ripping through data - challenges faced in the digital front end

© Copyright 2011 Global Graphics Software Limited1

Martin Bailey

CTO, Global Graphics

RIPping through dataChallenges faced in the digital front end


– This presentation was created with

assistance from our partners at

Hewlett Packard.

– Especial thanks are due to Dave Staas,

Lead Software Architect,

Indigo Digital Press DFE

ACKNOWLEDGEMENTS

3

INTRODUCTION

– A Controller or Digital Front End (DFE) provides a number of functions

for digital press print jobs:

• Workflow definition, control, and management

• Job management (submission, status, view, edit, cancel, etc.)

• Color, ink, and media management

• Imposition and finishing management and control

• The conversion of rich document formats like PDF and PPML into “print ready bits” –

data that is rendered and formatted for the marking engine of the digital press

HP Indigo W7200 Digital Press


CONSTRUCTING A DFE

Control process

RIP

RIP

RIP Press controller

Pre-processing

Post-processing

HP Indigo 7500

Digital Press

Job cache

Raster cache


WORK ALLOCATION

– Interpreting/rendering –

– Color management –

– Imposition – , or

– Trapping – or

– Screening – or

– Font handling –

– Variable data –

– + for PPML etc

for PDF with no h/w assist

+ for PDF with h/w

(+) or (++) for PDF/VT

Control process

RIP

RIP

RIP

Press controller

Pre-

processing

Post-

processing

6

WHAT’S THE PROBLEM?

– A typical print shop can have many digital presses and DFEs (Consolidated

Graphics, for example, has more than 50 Indigo digital presses across several sites1)

– A standard mid-range digital press (120 PPM) requires the processing of over

one hundred million pixels every second, worst-case, with possibly multiple transforms,

and in 4 (or more) colors

– HP’s high-end presses (like the T400 below) require nearly three billion pixels every

second

– The primary performance goal for a DFE is to process any job or workflow at or above

press speed – strive to always have the DFE outpace the press over a shift

– Maximum efficiency must be exploited in every aspect of the system’s design in order

to achieve this goal within reasonable cost constraints

HP T400 Color Inkjet Web PressHP Indigo 7500 Digital Press

7

18”

12”

8

1m

m

1m

m

1 mm2

Each color plane is

32 pixels/mm2 (4096

pixels as shown)


It’s solved for current jobs and current presses, but:

– Presses need higher data rates

• Larger format/wider webs

• Higher paper speeds/pages per minute

• Higher resolution (2x resolution = 4x raster size)

IT’S A SOLVED PROBLEM, ISN’T IT?


– Larger coverage of variable data in direct marketing, triggered by

• Better demographic data

• Better data mining techniques

• Proven better response rates to well-crafted personalised mail

– More use of live transparency

• Driving adoption of PDF for direct marketing

• Expanding out of general design practice for books, publication, POD, print-for-pay and

general commercial print

• Many designers don’t even know they’re using transparency!

– In a well-optimized RIP transparency requires more processing than

an opaque job

• Color transforms & read/modify/write cycles

JOBS ARE GETTING MORE COMPLEX


THIS IS TRANSPARENCY …


AND THIS …


AND THIS


– PDF/VT (ISO 16612-2) defines structures in a PDF file to:

• Allow easier identification of re-used and single-use graphical elements

• Define which sets of pages go together in a hierarchical structure

− E.g. as components that will be supplied to a single direct mail recipient

• Enable pseudo-streaming

– This means that PDF/VT is a useful standard!

– But it does not address the fundamental issues of:

• Compute power required to process transparency

• Sheer data volume required to drive current and future digital production presses

DOESN’T PDF/VT FIX THE PROBLEM?

15

ARCHITECTURAL CONSIDERATIONS

– Some of the more relevant architectural considerations for enabling

maximum efficiency:

• Reliability

− Fast, unreliable systems usually aren’t worth much. Stability first, performance second

• Work Avoidance

− Look for ways to move or eliminate work first rather than scaling an inefficiency

• Centralized or Distributed Caching

− Caching can avoid work and improve performance

− Watch for centralized caches becoming a bottleneck

• Instrumentation and Measurement

− Establish a way to measure performance in your code and system

• Planning

− An ounce of design effort up-front will save more than a pound in efficiency and cost-savings in development and

manufacturing

− If you drive a range of devices you may gain from a common, scalable solution across at least some of that

range

– No universal right answer on most of these considerations; they’re

useful topics to think about in the context of efficiency


– With the right architecture and components you can make a DFE drive

your press at engine speed

• Every component makes a difference

– What matters is the throughput achievable per $ total bill of materials

• Include hardware and software

– The target is to drive the press at rated speed while minimizing the

cost of the DFE

• If the software is faster or more efficient you can reduce the hardware required

– Reducing hardware reduces power consumption and cooling

• Going green can be profitable!

THE REAL GOAL

17

– Many machines per rack

– Typically one DFE per rack

• For very high end needs, one DFE in multiple racks

– Up to 12 Indigo presses per DFE, depending on

their type and speed

• “Ultra” version allows many more

– Each DFE can drive:

• Multiple presses

• Multiple press controller machines

• Multiple RIP machines

• Multiple pre-RIP and post-RIP storage arrays

• Multiple remote UI instances

– Each DFE has a central System Manager

• Generally speaking, no post-RIP data flows through

PARALLELISM – WITHIN THE DFE

18

Split into page ranges and assign to RIPs

RIPs deliver data in parallel to press controllers

Press controllers deliver to presses

PARALLELISM – END-TO-END SOLUTION

Split files into multiple “partitions” or chunks and process in parallel

Parallelize early, maintain multiple parallel pipelines

Parallelize in pre-RIP, where the data is much smaller (1/7th the size)

Process multiple jobs in parallel

Different variations optimize first-page-out, engine loading or throughput

19

– Multiple CPUs per machine

– Multiple cores per CPU

– Multiple physical disks per machine

– Multiple physical disks per logical disk

– Multiple (teamed/bonded) network

interfaces per logical network connection

– Multiple RIPs per machine

– Multiple threads per RIP

PARALLELISM – WITHIN A MACHINE

We invest effort to take advantage of all of

these machine-level parallelisms:


– Digital printing architectures need careful design

– Many different strategies must be employed in unison for the best

effect

– Key architectural considerations can help guide your efforts

– Selection of the best components and supplier/partners is an important

aspect

– The ultimate goal is to reduce cost, power, and cooling for customers

SUMMARY


Q&A

More information at www.globalgraphics.com/imiconf

ripping through data - challenges faced in the digital front end

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