Integrated circuits - Center for Bits and Atoms

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engineering emergence
a view of complex system engineering
from integrated circuit design evolution
brian w bramlett
intel corporation
for mit media lab : center of bits and atoms : emergent engineering : 2002 october 16
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brian w bramlett
intel corporation
for mit media lab : center of bits and atoms : emergent engineering : 2002 october 16
overview: four target research areas
language commonality across domains+disciplines
limits of atomic system complexity
formalization of complexity engineering
design system implications
(methodologies, tools, frameworks, infrastructures)
brian w bramlett
intel corporation
for mit media lab : center of bits and atoms : emergent engineering : 2002 october 16
on language: semiotics and semantics
since these fields are only beginning to interact broadly
across "traditional" disciplines, there is a great deal of
semantic disconnect [and things that fill that gap…]
more critically in systems science when exploring the
relationships among and emergent behavior of connected
components in dynamic systems near chaotic boundaries
1: common semantics for complex, multi-disciplinary
systems is a unique, arguably critical challenge
brian w bramlett
intel corporation
for mit media lab : center of bits and atoms : emergent engineering : 2002 october 16
context: setting the stage
emerge
to come into view
evolve
to unroll or unfold; yet grow in complexity
converge
to come together: close, meet
to direct toward a common center: concentrate, focus
convergence is a core concept in modern cpu design
brian w bramlett
intel corporation
for mit media lab : center of bits and atoms : emergent engineering : 2002 october 16
integration: from the top
• Central Processing Unit
very semantically accurate
(see «atomic system complexity»)
• integrated (circuits)
bound or tightly coupled
often implies «non-modular» within the system
• complex integration
couplings among abstractions become so profound, they
challenge their meaning
component boundaries blur beyond practical use
to characterize: how well-defined are the interfaces, how
much mapping is required across abstract domains
brian w bramlett
intel corporation
for mit media lab : center of bits and atoms : emergent engineering : 2002 october 16
*lsi design space: notable parameters
• volume-margin-yield
cost per manufactured part before NREs; ASPs
coupled to die size
• structural complexity
unique patterns, equivalence classes, «compressibility»
• performance
highly visible within the functional domain
others prominent due to cost of quality+reliability
emerging: metrics like MIPS/Watt, peak+average
brian w bramlett
intel corporation
for mit media lab : center of bits and atoms : emergent engineering : 2002 october 16
*lsi: types of products
semiconductor memory, displays, ASICs, graphic
controllers, CPUs, chipsets, interfaces (USB, FireWire*,
WiFi*...), SOC products, microcontrollers…
[imagine a three-axis plot]
• low-volume, high complexity, high performance designs
are not economically justified; breaks the “choose two
of three” phenomenon
• mass-market performance cpu design is highly
constrained, which dramatically restricts the
design space due to coupling effects
brian w bramlett
* Other names and brands may be claimed as the property of others.
intel corporation
for mit media lab : center of bits and atoms : emergent engineering : 2002 october 16
cpu design: unique systems issues
other vastly complex engineered artifacts are currently
produced, but:
• many rely on complex feedstock or bulk properties
• most are composed of less complex,
replaceable/serviceable components
• few are as complex, reliable, and optimized at physical
limits of performance, with commodity volumes
[…a twist: prerequisite to evolving engineering disciplines]
so, to focus: highly optimized, closed complex systems
brian w bramlett
intel corporation
for mit media lab : center of bits and atoms : emergent engineering : 2002 october 16
about: atomic system complexity
•
•
•
•
•
a hallmark of this degree of coupling; strong local coupling or
large statistical contribution to intertwined first-order effects
intrinsically coupled design, ecologically «closed» systems
coupling approaches the limit of what can be distinguished as
a system of connected components; inseparable, insufferable
design abstraction becomes very difficult to manage mentally
and in the data models
a useful view during the design process is a series of phase
transitions in convergence toward design requirements: an
emergent property
…and since you will need to get used to me saying it: "coupling, coupling, coupling…”
brian w bramlett
intel corporation
for mit media lab : center of bits and atoms : emergent engineering : 2002 october 16
why/how: exploring atomic system limits
2: is there a practical or theoretical limit to complexity
and reliability in an «atomic system» component?
•
how much of this is due to a "single-minded" entity defining
design, rather than what might happen with a
collective/emergent design intent?
•
other examples of complex systems that are more economic to
replace than repair? a biological tactic?
•
some theory already, but do any comparable engineered
systems exist? any coming?
•
does this imply that this form of engineering a specialization?
subsumable? bootstrap/replaceable?
•
…essential? insufficiently developed?
brian w bramlett
intel corporation
for mit media lab : center of bits and atoms : emergent engineering : 2002 october 16
cpu design: major subsystems
•
•
•
•
economy / business ecology
business model / fiscal + market analysis
cross-platform design strategy
platform design (a highly distributed function)
»
»
»
Instruction-level architecture
micro-architecture and logic design
circuit (dynamic) and physical (structural) design
•
•
physical fabrication / manufacturing process and system
physical test, systems integration, back-end q+r
although there are equally critical complex inter- and intra-system coupling (clear up to
organizational change theory's “absorptive capacity”), many of these aren't
exclusive to IC design generally, nor mass-market CPU design specifically.
manufacturing systems for CPUs is highly specialized in and of itself, and has large,
often blunt effects on the others. the top few layers are not as well-structured (with
implications to evolution).
although very strong and increasingly complex coupling exists across all these domains,
those emphasized above are the among the tightest subset.
brian w bramlett
intel corporation
for mit media lab : center of bits and atoms : emergent engineering : 2002 october 16
jargon file: engineering process 101
what you want, what you can't have, and how to reasonably get there on
time and in budget
requirements: domains of convergence, design “qualities”:
• function, performance, power, reliability, manufacturability, cost,
schedule, risk…
cost (resources + time):
• human resources, compute systems, intellectual property (including
licenses), time
tools:
• abstractions within domains, marked by level of granularity and
language; these levels usually cross sets of domains
rules: (process)
• moving efficiently toward convergence over time using abstraction
granularities to define convergence phases, rates, and transitions
brian w bramlett
intel corporation
for mit media lab : center of bits and atoms : emergent engineering : 2002 october 16
coupling: characteristics
Scope (across abstractions, information: in the design system)
• Many levels of formal abstraction/granularity; often one or more
languages and models each
• incremental mapping from specification to implementation; information
to physics
• Hard to span with precision [hint: good emergence target]
Scale (numeric and physical: everywhere)
What is often thought of as complexity, but often isn’t.
• a billion transistors, each connected to at least three others, [graph
layout shares issues]
• «computationally intractable», «incomprehensibly large»
brian w bramlett
intel corporation
for mit media lab : center of bits and atoms : emergent engineering : 2002 october 16
coupling: characteristics
Strength/Degree (across domains, physics: in the artifact)
toward the limits of information physics and space-time physics, and where
they intertwine (thermodynamics meets information theory)
approaching the level of bits and quanta, and a very short distance to qbits
coupling is strong, complex, atomically non-linear
component isolation (well-defined interfaces) costs more (noise, parasitics)
unlike most «complex systems» where simple rules imply complex behavior,
the rules are not simple, either.
Consider:
microarchitecture performance + device/wire placement + em noise + power
+ process variation + physical limits
brian w bramlett
intel corporation
for mit media lab : center of bits and atoms : emergent engineering : 2002 october 16
an abbreviated evolutionary history
early on, coupling (for design) was primarily human-scale:
practical to do by small groups, manual work
Moore-type scaling (you knew that was coming) in efficiency enabled by
(among others):
increasing use of design abstraction
domain-specific engineering techniques
improved process control
refined and extended automation
sticking points generally defined by coupling issues
optimization is still a central, competitive engineering focus and driven to
local maximum, even if global constraints change the landscape
proportion of design with this emphasis drops, but often with net growth
brian w bramlett
intel corporation
for mit media lab : center of bits and atoms : emergent engineering : 2002 october 16
comparison to familiar software systems
Inversion of approach to parallelism
•
parallelism tends to be aligned to a physical basis
•
sequential/serial elements map to logic
massive default low-level parallelism with explicit serialization
versus
typically serial design, with explicit thread-based parallelism or high-symmetry
distributed processing getting design attention, and optimizing compilers
defect tolerance, cost, and performance
without the redundancy/intelligence for device-level faultdetection at manufacture:
•
every transistor on every die must effectively be testable
and «perfect»
•
very low design defect tolerance; efficient robustness
clearly, there are software systems which exhibit similar qualities to cpu design
brian w bramlett
intel corporation
for mit media lab : center of bits and atoms : emergent engineering : 2002 october 16
making it all fit and fit together
Why decomposition? (partitioning, hierarchy)
optimal fit to:
• computation, communication, capacity/cache
• Mind or machine or tools
[looks like a classical system model]
Mapping [complex coupling makes this hard!]
• Extraction, synthesis, and verification
• Based on encapsulation of partition contents by interface/boundary
• Across abstraction granularity, convergence domains
Common design system abstractions [architectural hierarchy]
• design representation, query, transformation, measurement
• state management
• workflow management
• role management
brian w bramlett
intel corporation
for mit media lab : center of bits and atoms : emergent engineering : 2002 october 16
«…essential? insufficiently developed?»
for the purposes of this discussion, an assertion: yes and yes
the design system itself becomes (is) far more complex than the
artifacts it produces
complex system design infrastructure requires high fiscal
motivation not currently present
each wave of evolutionary improvement moves toward a local
maximum around existing engineering methodologies
interactive design is still often single-cpu (even single-thread),
and license bound; even graphite and pressed wood pulp
design-expertise IP is still costly, but little market justification
EDA is nowhere near the maturity/commodity of SW compilation;
plenty of room to grow
brian w bramlett
intel corporation
for mit media lab : center of bits and atoms : emergent engineering : 2002 october 16
what's the emerging issue?
(does this look familiar yet?)
•
•
•
•
early attempts within EDA alone have fallen short; lack of
incentive in existing business models
current «open» design systems do not scale for required
capacity, and lack modular integration required for evolution
as other engineering disciplines evolve, this looks to become
common
de novo invention of specialized design systems for every new
combination of disciplines introduces diversity without common
abstraction
4: open architectures designed for emergent and crossdisciplinary engineering are needed; the design system
itself seems a candidate for emergent engineering
brian w bramlett
intel corporation
for mit media lab : center of bits and atoms : emergent engineering : 2002 october 16
complexity engineering: (re)defined
…or “bramlett’s semantic gripe”
a frequent misnomer for emergent engineering
A discipline including partitioning a design (even dynamically and by
evolutionary means) into various design approaches, such as traditional or
emergent, by considerations such as requirement domains, effort/cost,
and risk.
Another view:
engineering how complexity is managed and manifested in a design
instance and its design process as a method of optimization
Or, to appease the emergilentia:
a formal specialization within system engineering
brian w bramlett
intel corporation
for mit media lab : center of bits and atoms : emergent engineering : 2002 october 16
complexity: my own taxonomy
as if there weren’t enough:
• Intrinsic
physically or logically inherent
• Artificial
Due to design or construction of abstract model. This is
becoming more fluid, and can be subject to engineering
• Pseudo
Attributes that are misunderstood as complexity, like scale
A form of noise, basically.
brian w bramlett
intel corporation
for mit media lab : center of bits and atoms : emergent engineering : 2002 october 16
simplistic design system evo scenario
how might emergent engineering be incorporated into
existing disciplines and infrastructures (in vivo)?
1. traditional; extended + conventional reuse of
standardized components
2. complexity engineering applied within the design model
and automation space
3. complexity engineering with awareness of humans as
part of design system
4. inclusion of emergent methods
brian w bramlett
intel corporation
for mit media lab : center of bits and atoms : emergent engineering : 2002 october 16
directions in design system engineering
pattern languages and automation for query, transformation, mapping
[often from graph/string domains; linguistic analog of…]
standardized, modular interfaces and visualization engines
[aligned to human/machine relative efficiencies;
biological pattern recognition/learning, machine-precise manipulation]
information design including information physics
[self-assembling data visualization]
domain-agnostic architectures and frameworks
[analogous to movement toward semantic web]
resource + model partitioning and allocation; complexity engineering
[humans, computation/machines, design]
fine-grained workflow / state / design management
[dynamic precision decoupling]
merging and convergence of engineering methods across disciplines
bootstrapping via formal systems and workflow analysis
[reusing design tools on the design system itself; autocatalysis?]
brian w bramlett
intel corporation
for mit media lab : center of bits and atoms : emergent engineering : 2002 october 16
questions: a step out from the formal scope
project planning:
• how to staff and schedule for a set of goals or design intent
• including direction of complex infrastructure development/investment
organizational composition, structure, and dynamics:
• what roles and disciplines are needed? how do they relate/couple?
• engineering for/to absorptive capacity
even within electrical engineering, augmented by computer science, the scope of
domain knowledge required is vast
on a larger scale, process / infrastructure to support design intent:
• facilitating emergent design (expression of collective intent) evolved
from non-globally aware system components
• what does design mean here as a manifestation of desire or intent?
and are these traditional, emergent, complex…?
brian w bramlett
intel corporation
for mit media lab : center of bits and atoms : emergent engineering : 2002 october 16
postscript: complex design engineering ecology
design cost relative to manufactured margin is still small
[capital, nre, r+d cost/effort weighted in manufacturing]
design productivity driven by market opportunity
cost/gain and capital investment/amortization
interesting to see what happens when cost of
manufacturing and barriers to entry drop…
[hint: design engineering is coming up for commodification]
brian w bramlett
intel corporation
for mit media lab : center of bits and atoms : emergent engineering : 2002 october 16

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