Digital Video Free

Gene Frantz
TI Principal Fellow and Business Development Manager, DSP

Over the last several months, I’ve been working with some of my colleagues to articulate the future of IC architectures. One of the things that is clear, we are no longer in a world where Moore’s law can and should always apply. Here I’m trying to outline why I think that is and look forward to hearing what your thoughts are on the topic.

When following the progression of modern processor architectures, it is possible to see where we may have lost our way. The introduction of the first microprocessor allowed us to process very simple signals in real time. During this time, the array processor and mini-computer were considered the state-of-the-art tools for signal processing and premier choice in the research community. As researchers discovered and developed new signal processing concepts and algorithms, another community of technologists were already on the path to creating the first DSP device. Approximately 20 years after the invention of the transistor, the first commercially available DSPs appeared on the market and dramatically changed the future of the world.

Early work in DSP algorithm implementation focused on reducing the number of multiplications since multiplies were expansive and slow when implemented in hardware. The primary breakthrough of widespread DSP adoption was the addition of a specialized hardware multiplier to the microprocessor. This innovation changed the focus of digital signal processing from reducing the number of multiplies required by an algorithm to instead, optimizing the numbers of necessary multiplies and additions.

Another major facet of the fast evolving DSP architecture was the use Harvard architecture (two busses – one for program memory and one for data memory) rather than Von Neuman architecture (a single bus with program and data sharing the same memory space). To better suit the needs of mathematically intense processors, the two busses of the Harvard architecture were modified to support both program and data memory allowing both busses to feed the multiplier.

To take advantage of the accelerated multiplication capabilities, new instructions were created to bring together the necessary operations to perform a multiply in a single instruction cycle. Later, the accumulate operation was added to create the familiar MAC function.

Further improvements to the DSP architecture followed. Combining the best of both the Harvard and Von Neuman architectures resulted in a multiple bus Von Neuman-style architecture. As IC performance increased, the concept of the Very Long Instruction Word (VLIW) was introduced allowing parallel processing to meet real-time constraints.

Modern architectures continue to press the limits of performance and efficiency through innovations such as deep pipelines, extensive branch prediction technology and advanced instruction sets. These innovations, in turn create new challenges even as they overcome previous limitations, which I plan to discuss in several future blogs.

Gene Frantz
TI Principal Fellow and Business Development Manager, DSP

Over the last several months, many of you have been asking if I were going to start blogging again. So here I am. Fortunately, I have a lot on my mind and look forward to re-engaging with you all. Over the last several months I’ve been traveling, including a recent trip to China. (Here is a picture of me while in China – I’m the one on the right.)

 

I’ve also been to Russia, Israel, Taiwan and other foreign places like Boston to visit MIT (Note that I am on a cruise in the Caribbean as I write this). But, this wasn’t my first year to extensively travel – I have traveled my whole career. One of the skills I have managed to develop is handling jetlag. I can now fly to anywhere in the world without jetlag. Actually this is not totally true. I notice that the first couple of days I am hungry at breakfast time. But after those couple of days I am back to only a cup of coffee (refilled many times) to be all I need. And, before you ask, no, it doesn’t matter which way I fly as I don’t have jetlag when I get home for the most part.

I have said all of this as I think there is a new phenomena happening to us today very similar to jetlag. That new phenomena is what I call “Net lag”. So, just as a term was created to describe the reaction of our bodies to the jet airplane, there needs to be a term to describe the problems that have been created by the Internet.

I am certain you have thought about some of them. For example, we have design teams in TI made up of people from Texas, California, Boston, Japan, India and Europe. Finding a time for weekly team meetings becomes somewhat difficult. Someone has to attend in the middle of their night while others are just awakening, and others are preparing for bed. The best I can tell no one seems to have the luck of the meeting being in the middle of their day.

Other examples

• sending and receiving email
• playing Internet games
• phone calls – we’ve gone from four digit phone numbers to seven to ten. Will we be able to remember phone numbers with more digits that we have on our hands?

This will only get worse with video phones and video conferencing. The idea of virtual teams will spread like wildfire. Employees will be able to live where they want while being an active part of the team.

What will be the casualty of this Net lag phenomena? Our health, our social life and our sense of community? But, of course, there will be great advantages.

So, I’ll stop here with this topic. But I invite you to send me other examples of Net lag and even good stories about it.

Gene Frantz
TI Principal Fellow and Business Development Manager, DSP

Smart, programmable cameras with a high degree of analytical intelligence will be the workhorses that enable the next generation of applications for the security and automotive markets to name just a couple.

Smart cameras will constantly be absorbing, processing and acting on information all around us, so we are free to think about other things. If someone climbs over a fence at 1:00 in the morning, these cameras will be able to distinguish between your teenage son sneaking home or a burglar trying to sneak off with your TV set. In an airport or other public places, they will know if a bag has been left unattended and will contact the appropriate authorities. On the streets, they will reduce the work load on the police force and other emergency services. In our cars they will serve as a security function but will also eventually take over the driving responsibilities. (Read my entry on, “Security vs. Safety and Privacy”)

Currently, when we think of video analytics, we think of a human as the end user. We think in terms of receiving information in a storable size that still contains all the data, of compression and reproduction. But the future of analytics will feature a computer as the end user. In that scenario, compression is no longer an issue and a perfect picture is unimportant – to a machine, a bad pixel is merely a spec of dust to be ignored. Analytics becomes less about data and more about intelligence, and that is a huge step that will require not just technological transition, but sociological transition as well. People may not be quite ready for machines to make important decisions without any human input. (Another good one to read, “Is Technology getting more Personal or Intimate?”)

I think this transition will occur in steps. Take the automotive industry for example. First, we will put cameras in to allow drivers to make better decisions. For instance, a camera can look at a driver’s blind spot and pass along the data of whether a car is there or not. The driver makes a decision about what to do with that data. In the second iteration of the technology, the camera becomes the second opinion on a decision. If I try to change lanes and the camera sees a car in the other lane, it tightens the tension in the steering wheel to let me know there is a potential problem. Third, the camera becomes the leading decision maker and the driver has to option to override it. Ultimately, we will reach a point where the camera is the only opinion and decision maker. (“Is There a Consumer Breaking Point In Terms Of Convergence?” )

Of course, all of this is going to require programmability. Not only because the system has to be instructed in the myriad of decisions it will have to make, but also as a reality of business. We will need cameras that are programmable and able to have the software adapted according to the application, which will continue to evolve with time. But the bottom line is, as long as you have enough programmability, there’s no limit to what you can do. (SoCs Are Answering Demand for Converged and “Architecture or Application?”)

Of course, we humans will need some re-programming as well. We have to be able to trust these cameras and the decisions they make.

But once we do, we will see these smart cameras used in every aspect f our daily lives. They will be used by the department of transportation to detect not only the location of traffic problems, but the root cause. They will be used for every form of security, from facial recognition in airports, to guarding newborn infants in hospitals. They will be used to transform transportation as computers relieve us of the burden of driving, thus ending gridlock, accidents and delays.

The technology will be in place. Are we ready for it as human beings?

This entry may also be found on SemiApps.com