information system engineering: the end of bricoleurs€¦ · professor emeritus at cnam ©2014...

©2014 /J.Printz / Information system engineering project management

Information system engineering: the

end of “bricoleurs”

The impact of real time, big data and massive

parallelism on IT project management

Jacques Printz, CSDM 2014

Professor Emeritus at Cnam


Information engineering

Human machinery

BUSINESS processes

Technical engineering

INDUSTRIAL processes

Digitalization of

all or parts of

these processes

Percolation

Processes everywhere

Integration of everything through information

System of systems engineering

Business information system Industrial information system

Information Information


Interactions between systems and

people

Symbiotic

relationships

End-users Engineering

Hardware

Software

R&D

[State of the art]

Open questions

Feedbacks

Usages

[State of needs]

Do-it-yourself?!

Knowledge integration

People ware

System as a whole

People ware

Response time Response time Response time

Agile engineering From WHAT to HOW

Development

Maintenance

Operations

High

pressure

of the

customer

High

pressure

of the

management

Any interaction is becoming Real Time


Human complexity

Nothing technical here: just

choices, decisions, cooperation,

soft or hard power, capacity and

maturity, authority, etc.

Information systems complexity

Engineering

complexity

Usages

complexity

Technology

complexity

Interactions

Classical

complexity

The heart of information

system project management


The “work horse” of IS engineering

Building blocks

Transaction processing

That?

Or that?


Layout of the classical TP

Atomic Transaction

with ACID properties

The quantum of information processing

Mainly data

referenced

by the TP

Take a snapshot

of the initial state

Restore the

initial state Rule of thumb:

A piece of code not

larger than 1 or 2

thousands lines of code

Atomic

Consistency

Isolation

Durability

A coherent

memory state

Next TP


Examples: Transactional situations from

the end-user point of view

Typical long

transactions

based on short

ACID

transactions


Just evolution

Evolution of transaction programs concept

Classical TP

Distributed processing Parallel processing Mainframes, sequential processing

Short ACID TP Long TP Micro TP

Time

70-80 2010-… 90-2000

Client/Server TP

Fully automatic recovery

mechanism

Multi-core parallel programming

New mechanisms like

Autonomic computing are

needed

Multi-core is a

black-box

Complexity wall

New tools and methods

are needed


The multicore revolution

Blue Gene Computer

Tera-100 Computer


Organize the parallelization

P1 P2 P3 P4 P5 PN . . . N Physical Processors

[but many more virtual processors]

Processes synchronization & communications

Semaphores Mail boxes

Timers

Locking

mechanism

Priority

Thousands of threads


From one sequential flow to many …

P

Sequential flow

Core-1

Rule : 1 thread 1 processor

Can be done by hand

Rule : 1 thread Many processors

Just impossible to

do it by hand

Parallel flow

Data processed

by that flow

Core-2

Core-N

Major program transformation to adapt the

sequential code to the many cores execution

flow especially the data

Data

“Compiler”


What is the real status of YOUR code?

Patches


How to transform bad code?

No magic behind!

Just engineering


A new approach for information

engineering

New tools are needed to extract the natural

parallelism hidden in data Data is the new code

The solution has to model data semantic, explore

different data organization, choose one based on

simulation result maximizing resource usage and

allowing to organize the parallelism in a reversible

way to manage the unavoidable programming errors

David Patterson, Professor UC Berkeley:

“We desperately need new approach to

HW & SW based on parallelism since

industry has bet its future that

parallelism works”


The way [道] to system architecting

SysML, BPMN/BPEL, WSDL, …

System Architecting

[requirement

engineering]

Functional Architecture

[Business Computing]

Organic/Physical

Architecture Usual Languages : C/C++, Java, … + Compilers

Mapping done by hand DSL

Automated Mapping

from the System view

Components view

The singularity is here!

Final

mapping on

the available

cores for

execution

Programs development validation & verification

can no more be done by trial & errors, but only by

simulation on the functional layer, using models


Facing complexity: layered architecture

Applications

Operating System API (programming languages)

Operating System

Interface Hardware/Software

hardware Functions

Machine Architecture and language(s)

Physical Architecture (cache memory, pipe-line, …)

Application Programming Interface – Library / Middleware

OS « Boot »

Circuits Architecture and wiring (ECC)

Transistors and Silicon – Atoms & Electrons

Microprocessor architecture and hardware« programming » - Buses

Microsoft

Office Internet – Web

Information

System

Scientific

computing

Signal & Image

processing . . .

Quantum world

Deterministic

World

Physical

Laws

Network stack

Recovery

mechanism

Recovery

mechanism

Recovery

mechanism

Non deterministic

Nanoworld

Silicon cristal


Visible part

[Added value]

System Plate-form

Business API /

Plates-forms &

infrastructures

Patrimonial

Business software

Facing complexity: Visible or hidden?

Business API

Generic Applications –

Packages

Specialized Applications and

processes automation

Business processes

Scripting

End-users

Hardware / QOS

Couches

Télécoms

Middleware and system

services OLTP, SGBD,

CORBA, ... Administration, ...

API associated with

programming languages

Middleware Integrated like

Internet/W3C, ESB, ...

• Network

• Operating system

• Virtualization (Cloud / multi

core computing, .)

OS

Circuits / QOS

Events

Dynamical control

“Black box”

Autonomic computing

Hidden

reality


Conclusion

Information engineering,

through the pressure of ultra

high complexity at all levels,

requires now the same rigor

as any other traditional

engineering

There is no alternative to

modeling techniques to

master complexity

If we don’t organize

complexity, the complexity

will kill us … like in the

Babel tower story !!!

M.C.Esher Drawing

information system engineering: the end of bricoleurs€¦ · professor emeritus at cnam ©2014...

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