Electronic Design Automation

fanaticalpumaMechanics

Nov 5, 2013 (3 years and 8 months ago)

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NSF Workshop

Electronic Design Automation

Past, Present, and Future

July 8
-
9, 2009

Sankar Basu, Robert Brayton, and Jason Cong,


Purpose

This workshop was organized

1.
to reflect on the success of EDA to see how

a)
its practice can influence other fields of computer
science, and

b)
its methodology can be applied to other application
domains, and

2.
to review the progress made under the National
Design Initiative and evaluate what new directions
and topics should be added to the Initiative.

3.
Counteract the notion that it is only engineering

4.
Clarify to outsiders what EDA is

Organization

First Day

series of talks covering broad areas of EDA and
selected emerging technologies that might benefit from
EDA methodologies.

Second Day




broke up into focus groups

1.
EDA Past, Present and Future Support.

2.
Funding of EDA, Research Opportunities and Interaction with Industry.

3.
EDA for Emerging/Adjacent Technologies.

4.
Educational Aspects.

5.
EDA and Theory.


groups answered focused questions and prepared summaries


reconvened to hear summaries






Follow up


Groups prepared extensive reports which were
merged into a final report
http://cadlab.cs.ucla.edu/nsf09/


Talks


Keynote Talks

Ralph Cavin and Bill Joyner (SRC),
and Wally Rhines (Mentor
Graphics)

Prith Banerjee (HP)

Invited Talks

Sharad Malik, Princeton

Andreas Kuehlmann, Cadence

Arvind, MIT

Jochen A. G. Jess, Eindhoven
University (emeritus)

Carl Seger, Intel Corp.

Edmund M. Clarke, CMU

Shaz Qadeer, Microsoft


Tim Cheng, UC Santa Barbara

Rupak Majumdar, UC Los Angeles

Jaijeet Roychowdhury, UC Berkeley

Rob A. Rutenbar, CMU

Jason Hibbeler, IBM

Jyuo
-
Min Shyu, National Tsing Hua
University

Igor Markov, University of Michigan

Mary Jane Irwin, Penn State

David Z. Pan, UT Austin

Jim Heath, Caltech

Chris Myers, University of Utah

Lou Scheffer, Howard Hughes
Medical Institute

abstracts and .ppt slides of talks
-

http://cadlab.cs.ucla.edu/nsf09/

Keynote Talks

The Brave New Old World of Design Automation Research
, Ralph Cavin Bill Joyner Wally Rhines

Future IT Infrastructure Research Challenges: An HP Labs View
, Prith Banerjee


Invited Talks

The Future of Electronic Design Automation: Methodology, Tools and Solutions
, Sharad Malik,

EDA
-

Electronic Design Automation or Electronic Design Assistance?
, Andreas Kuehlmann,

Front
-
end SoC design: The Neglected Frontier
, Arvind

EDA Challenges in Systems Integration
, Jochen A. G. Jess

Is Today’s Design Methodology a Recipe for a "Tacoma Narrows" Incident?
, Carl Seger

Statistical Model Checking of Simulink Models
, Edmund M. Clarke

Deconstructing Concurrency Heisenbugs
, Shaz Qadeer

Test and Validation Challenges in the Late
-
Silicon Era
, Tim Cheng

A Faulty Research Agenda
, Rupak Majumdar

Numerical Modeling and Simulation for EDA: Past, Present and Future
, Jaijeet Roychowdhury

ANALOG CAD: NOT DONE YET
, Rob A. Rutenbar

A Flat Earth for Design and Manufacturing
, Jason Hibbeler

Collaborative Innovation of EDA, Design, and Manufacturing
, Jyuo
-
Min Shyu

From Computability to Simulation, Optimization, and Back
, Igor Markov

Working Around the Limits of CMOS
, Mary Jane Irwin

More Moore’s Law Through Computational Scaling
-

and EDA’s Role
, David Z. Pan

Robotics
-
Based Fabrication and Assay Automation for In Vitro Diagnostics Technologies
, Jim Heath

Synthetic Biology: A New Application Area for Design Automation Research
, Chris Myers

EDA and Biology of the Nervous System
, Lou Scheffer

What is EDA?


methodologies, algorithms and tools
, which assist
and automate the design, verification, and testing
of electronic systems.


a general
methodology for refining

a high
-
level
description down to a detailed physical
implementation for designs ranging from


integrated circuits (including system
-
on
-
chips),


printed circuit boards (PCBs) and


electronic systems.


the
modeling, synthesis, and verification

at every
level of abstraction.

Foundational Areas


Verification/validation, model checking, and
testing


Synthesis (logical and physical) research


Programming language research


Analog and mixed signal design


Non
-
linear model reduction


Key EDA challenges


Scalable design methodologies


synthesis,


validation/verification


New classes of algorithms for scalability


Linear/sub
-
linear algorithms.


Incremental algorithms


Parallel algorithms.


Deterministic algorithms for parallel programs


Design for security


resilient to attacks


Dealing with new technologies


Designing with uncertainty and fragility

EDA Funding comparisons

NSF funding of academic
EDA

research


Computer & Information Science & Engineering (CISE)
($8M
-
$12M)


Electrical, Communications and Cyber Systems (ECCS)
($1
-
$3M)

SRC funding of EDA


$5M/year

SRC and DARPA Focus Research Centers


EDA part


$4
-
5M/year

TOTAL


$18M
-
$25M
/year

Total NSF funding in related areas


CISE
-

$574M/year


ENG
-

$693M/year


Electrical Communication and Cyber
-

$125M/year


Cyber Infrastructure
-

$199M/year


Total


$898M/year

(EDA part ~1.3
-
2%)



Funding Comparisons

Taiwan


SoC $70M/year (~35M is EDA support)


Telecommunications $70M/year


Nanoelectronics $100M/year


Total
$240M/year


EDA part?


35M+/year


* academic grants have only a 5% overhead.

Funding Comparisons

Europe


information and communication technology (ICT)
-

1500M
Euro/year


nanosciences, nanotechnologies, materials and new
production technologies
-

575M Euro/year



Electronics, Microelectronics part of EUREKA Consortium


310M Euro/year


Cluster for Application and Technology Research in Europe
on NanoElectronics


750M Euro/year


ENIAC
-
JRT (500M Euro/year) supported 15 EDA projects


Total


Europe


3,635Euro/year = $5,452M/year


EDA part?

Emerging Areas and EDA technology


Biology

systems


System biology


Synthetic biology


Emerging computing /communication /storage
fabrics and
manufacturing

substrates


Nano and flexible electronics


Analysis, characterization, and potential design of
hybrid
electronic/biological

systems.


Bio
-
neural systems and readouts


Cyber
-
physical

systems.


Smart systems, real time


Datacenter

design and optimization.


Energy and reliability in a dynamic workload


Software


Concurrency and scalability

Educational Challenges

EDA is very broad


what to teach


how to teach it


when to teach it

Need to attract more students


Current EDA Climate


Many EDA companies are hurting financially, and


job opportunities are down.


EDA summer internships are very tight.


Venture capital for start
-
ups in EDA has decreased significantly.


have served as major centers for research and development and employment
of PhDs.


Faculty positions in EDA are tight,


Difficulty in obtaining funding to support research and students.


Student interest in EDA as a career has decreased in recent years.


reduced industrial research efforts in EDA


large system design companies have throttled back on the research
components of their activities.


Transition of academic research to industry is much harder than before.


technologies are more complex


harder to get new ideas into the sophisticated and mature software offered by
EDA vendors.

Some Good News


EDA will not go away and cannot stagnate.


Cooperation between industry researchers and developers and university faculty
and students remains very high


As technology shrinks, the problems get harder, so not less but more EDA activity
is required.


EDA engineers are well paid, apparently better than most other types of engineers.


EDA training in its various disciplines, including complex and large problem solving,
will be valuable as new growth areas come into


Aside from the new emerging hot areas, EDA continues with its own hot areas,


system
-
level design


embedded software


design for manufacturing including lithographic and scaling problems


issues of robustness and unreliable components


parallelism, design and application of many core processors


application of probabilistic methods to enhance scaling of algorithms


new methods for derivative and incremental design.

Recommendations to NSF

Research Programs


new funding for:

1.
mid
-
scale or large
-
scale research efforts that couple design with EDA.

2.
joint research programs between research groups from universities,
commercial EDA companies, and large systems
-
houses.

3.
shared infrastructure for design and design automation.

4.
joint exploration of DA for emerging areas.


cyber
-
physical systems.


architecture and networking programs for data center design and optimization.


software analysis


scalable and more precise large
-
scale analysis,


tools and methodologies to extract and manage concurrency.


system biology and synthetic biology.


DA for emerging computing/communications/storage fabrics and manufacturing
substrates (with Engineering Directorate)

5.
interaction between


DA and theory communities,


DA and mathematical sciences.


Recommendations to NSF

Education Programs

1.
Support for the development of a senior level EDA course.



emphasize the underlying algorithmic and theoretic foundations of EDA


motivate EDA’s breadth and flexibility with specific interesting applications.


materials broadly submitted by many faculties


materials available online.

2.
Support from NSF to develop shared courseware infrastructure in EDA.



Might utilize
connexions

(cnx.org), an open platform for course sharing.

3.
An increased post
-
doc program to alleviate the lack of research positions
for new graduates.



such a program was perhaps part of the stimulus effort, but quite limited and
not specific to EDA.

Recommendations to NSF

Collaboration with Industry

1.
An enhanced program to support longer
-
term faculty/industry interactions
.


seeded by enhanced faculty stays in industry


visits by technical leaders from industry to academia.


enabled by matching NSF and industry contributions.


in Engineering Directorate there is a GOALI program


similar program is needed for CISE.

2.
An enhanced program to support EDA students working summers at
companies.



students physically at the company.


proposals would be joint effort between a faculty member and a company staff
person


could include small start
-
ups.

3.
A program to help faculty members and graduate researchers spin off start
-
ups to commercialize successful research projects
.


similar to an SBIR program but more focused on EDA.


help cross over from a research paper or prototype to first customer adoption,


then VCs or the large EDA companies could take over from there.

4.
A program to help marry faculty to existing start
-
ups
(related to the above).


encourage new ventures in EDA
-
type activities.


Estimated Cost of Recommendations


$10
-
15M/year
NEW

funding


Shared with engineering directorate


More Information

See


http://cadlab.cs.ucla.edu/nsf09/


for both the talks (titles and slides) and report.