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He amassed a vast trove of art and artifacts and built a castle-like repository so the public could see it, partly because his family wasn’t happy with his collecting.

Final Score: 71-53

Let’s face it – the EDA industry needs new people and new ideas. One of the best places to find both is academia, and a presentation at the Cadence Theater at the recent Design Automation Conference (DAC 2015) described collaboration models that are working today.

The presentation was titled “Industry/Academia Engagement Models – From PhD Contests to R&D Collaborations.” It included these speakers, shown from left to right in the photo below:

• Prof. Xin Li, Electrical and Computer Engineering, Carnegie-Mellon University (CMU)
• Chuck Alpert, Senior Software Architect, Cadence
• Prof. Laleh Behjat, Department of Electrical and Computer Engineering, University of Calgary

Alpert, who was filling in for Zhuo Li, Software Architect at Cadence, was the vice chair of DAC 2015 and will be the general chair of DAC 2016 in Austin, Texas. “My team at Cadence really likes to collaborate with universities,” he said. “We’re a big proponent of education because we really need the best and brightest students in our industry.”

Contests Boost EDA Research

One way that Cadence collaborates with academia is participation in contests. “It’s a great way to formulate problems to academia,” Alpert said. “We can have the universities work on these problems and get some strategic direction.”

For example, Cadence has been involved with the annual CAD contest at the International Conference on Computer-Aided Design (ICCAD) since the contest was launched in 2012. This is the largest worldwide EDA R&D contest, and it is sponsored by the IEEE Council on EDA (CEDA) and the Taiwan Ministry of Education. Its goals are to boost EDA research in advanced real-world problems and to foster industry-academia collaboration.

Contestants can participate in one of more problems in the three areas of system design, logic synthesis and verification, and physical design. The 2015 contest has attracted 112 teams from 12 regions. Cadence contributes one problem per year in the logic synthesis area. Zhuo Li was the 2012 co-chair and the 2013 chair. The awards will be given at ICCAD in November 2015.

Another step that Cadence has taken, Alpert said, is to “hire lots of interns.” His own team has four interns at the moment. One advantage to interning at Cadence, he said, is that students get to see real-world designs and understand how the tools work. “It helps you drive your research in a more practical and useful direction,” he said.

The Cadence Academic Network co-sponsors the ACM SIGDA PhD Forum at DAC, and Xin Li and Zhuo Li are on the organizing committee. This event is a poster session for PhD students to present and discuss their dissertation research with people in the EDA community. This year’s forum was “packed,” Alpert said, and it’s clear that the event needs a bigger room.

Finally, Alpert noted, Cadence researchers write and publish technical papers at DAC and other conferences, and Cadence people serve on the DAC technical program committee. “We try to be involved with the academic community on a regular basis,” Alpert said. “We want the best and the brightest people to go into EDA because there is still so much innovation that’s needed. It’s a really cool place to be.”

Research Collaboration Exposes Failure Rates

Xin Li presented an example of a successful research collaboration between CMU and Cadence. The challenge was to find a better way to estimate potential failure rates in memory. As noted in a previous blog post, PhD student Shupeng Sun met this challenge with a new statistical methodology that won a Best Poster award at the ACM SIGDA PhD Forum at DAC 2014.

The new methodology is called Scaled-Sigma Sampling (SSS). It calculates the failure rate and accounts for variability in the manufacturing process while only requiring a few hundred, or a few thousand, sample circuit blocks. Previously, millions of samples were required for an accurate validation of a new design, and each sample could take minutes or hours to simulate. It could take a few weeks or months to run one validation.

The SSS methodology requires greatly reduced simulation times. It makes it possible, Li noted, to run simulations overnight and see the results in the morning.

Li shared his secret for success in collaborations. “I want to emphasize that before the collaboration, you have to understand the goal. If you don’t have a clear goal, don’t collaborate. Once you define the goal, stick to it and make it happen.”

Contest Provides Learning Experience

Last year Laleh Behjat handed two of her new PhD students a challenge. “I told them there is an ISPD [International Symposium for Physical Design] contest on placement, and I expect you to participate and I expect you to win. Not knowing anything about placement, I don’t think they realized what I was asking them.”

The 2015 contest was called the Blockage-Aware Detailed Routing-Driven Placement Contest. Results were announced at the end of March at ISPD. And the University of Calgary team, despite its lack of placement experience, took second place.

Such contests provide a good learning tool, according to Behjat. Graduate students in EDA, she said, “have to be good programmers. They have to work in teams and be collaborative, be able to innovate, and solve the hardest problems I have seen in engineering and science. And they have to think outside the box.” A contest can bring out all these attributes, she said.

Further, Behjat noted, contest participants had access to benchmarks and to a placement tool. They didn’t have to write tools to find out if their results were good. Industry sponsors, meanwhile, got access to good students and new approaches for solving problems.

“You can see Cadence putting a big amount of time, effort and money to get students here and get them excited about doing contests,” she said. She advised students in the theater audience to “talk to people in the Cadence booth and see if you can have more ideas for collaboration.”

Richard Goering

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I have a script to handle many polys in memory in allegro. 

But after the completion of the script, 

I run the axlPolyMemUse(), it reports (31922 0 0 55076 252482)

Seems too many polys are still in the memory，and they are not being used. 

So how to delete these polys from the memory? And reclaim the memory?

BTW. I have no skill dev license. So gc() function doesn't work. 

Thanks.

I have a problem connected with my AXI4 coverage.

I enable coverage collection in AXI4 

      set_config_int("axi4_active_slave_agent_0.monitor.coverModel", "burst_started_enable", 1);
      set_config_int("axi4_active_slave_agent_0.monitor.coverModel", "coverageEnable", 1);

but i don't have a result.

I think the problem in Callback, but i try to connect all callback and i don't have positive result.

Can you help me?

As noted in white papers, posts on the Team Specman Blog, and the Specman documentation, IntelliGen is a totally new stimulus generator than the original "Pgen" and, as a result, there is some amount of effort needed to migrate an existing verification environment to fully leverage the power of IntelliGen.  One of the main steps in migrating code is running the linters on your code and adressing the issues highlighted. 

Included below is a simple utility you can include in your environment that allows you to collect some valuable statistics about your code base to allow you to better gauge the amount of work that might be required to migrate from Pgen to IntelliGen.  The ICFS statistics reported are of particular benefit as the utility not only identifies the approximate number of ICFSs in the environment, it also breaks the total number down according to generation contexts (structs/units and gen-on-the-fly statements) allowing you to better focus your migration efforts. 

IMPORTANT: Sometimes a given environment can trigger a large number of IntelliGen linting messages right off the bat.  Don't let this freak you out!  This does not mean that migration will be a long effort as quite often some slight changes to an environment remove a large number of identified issues.  I recently encountered a situation where a simple change to three locations in the environment, removed 500+ ICFSs!

The methods included in the utility can be used to report information on the following:
- Number of e modules
- Number of lines in the environment (including blanks and comments)
- Number and type of IntelliGen Guidelines linting messages
- Number of Inconsistently Connected Field Sets (ICFSs)
- Number of ICFS contexts and how many ICFSs per context
- Number of soft..select overlays found in the envioronment
- Number of Laces identified in the environment

To use the code below, simply load it before/after loading e-code and then
you can execute any of the following methods:

- sys.print_file_stats()             : prints # of lines and files
- sys.print_constraint_stats()   : prints # of constraints in the environment
- sys.print_guideline_stats()    : prints # of each type of linting message
- sys.print_icfs_stats()            : prints # of ICFSs, contexts and #ICFS/context
- sys.print_soft_select_stats() : prints # of soft select overlay issues
- sys.print_lace_stats()           : *Only works for SPMNv6.2s4 and later* prints # of laces identified in the environment

Each of the above calls to methods produces it's own log files (stored in the current working directory) containing relevant information for more detailed analysis.
- file_stats_log.elog : Output of "show modules" command
- constraint_log.elog : Output of the "show constraint" command
- guidelines_log.elog : Output of "gen lint -g" (with notification set to MAX_INT in order to get all warnings)
- icfs_log.elog       : Output of "gen lint -i" command
- soft_select_log.elog: Output of the "gen lint -s" command
- lace_log.elog       : Output of the "show lace" command

Happy generating!

Corey Goss

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