NSF WorkshopElectronic Design Automation

Past, Present, and FutureJuly 8-9, 2009

Sankar Basu, Robert Brayton, and Jason Cong,

PurposeThis 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 engineering4. Clarify to outsiders what EDA is

OrganizationFirst 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/

TalksKeynote TalksRalph Cavin and Bill Joyner (SRC),

and Wally Rhines (Mentor Graphics)

Prith Banerjee (HP)Invited TalksSharad Malik, Princeton Andreas Kuehlmann, CadenceArvind, MIT Jochen A. G. Jess, Eindhoven

University (emeritus)Carl Seger, Intel Corp. Edmund M. Clarke, CMU Shaz Qadeer, Microsoft

Tim Cheng, UC Santa BarbaraRupak Majumdar, UC Los AngelesJaijeet Roychowdhury, UC BerkeleyRob A. Rutenbar, CMUJason Hibbeler, IBMJyuo-Min Shyu, National Tsing Hua

University Igor Markov, University of Michigan Mary Jane Irwin, Penn StateDavid 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 TalksThe Brave New Old World of Design Automation Research, Ralph Cavin Bill Joyner Wally RhinesFuture IT Infrastructure Research Challenges: An HP Labs View, Prith Banerjee

Invited TalksThe 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. JessIs Today’s Design Methodology a Recipe for a "Tacoma Narrows" Incident?, Carl Seger Statistical Model Checking of Simulink Models, Edmund M. ClarkeDeconstructing Concurrency Heisenbugs, Shaz Qadeer Test and Validation Challenges in the Late-Silicon Era, Tim ChengA Faulty Research Agenda, Rupak MajumdarNumerical Modeling and Simulation for EDA: Past, Present and Future, Jaijeet RoychowdhuryANALOG CAD: NOT DONE YET, Rob A. RutenbarA Flat Earth for Design and Manufacturing, Jason HibbelerCollaborative Innovation of EDA, Design, and Manufacturing, Jyuo-Min ShyuFrom Computability to Simulation, Optimization, and Back, Igor Markov Working Around the Limits of CMOS, Mary Jane IrwinMore 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 MyersEDA 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 ComparisonsEurope

– 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 NSFResearch 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 Programs1. 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 NSFCollaboration with Industry1. 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

Seehttp://cadlab.cs.ucla.edu/nsf09/for both the talks (titles and slides) and report.