions with plugins that make the process a bit more seamless for uploading and

retrie"ing data, but you are freCuently uploading and downloading large amounts of data& Nou are often

restricted to their plugin offerings and system configurations, with most pro"iders offering only select

rendering software options and ! only system configurations&

ost of these ser"ices is fairly consistent, "arying mostly by ease of use and integration to the workflow&

7n a"erage current prices are showing around YI&KI +% per ! core hour&

Re-ote 3irtuali4ed %achines 5or Rendering .3irtual Render 1ar-

!otentially the most economical, but technically challenging is to le"erage the "irtually unlimited cloud

resources a"ailable with ser"ices like Amaon E& The ad"antage is you get full control o"er the systemconfiguration& The additional machines can be configured as if they were sitting right ne*t to you on thesame network& Essentially a "irtual e*tension of your local network and allowing use of all the same tools,plugins and configurations as you would on a regular local render farm&

Mith the solution being non-industry specific the "olume, demand, and scalability factors are significantlydifferent than the more specialied rendering ser"ice pro"iders& This results in much more fa"orableeconomic factors and increased machine a"ailability for increased rendering power&

9H


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onfiguring and automating the setup of a "irtual farm can be challenging& Nou will need to understand

how to setup /!1 tunnels, #achine ;mages, subnets, %1+ forwarding, scripting system preferences, and

replicating data depositories& ;t>s definitely not for those challenged by comple* network setups, howe"er

it can be done with a little research and automated to the point of a few simple clicks of the mouse&Autodesk onsulting +er"ices does ha"e the e*pertise in customiing these types of configurations and

pro"ide additional support&

Securit!As with any digital data you are at risk of the information being replicated somewhere else, this risk is

e"erywhere @e"en your local network 8ust slightly more increased when using a remote ser"ice& sing a

render farm ser"ice "s& a "irtual farm could increase this risk as there is often a person or persons

responsible for render wrangling the data and monitoring the acti"ities on the remote farm&

Amaon E and other large cloud ser"ice pro"iders adhere to the ++AE 9 and the ;+AE )DI

professional standards, and undergo regular security audits by independent third party organiations&

+ecurity is taken "ery serious and there are many sources for additional information at the following links&

aws&amaon&com5security

++AE 9 - 7"er"iew

;+AE )DI - 7"er"iew

+A+ KI - 7"er"iew

Re-ote Rendering Advantages/0isadvantages

Advantages

1o upfront capital, maintenance, or infrastructure costs

Easy to scale with limited budget

#any pro"iders offering competiti"e pricing options

/! offers complete control o"er farm setup

Morld wide access to large numbers of resources

Disadvantages

Takes time to upload source assets and download rendered image data

!otential +ecurity risks

2imited plugin support with )rd!arty ser"ices

%oesn>t support interacti"e rendering

=ueuing doesn>t work for iterati"e rendering

I
http://ssae16.com/SSAE16_overview.htmlhttp://isae3402.com/ISAE3402_overview.htmlhttp://sas70.com/sas70_overview.htmlhttp://ssae16.com/SSAE16_overview.htmlhttp://isae3402.com/ISAE3402_overview.htmlhttp://sas70.com/sas70_overview.html


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!rimarily used to final rendering, reCuiring local render resources still

Any changes reCuires uploading the entire scene again

0eCuires proper scene setup for file paths and dependencies

2imited G! options and difficult to use with iray

Cost Considerations

2ocal 0ender arm:

o 9I a"erage workstations

o %ual Cuad core &< Gh

o ZY,)II per blade R Y),III in capital e*pense

o 9FII frames 6 < minutes5frame -[ 9< hours

o ost: YI X cost of ownership

0ender arm +er"ice !ro"ider:

o 0ebus arm

o @D * @%ual PE71 * core * &DI G X @KI * @%ual PE71 * D core * &< G

o 9FII frames 6


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Autodesk Cloud Rendering SolutionsAutodesk has been researching the use of the cloud for rendering in multiple ways& #ost recently,

Autodesk announced the Autodesk loud 0endering ser"ice for 0e"it and AutoA%& This was formerly

known as !ro8ect 1eon and pro"ides batch rendering ser"ices using a custom Autodesk renderer for

rendering& ;n addition to this effort, another effort was launched with 1"idia to e*plore how to use cloud

resources for a more interacti"e rendering e*perience, this is known as !ro8ect !andora and is currently

in a research5pilot phase with limited customers&

Project &eon) Autodesk Cloud 6 renderingAutodesk started de"eloping the new ser"ice and the new renderer using Autodesk 2abs to connect to

the users ? !ro8ect 1eon& This ser"ice initially reCuired submitting a %MG file, but it has since been better

integrated with 0e"it&

Goals 5or Autodesk Cloud Rendering

Goals we set for small studios or indi"iduals

Eliminate most of the hardware and software costs related to rendering

Gi"e them on-demand rendering muscles when needed for any 8ob type

2ittle to no learning reCuired

le*ibility and access when on the run

Goals we set for large studios

2ower infrastructure costs by pro"iding an alternati"e, on-demand resource

7pen the doors for rendering by non-technical people @marketing, sales, management

+implify contracts and dealing with )rdparties

0educe dependencies on the in-house e*perts for rendering needs

"he Revit CaseMe started with AutoA% and a simple upload-and-render approach, and then we e"ol"ed into an

integrated solution with 0e"it&

Rendering 'ith Revit

0e"it>s nati"e approach to rendering is of the .make it simple3 kind& #ost of the mental ray rendering

engine options are hidden& The user can choose basic Cuality and en"ironment settings, control lights,

and with the custom option, tweak some e*tra parameters&


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That>s good for the rendering non-e*perts, but when pushing the Cuality and image sie settings for your

final renderings, it>s not unusual to face hours and hours of machine time and risking missing your

deadline&

And while your workstation is rendering, "ery little can be done on it, as rendering tends to use all your

! cores and plenty of your memory too&

The alternati"e often used, is to e*port from 0e"it and adopt a )ds #a* workflow& Nou need )ds #a*, the

time to prepare, tweak and fi* your model in #a*, and a lot of time to ad8ust your new rendering settings&

1ot something you want to try unless you ha"e some e*perience in using )ds #a*&

7nce in )ds #a*, you ha"e access to other rendering engines, single image distributed renderings, and

animations network rendering& As we mentioned abo"e, all this reCuires hardware, licenses, and

maintenance&

Autodesk Cloud Rendering 5or Revit

Mhen submitting a rendering, you will still use most of the 0e"it /iews rendering settings, like the skycloudiness or color, the lights you want on or off, and your e*posure&

Mhen starting the online process, you will ha"e a few more settings that are specific to the cloud ser"ice,

like selecting the "iews you want to render, the Cuality, the sie, the type @still image or panorama, and

the output format&

But as we mentioned before, we encourage a workflow where you submit low Cuality images first, so you

can ha"e a Cuick pre"iew, and delay the decision-making about Cuality, sie and "iew choices to a later

time, directly on the ser"ice portal&

After a few seconds of preparation, 0e"it will be ready and let you get back to work while the data is

uploaded and rendered&

But don>t think that once your data is on the cloud it will be rendered as slow as you are used to& 7ur new

rendering engine runs on D-cores machines, and is highly optimied& The speed is often an order of

magnitude faster than what you are used to&

A 7rand &e' Rendering 8ngine

ere are some of the goals for the custom Autodesk rendering engine:

Mritten from scratch using uniCue technologies

AE market focused

+calable: +ingle machines and F-machine clusters @D-cores

Enhanced G; features

+upport for high number of lights

igh Cuality materials

)


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onstantly updated

And the list of future possibilities is Cuite long& Me are researching implementing sun studies rendering,

real self-illuminated materials, and plenty of impro"ements to e*pand e*isting features&

&ot !our t!pical Rendering Service

The key differentiator of the Autodesk loud 0endering ser"ice is the online workflow we created& Nour

interaction with the cloud ser"ice is not limited to monitoring and downloading, or keeping images&

;nstead, we wanted users to do most of their renderings on the cloud portal&

Me wanted to a"oid the user making decisions in ad"ance, decisions that take time and cost money if the

result is not what they e*pected&

;n our "ision, the pro8ect upload was supposed to be 8ust the beginning, not the final step& Me are at the

first rest stop on the road to that "ision&

"he 1uture o5 Autodesk Cloud Rendering service

Me are 8ust at the beginning of the de"elopment of this rendering ser"ice& Me ha"e the basic

functionalities and the infrastructure ready to impro"e customer>s producti"ity, but a lot more will come as

the ser"ice e"ol"es&

+ome ideas we are working on for the custom rendering engine:

E"en better materials

D


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Accurate lighting analysis @beyond 2EE% certification reCuirements

+un +tudies and Malkthroughs nati"e formats

+upport for comple* luminaries

G! acceleration for faster results

+ome ideas for ser"ice impro"ements:

;ntegration with Autodesk loud J documents to allow sharing

#ore scalable @faster machine, more render nodes on-demand

niCue optimiations deep within files content

!re-processed components

ontent "ariations from pri"ate or public catalogs

ontinuous hardware and software impro"ements transparent to the user

General uestions about Autodesk Cloud Rendering

How $uch Does %t Cost&

The price structure is being discussed and "arious proposals analyed& Me are still gathering data and a

final decision has not been made&

'hen 'ill % (e A#le !o Render 'alkthroughs&Malkthroughs, as well as many other features are being considered& loud ser"ices allow us to update

things freCuently and react more Cuickly to reCuests&

'hat Are Cloud )nits and How Can % Get $ore&

.loud units3 is our way to abstract the pricing of each cloud ser"ice& loud units will let you easily

manage and budget your ser"ices usage& Mhen a pricing structure is in place you will ha"e different ways

to get e*tra loud units&

'hen 'ill Autodesk Cloud Rendering and Cloud Documents (e *ully %ntegrated&

0endering @aka !ro8ect 1eon started a long time before %ocuments @aka !ro8ect 1itrous&Me kept separate web portals while %ocuments was in de"elopment and we will work toward integrationas the ser"ices mature&

Autodesk Cloud Rendering Advantages/0isadvantages

Advantages

;ntegrated with 0e"it ? ad8ustments to the scene stay in 0e"it

!anorama rendering


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aster results than working with mental ray in 0e"it

rees up seat of 0e"it when rendering @unlike local rendering

;ntegrated with Autodesk loud offerings and framework

#ore predictable image Cuality @less need to ad8ust parameters to get it .right3

%oesn>t reCuire an e*pensi"e workstation to render

%oesn>t reCuire special e*pertise to use

Disadvantages

0eCuires ;nternet connecti"ity %ata must lea"e the facility %oesn>t support animations, motion blur, depth of field, interacti"ity %oesn>t work with )ds #a* or other "isualiation tools !re"iewing reCuires using the cloud npredictability about when results will be a"ailable @depends on system loading Any changes reCuires uploading the entire scene to the cloud


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Project Pandora

!ro8ect !andora is a research effort that Autodesk and 1"idia are e*ploring to enable interacti"e cloudcomputing for iray with )ds #a* @and possibly other products in the future& The pro8ect is currently in pilot

mode for a limited number of users& At this time, it is not part of the Autodesk loud framework and is

completely separate from the Autodesk loud 0endering ser"ice&

Project Pandora Use Cases

There are si* primary rendering use cases currently being researched& These use cases fall into the two

general categories of .loud3 and .onnected3& loud use cases are those in which, once the scene is

uploaded, a )ds #a* session is no longer connected to cloud processing and can be terminated or run

independently& 0endering is then completely controlled e*ternally to the )ds #a* application @primarily

through a web browser interface& onnected use cases are those in which there is a continuous coupling

of )ds #a* and cloud ser"ices while rendering is performed& or comparison, a .2ocal3 use case is one

where rendering is performed on the local system or network&

Cloud Use Cases

pload for an interacti"e online design re"iew @2i"e/iew ? )ds #a* uploads a scene to the cloud

for later interacti"e re"iews&

pload for production single-frame rendering in the cloud ? )ds #a* uploads a scene to the cloud

for later production single frame rendering using the iray renderer& ontrol and results deli"ery is

"ia a web interface&

pload for production animation rendering in the cloud ? )ds #a* uploads a scene and seCuence

of frame scene changes to the cloud for later production Cuality animation rendering using the

iray renderer& ontrol and results deli"ery is "ia a web interface&

Connected Use Cases

!roduction rendering in the cloud ? final frame generation for the iray !roduction 0enderer

component of )ds #a* is performed in the cloud with the iray renderer, rather than by the local

iray rendering component of mental ray&

Acti"e+hade in the cloud ? rendering for the iray Acti"e+hade component of )ds #a* is

performed in the cloud with the iray renderer, rather than by the local iray rendering component of

mental ray&

o ;f the scene has also been uploaded for 2i"e/iew rendering in the cloud, then the

Acti"e+hade user can dri"e a remote design re"iew with multiple participants e*ploring

the space independently in web browsers, but with the capability of altering the scene in

)ds #a* interacti"ely during the design re"iew&

!roduction animation in the cloud ? production animation frames are computed in the cloud with

the iray renderer, rather than by the local iray !roduction 0endering component of mental ray&

K


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Latenc!

;n all cases, the system is designed to minimie uploading of data unless it has changed& E"ery item

@ob8ect, te*ture, etc& that gets uploaded is assigned a uniCue identifier& Before something is uploaded, the

system checks to see if it already has that ob8ect& ;f so, it doesn>t upload it& This means that o"er time,more and more data can be reused and latency is reduced&

$roect $an)ora ieiew in action wit2 C2rome row&er.

7asic Process

urrently, we>re e*ploring the following process of using the cloud:

9& Each person will ha"e an Amaon account and will ha"e to supply Amaon with a credit card number

or make some arrangements to pay Amaon&

& ;n that account, a permanent !andora loud Application +er"er will be running on a low cost ser"er

@\YI&9I5hour and users will be paying for Amaon permanent storage @+)& This ser"er initiates

!andora rendering nodes when reCuested for rendering&

)& Each person will be able to manage their usage from the Amaon account

D& 1either Autodesk nor 1"idia ha"e access to this account or the data

0etails o5 the process

At any time, the )ds #a* user can bring up the !andora loud ontrol Mindow in )ds #a* through a

menu item @or #a*+cript call& ;f the )ds #a* user initiates a loud onnected #ode operation @such as

reCuesting Acti"e+hade rendering or !roduction rendering in the cloud, and if the !andora loud has not

yet been setup and initialied properly for the particular user, then the !andora loud ontrol Application

@A will automatically pop-up this window and reCuest the user to input the setup information

necessary to initialie cloud rendering support&

F


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$aking +resentation %mages *easi#le

The "ast ma8ority of )ds #a* users only render still images& #ost users want to produce large format

images, with most of these using large format color printers&

!resentation sie images are a challenge with iray because render times are linear to the number of

pi*els rendered, and larger resolutions magnify areas needing more refinement& +o while a Dk image

should only take 9P longer than a 9k image, with many people saying the D "ersion isn't LdoneL until it's

gone D)P longer&

$aking iray Animations *easi#le

or the )ds #a* users doing animation, rendering times benefit greatly from a render farm& But a render

farm can't accelerate a gi"en frame, so the ratio of nodes to render time isn't linear& This isn't the case of

!andora, which can balance the number of nodes for a frame alongside the number of frames being

rendered&

Network Rendering for Animations

#ost companies with render farms take pride in configuring the cheapest rendering nodes with the

highest render performance, usually resulting in dual socket !s with no G! and minimal capability to

accept a G!& or iray, this means most e*isting farms will be rendering using the ! instead of the

G!, which will be at a significant performance disad"antage compared to a G!-based render farm like

!andora is based on&

$aking +hotoreal %nteractive

!andora makes the prospect of interacti"ely na"igating, or working, within a photorealistic "iew a true

possibility& !andora's 2i"e/iew feature allows anyone to na"igate the )% scene on the ser"er, and pause

the "iew for final images&

;nteracti"e speeds on modern workstations ha"e difficulty reaching < !+ at standarddef resolutions&

!aying Y


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0endering can now be billed to the client as the costs are clearly defined and documented&

!andora uses progressi"e iterations to show if results are on track, allowing midstream

corrections or cancellations&

7nce data has been rendered on !andora, it li"es on the cloud and affords the additional

possibility to access it remotely and share it with others&

Mith !andora, you can ha"e a more collaborati"e process based on 2i"e/iew as guests and

coworkers can ha"e photorealistic re"iews at their leisure from any location&

!rocessing the data directly from )ds #a* ensures "ersion matching ? which "ersion of )ds #a*

will be less of an issue with !andora&

The same rendered used by !andora is also shipped with )ds #a* ? allowing you to do pre"iews

on your local machine before committing to a production render using !andora&

Mith !andora, any ob8ect or asset @te*ture, etc& that has been rendered once won't be uploaded

again ? this optimies bandwidth and the time it takes to see changes rendered&

All preparation for rendering the scene occurs on the client ? which means you don>t need to

install special scripts or third-party plug-ins on the render nodes or manage them&

Disadvantages

0eCuires ;nternet connecti"ity

%ata must lea"e the facility

0eCuires adopting the iray rendering workflow, which may be different than what is currently used

Billing is by the hour, e"en if you only need 9< minutes @but you can schedule other renderings to

use the full hour&

2i"e/iew interacti"e rendering mode reCuires low latency to the Amaon ser"ers ? may not pro"e

acceptable in some regions&

1ot integrated with Autodesk loud framework initially&

urrently, Amaon G!s are limited to )Gb memory so all the scene must fit into this to render

urrently, the )ds #a* workstation is tied up rendering in production mode because it is recei"ing

a stream of rendered imagery from !andora @not true for 2i"e/iew&

Costs considerations

Nou can find the costs of running the AM+ luster G! instances on Amaon>s web site,

@http:55aws&amaon&com5ec5pricing5 & urrently the rate is Y&9I per instance per hour& There is

no fractional billing for less than an hour& Each instance contains two G!s

@http:55aws&amaon&com5ec5instance-types5 and two processors& urrently !andora will only

)9
http://aws.amazon.com/ec2/pricing/http://aws.amazon.com/ec2/instance-types/http://aws.amazon.com/ec2/pricing/http://aws.amazon.com/ec2/instance-types/


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use G!s because they scale better& Nou will ha"e to use a minimum of one instance @two

G!s& ;f the ser"ice becomes a commercial reality, Autodesk and 1"idia will be charging a

surcharge on top of the Amaon charges& There is roughly a


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Su--ar! ustomers ha"e many options

loud computing pro"ides uniCue abilities to meet demands and deadlines

Autodesk loud J 0endering re"olutionies 0e"it rendering today

!ro8ect !andora is researching the solutions of tomorrow