Jay Littlefield, Director, Product Strategy & Business Development
Jay is a Product Strategist at Real Intent with over 20 years of design and EDA experience. His primary focus for the past decade has been support and marketing of static verification products. He has a MSEE from Stanford and a MBA from San Jose State.
Drowning in a Sea of Information
March 15th, 2010 by Jay Littlefield, Director, Product Strategy & Business Development
We are a society inundated with information. At no previous time in history has so much data been available to such a wide population with access literally at their fingertips. But information abundance has not necessarily translated into increased actionable knowledge. It seems that we reach a point where the more information we have available, the harder it becomes to make use of it.
I was recently reading an old Scientific American article by Hal Varian, then Dean of the UC Berkeley School of Information Management and Systems1. In this document, Dr. Varian argues that the fundamental limits of human comprehension will prevent the realization of a future “information economy”. He quotes Nobel laureate economist Dr. Herbert A. Simon as saying, “What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention, and a need to allocate that attention efficiently among the overabundance of information sources that might consume it.” Dr. Varian then proceeds to frame his argument that information itself is meaningless without “some way to locate, filter, organize and summarize it.”2
In the 15 years since this article was written, the expanse of information has continued to grow, and formed the basis for the Internet search engine market. Like many people, I have Google as my browser’s home page. This is how I deal with my desire to find relevant information among the vast quantities of data on the internet. It not only helps me when I know up front what I am looking for, but also to help me refine my understanding by highlighting the best representations of the type of information I want to find.
While Internet search engines have provided a step towards Dr. Varian’s vision of information organization, the Electronic Design Automation industry has lagged behind in this ability. Each year designs chase Moore’s Law and the complexity of Integrated Circuits has increased exponentially. But in many ways, EDA tools are still delivering data to design and verification engineers as if we were back in the days of schematic entry. Sure, there have been some advances, such as reporting data based upon design hierarchy instead of flat netlists, but the sheer size of designs produce volumes of data that cannot reasonably be parsed without hitting Dr. Simon’s “poverty of attention”.
One doesn’t need to look too far to see examples of this. Most engineers (especially in EDA) have had the experience of reporting a tool problem to an EDA company, only to have customer support point out a single line in a voluminous log file that explains exactly the reported issue. Does that mean engineers are more careless than previous generations? Not at all, but our predecessors rarely had to deal with log files in the tens of thousands of lines, and “summary reports” longer in length than the United States Constitution. It’s gotten bad enough that many tools now provide engineers with the ability to turn off warning messages they know they don’t care about. Engineers are busy people, with many conflicting requirements for their attention. EDA should be working more on a Google-style model of information delivery – finding information the engineer knows they want fast, and guiding them towards the best representations of cases with which they are not familiar.
At Real Intent, we’ve made information organization a top priority in all our tools. Because our focus is on automating much of the work required to run verification analysis, we take our responsibility for organizing the analysis information seriously. Our lint tools provide more meaningful warnings with less noise, our automatic formal tools classify failures by cause and effect, and our clock domain crossing analysis aims to highlight the source of problems, not the symptoms. Have we achieved the goal of a Google-like repository of information management? Not yet, but we continue to strive towards making it faster and more efficient for our customers to consume the volumes of data and prevent “attention poverty”. We welcome your feedback on how we are doing.
1. Varian, Hal R., “The Information Economy – How much will two bits be worth in the digital marketplace?”, Scientific American, September, 1995, p 200-201, http://people.ischool.berkeley.edu/~hal/pages/sciam.html