One Protocol to Rule Them All!? – #34

The USB Type-C brings a lot of protocols into one physical connector, but is there room for one protocol to handle all our IO needs? Mike Hoffman and Daniel Bogdanoff sit down with high speed digital communications expert Jit Lim to find out.

USB Type-C brings a lot of protocols into one physical connector, but is there room for one protocol to handle all our IO needs? Mike Hoffman and Daniel Bogdanoff sit down with high speed digital communications expert Jit Lim to find out.

 

0:00 This is Jit’s 3rd podcast of the series

1:00 We already have one connector to rule them all with USB Type-C, but it’s just a connector. Will we ever have one specification to rule them all?

2:00 Prior to USB Type-C, each protocol required it’s own connector. With USB TYpe-C, you can run multiple protocols over the same physical connector

3:00 This would make everything more simple for engineers, they would only need to test and characterize one technology.

3:30 Jit proposes a “Type-C I/O”

4:00 Thunderbolt already allows displayport to tunnel through it

4:30 Thunderbolt already has a combination of capabilities. It has a display mode – you can buy a Thunderbolt display. This means you can run data and display using the same technology

6:30 There’s a notion of a muxed signals

7:00 The PHY speed is the most important. Thunderbolt is running 20 Gb/s

7:15 What would the physical connection look like? Will the existing USB Type-C interface work? Currently we already see 80 Gb/s ports (4 lanes) in existing consumer PCs

9:20 Daniel hates charging his phone without fast charging

9:40 The USB protocol is for data transfer, but is there going to be a future USB dispaly protocol? There are already some audio and video modes in current USB, like a PC headset

11:30 Why are we changing? The vision is to plug it in and have it “just work”

12:00 Today, standards groups are quite separate. They each have their own ecosystems that they are comfortable in. So, this is a big challenge for getting to a single spec

13:15 Performance capabilities, like cable loss, is also a concern and challenge

14:00 For a tech like this were to exist, will the groups have to merge? Or, will someone just come out with a spec that obsoletes all of the others?

15:30 Everyone has a cable hoard. Daniel’s is a drawer, Mike’s is a shoebox

16:30 You still have to be aware of the USB Type-C cables that you buy. There’s room for improvement

17:30 Mike wants a world of only USB Type-C connectors and 3.5mm headphone jacks

18:30 From a test and measurement perspective, it’s very attractive to have a single protocol. You’d only have to test at one rate, one time

19:30 Stupid questions

USB 3.2 + Why You Only Have USB Ports On One Side of Your Laptop – #32

USB 3.2 DOUBLES the data transfer capabilities of previous USB specifications, and could mean the end of having USB ports on just one side of your computer. Find out more in today’s electrical engineering podcast with Jit Lim, Daniel Bogdanoff, and Mike Hoffman.

USB 3.2 DOUBLES the data transfer capabilities of previous USB specifications, and could mean the end of having USB ports on just one side of your computer. Find out more in today’s electrical engineering podcast with Jit Lim, Daniel Bogdanoff, and Mike Hoffman.

 

1:00
Jit is the USB and Thunderbolt lead for Keysight.

1:30
USB 3.2 specifications were released Fall 2017 and released two main capabilities.

USB 3.2 doubles the performance of  USB 3.1. You can now run 10Gb/s x2. It uses both sides of the CC connector.

In the x2 mode, both sides of the connectors are used instead of just one.

4:00
The other new part of USB 3.2 is that it adds the ability to have the USB silicon farther away from the port. It achieves this using retimers, which makes up for the lossy transmission channel.

5:00
Why laptops only have USB ports on one side! The USB silicon has to be close to the connector.

6:30
If the silicon is 5 or 6 inches away from the connector, it will fail the compliance tests. That’s why we need retimers.

7:15
USB is very good at maintaining backwards compatibility

The USB 3.0 spec and the USB 3.1 spec no longer exist. It’s only USB 3.2.

The USB 3.2 specification includes the 3.0 and the 3.1 specs as part of them, and acts as a special mode.

9:00
From a protocol layer and a PHY layer, nothing much has changed. It simply adds communication abilities.

9:55
Who is driving the USB spec? There’s a lot of demand! USB Type C is very popular for VR and AR.

12:00
There’s no benefit to using legacy devices with modern USB 3.2 ports.

13:45
There’s a newly released variant of USB Type C that does not have USB 2.0 support. It repurposes the USB 2 pins. It won’t be called USB, but it’ll essentially be the same thing. It’s used for a new headset.

15:20
USB Type C is hugely popular for VR and AR applications. You can send data, video feeds, and power.

17:00
Richie’s Vive has an audio cable, a power cable, and an HDMI cable. The new version, though, has a USB Type-C that handles some of this.

18:00
USB 3.2 will be able to put a retimer on a cable as well. You can put one at each end.

What is a retimer? A retimer is used when a signal traverses a lossy board or transmission line. A retimer acquires the signal, recovers it, and retransmits it.

It’s a type of repeater. Repeaters can be either redrivers or repeaters. A redriver just re-amplifies a signal, including any noise. A retimer does a full data recovery and re-transmission.

21:20
Stupid Questions:
What is your favorite alt mode, and why?
If you could rename Type-C to anything, what would you call it?

 

 

 

Memory, DDR5+, and JEDEC – #24

“It’s a miracle it works at all.” In this electrical engineering podcast, we discuss the state of memory today and it’s inevitable march into the future.

Hosted by Daniel Bogdanoff and Mike Hoffman, EEs Talk Tech is a twice-monthly engineering podcast discussing tech trends and industry news from an electrical engineer’s perspective.

“It’s a miracle it works at all.” Not the most inspiring words from someone who helped define the latest DDR spec. But, that’s the the state of today’s memory systems. Closed eyes and mV voltage swings are the topic of today’s electrical engineering podcast. Daniel Bogdanoff (@Keysight_Daniel) and Mike Hoffman sit down with Perry Keller to talk about the state of memory today and it’s inevitable march into the future.

Agenda:

00:00 Today’s guest is Perry Keller, he works a lot with standards committees and making next generation technology happen.

00:50 Perry has been working with memory for 15 years.

1:10 He also did ASIC design, project management for software and hardware

1:25
Perry is on the JEDEC board of directors

JEDEC is one of the oldest standards body, maybe older than IEEE

1:50 JEDEC was established to create standards for semiconductors. This was an era when vacuum tubes were being replaced by solid state devices.

2:00 JEDEC started by working on instruction set standards

2:15 There are two main groups. A wide bandgap semiconductors group and a memory group.

3:00 Volatile memory vs. nonvolatile memory. An SSD is nonvolatile storage, like in a phone. But if you look at a DIMM in a PC that’s volatile.

3:40 Nonvolatile memory is everywhere, even in light bulbs.

4:00 Even a DRAM can hold its contents for quite some time. JEDEC had discussions about doing massive erases because spooks will try to recover data from it.

DRAM uses capacitors for storage, so the colder they are the longer they hold their charge.

4:45 DRAM is the last vestige of the classical wide single ended parallel bus. “It’s a miracle that it works at all.”

5:30 Perry showed a friend a GDDR5 bus and challenged him to get an eye on it and he couldn’t.

6:10 Even though DDR signals look awful, it depends on reliable data transfer. The timing and clocking is set up in a way to deal with all of the various factors.

7:00 DDR specifications continue to march forward. There’s always something going on in memory.

8:00 Perry got involved with JEDEC through a conversation with the board chairman.

8:35 When DDR started, 144 MT/s (megatransfers per second) was considered fast. But, DDR5 has and end of life goal of 6.5 GT/s on a 80+ bit wide single ended parallel bus.

9:05 What are the big drivers for memory technology? Power. Power is everything. LPDDR – low power DDR – is a big push right now.

9:30 if you look at the memory ecosystem, the big activity is in mobile. The server applications are becoming focused with the cloud, but the new technology and investment is mobile.

10:00 If you look at a DRAM, you can divide it into three major categories. Mainstream PC memory, low power memory, and GDDR. GDDR is graphics memory. The differences are in both power and cost.

For example, LPDDR is static designs. You can clock it down to DC, which you can’t do with normal DDR.

The first DDR was essentially TTL compatible. Now, we’re looking at 1.1V power supplies and voltage swings in the mV.

Semiconductor technology is driving the voltages down to a large degree.

11:45 DRAM and GDDR is a big deal for servers.

A company from China tried to get JEDEC to increase the operating temperature range of DRAMs by 10 C. They fire up one new coal fired power plant per week in China to meet growing demand. They found they could cut it down to only 3 per month with this change in temperature specs.

13:10 About 5 years ago, the industry realized that simply increasing I/O speeds wouldn’t help system performance that much because the core memory access time hasn’t changed in 15 years. The I/O rate has increased, but basically they do that by pulling more bits at once out of the core and shifting them out. The latency is what really hurts at a system level.

14:15 Development teams say that their entire budget for designing silicon is paid for out of smaller electric bills.

15:00 Wide bandgap semiconductors are happy running at very high temperatures. If these temperatures end up in the data centers, you’ll have to have moon suits to access the servers.

16:30 Perry says there’s more interesting stuff going on in the computing than he’s seen in his whole career.

The interface between different levels is not very smooth. The magic in a spin-up disk is in the cache-optimizing algorithms. That whole 8-level structure is being re-thought.

18:00 Von Neumann architectures are not constraining people any more.

18:10 Anything that happens architecturally in the computing world affects and is affected by memory.

22:10 When we move from packaged semiconductors to 3D silicon we will see the end of DDR. The first successful step is called high bandwidth memory, which is essentially a replacement for GDDR5.

23:00 To move to a new DDR spec, you basically have to double the burst size.

Heterogeneous Computing & Quantum Engineering – #17

Learn about parallel computing, the rise of heterogeneous processing (also known as hybrid processing), and quantum engineering in today’s EEs Talk Tech electrical engineering podcast!

Learn about parallel computing, the rise of heterogeneous processing (also known as hybrid processing), and the prospect of quantum engineering as a field of study!

 

Audio link:

00:40

Parallel computing used to be a way of sharing tasks between processor cores.

When processor clock rates stopped increasing, the response of the microprocessor companies was to increase the number of cores on a chip to increase throughput.

01:44

But now, the increased use of specialized processing elements has become more popular.

A GPU is a good example of this. A GPU is very different from an x86 or ARM processor and is tuned for a different type of processing.

GPUs are very good at matrix math and vector math. Originally, they were designed to process pixels. They use a lot of floating point math because the math behind how a pixel  value is computed is very complex.

A GPU is very useful if you have a number of identical operations you have to calculate at the same time.

4:00

GPUs used to be external daughter cards, but in the last year or two the GPU manufacturers are starting to release low power parts suitable for embedded applications. They include several traditional cores and a GPU.

So, now you can build embedded systems that take advantage of machine learning algorithms that would have traditionally required too much processing power and too much thermal power.

 

4:50

This is an example of a heterogeneous processor (AMD) or hybrid processor. A heterogeneous processor contains cores of different types, and a software architect figures out which types of workloads are processed by which type of core.

Andrew Chen (professor) has predicted that this will increase in popularity because it’s become difficult to take advantage of shrinking the semiconductor feature size.

6:00

This year or next year, we will start to see heterogeneous processors (MOOR) with multiple types of cores.

Traditional processors are tuned for algorithms on integer and floating point operations where there isn’t an advantage to doing more than one thing at a time. The dependency chain is very linear.

A GPU is good at doing multiple computations at the same time so it can be useful when there aren’t tight dependency chains.

Neither processor is very good at doing real-time processing. If you have real time constraints – the latency between an ADC and the “answer” returned by the system must be short – there is a lot of computing required right now. So, a new type of digital hardware is required. Right now, ASICs and FPGAs tend to fill that gap, as we’ve discussed in the All about ASICs podcast.

9:50

Quantum cores (like we discussed in the what is quantum computing podcast) are something that we could see on processor boards at some point. Dedicated quantum computers that can exceed the performance of traditional computers will be introduced within the next 50 years, and as soon as the next 10 or 15 years.

To be a consumer product, a quantum computer would have to be a solid state device, but their existence is purely speculative at this point in time.

11:50

Quantum computing is reinventing how processing happens. And, quantum computers are going to tackle very different types of problems than conventional computers.

12:50

There is a catalog on the web of problems and algorithms that would be substantially better on a quantum on a computer than a traditional computer.

13:30

People are creating algorithms for computers that don’t even exist yet.

The Economist estimated that the total spend on quantum computing research is over 1 Billion dollars per year globally. A huge portion of that is generated by the promise of these algorithms and papers. The interest is driven by this.

Quantum computers will not completely replace typical processors.

15:00

Lee’s opinion is that the quantum computing industry is still very speculative, but the upsides are so great that neither the incumbent large computing companies nor the industrialized countries want to be left behind if it does take off.

The promise of quantum computing is beyond just the commercial industry, it’s international and inter-industry. You can find long whitepapers from all sorts of different governments laying out a quantum computing research strategy. There’s also a lot of venture capitalists investing in quantum computing.

17:40

Is this research and development public, or is there a lot of proprietary information out there? It’s a mixture, many of the startups and companies have software components that they are open sourcing and claim to have “bits of physics” working (quantum bits or qbits), but they are definitely keeping trade secrets.

19:50 Quantum communication means space lasers.

Engineering with quantum effects has promise as an industry. One can send photons with entangled states. The Chinese government has a satellite that can generate these photons and send them to base stations. If anyone reads them they can tell because the wave function collapsed too soon.

Quantum sensing promises to develop accelerometers and gyroscopes that are orders of magnitude more sensitive than what’s commercially available today.

21:35

Quantum engineering could become a new field. Much like electrical engineering was born 140 years ago, electronics was born roughly 70 years ago, computer science was born out of math and electrical engineering. It’s possible that the birth of quantum engineering will be considered to be some point in the next 5 years or last 5 years.

23:00

Lee’s favorite quantum state is the Bell state. It’s the equal probability state between 1 and 0, among other interesting properties. The Bell state encapsulates a lot of the quantum weirdness in one snippet of math.

 

 

 

 

 

 

 

Quantum Bits and Cracking RSA – #16

What does a quantum computer look like? What does the future of cyber security hold? We sit down with Lee Barford to discuss.

Hosted by Daniel Bogdanoff and Mike Hoffman, EEs Talk Tech is a twice-monthly engineering podcast discussing tech trends and industry news from an electrical engineer’s perspective

 

How will quantum computing change the future of security? What does a quantum computer look like? Mike and Daniel sit down with Lee Barford to get some answers.

Video Version:

Audio version

Last time we looked at “what is quantum computing” and talked about quantum bits and storing data in superstates.

00:40 Lee talks about how to crack RSA and Shor’s algorithm (wikipedia)

00:50 The history of quantum computing (wiki). The first person to propose it was Richard Feynman in the mid 1960s. There was some interest, but it died out.

In the 1990s, Peter Shor published a paper pointing out that if you could build a quantum computer with certain operational properties (machine code instructions), then you could find one factor of a number no matter how long it is.

Then, he outlined another number of things he would need, like a quantum Fast Fourier Transform (FFT).

Much of the security we use every day is both the RSA public key system and the Diffie Hellman Key Exchange algorithm.

HTTPS connections use the Diffie Hellman Key Exchange algorithm. RSA stands for “really secure algorithm” “Rivest, Shamir, and Adelman.”

4:00

RSA only works if the recipients know each other, but Diffie Hellman works for people who don’t know each other but still want to communicate securely. This is useful because it’s not practical for everyone to have their own RSA keys.

5:00

Factoring numbers that are made up of large prime numbers is the basis for RSA. The processing power required for factoring is too large to be practical. People have been working on this for 2500 years.

6:45

Shor’s algorithm is theoretically fast enough to break RSA. If you could build a quantum computer with enough quantum bits and operate with a machine language cycle time that is reasonable (us or ms), then it would be possible to factor thousand bit numbers.

7:50

Famous professors and famous universities have a huge disparity of opinion as to when a quantum computer of that size could be built. Some say 5-10 years, others say up to 50.

8:45

What does a quantum computer look like? It’s easier to describe architecturally than physically. A quantum computer isn’t that much different from a classical computer, it’s simply a co-processor that has to co-exist with current forms of digital electronics.

9:15

If you look at Shor’s algorithm, there are a lot of familiar commands, like “if statements” and “for loops.” But, quantum gates, or quantum assembly language operations, are used in the quantum processor. (more about this)

10:00

Lee thinks that because a quantum gate operates in time instead of space, the term “gate” isn’t a great name.

10:30

What quantum computers exist today? Some have been built, but with only a few quantum bits. The current claim is that people have created quantum computers with up to 21 quantum bits. But, there are potentially a lot of errors and noise. For example, can they actually maintain a proper setup and hold time?

11:50

Continuing the Schrodinger’s Cat analogy…

In reality, if you have a piece of physics that you’ve managed to put into a superimposed quantum state, any disturbance of it (photon impact, etc.) will cause it to collapse into an unwanted state or to collapse too early.

13:15

So, quantum bits have to be highly isolated from their environments. So, in vacuums or extreme cold temperatures (well below 1 degree Kelvin!).

13:45

The research companies making big claims about the quantity of bits are not using solid state quantum computers.

The isolation of a quantum computer can’t be perfect, so there’s a limited lifetime for the computation before the probability of getting an error gets too high.

14:35

Why do we need a superposition of states? Why does it matter when the superimposed states collapse to one state? If it collapses at the wrong time you’ll get a wrong answer. With Shor’s algorithm it’s easy to check for the right answer. And, you get either a remainder of 0 or your don’t. If you get 0, the answer is correct. The computation only has to be reliable enough for you to check the answer.

16:15

If the probability of getting the right answer is high enough, you can afford to get the wrong answer on occasion.

16:50

The probability of the state of a quantum bit isn’t just 50%, so how do you set the probability of the state? It depends on the physical system. You can write to a quantum bit by injecting energy into the system, for example using a very small number of photons as a pulse with a carefully controlled timing and phase.

18:15

Keysight helps quantum computer researchers generate and measure pulses with metrological levels of precision.

The pulses have to be very carefully timed and correlated with sub nanosecond accuracy. You need time synchronization between all the bits at once for it to be useful.

19:40

What is a quantum bit? Two common kinds of quantum bits are

1: Ions trapped in a vacuum with laser trapping . The ions can’t move because they are held in place by standing waves of laser beams. The vacuum can be at room temperature but the ions are low temperature because they can’t move.

2. Josephson junctions in tank circuits (a coil capacitor) produce oscillations at microwave frequencies. Under the right physical conditions, those can be designed to behave like an abstract two state quantum system. You just designate zero and one to different states of the system.

Probabilities are actually a wrong description, it should be complex quantum amplitudes.

23:00

Josephson junctions were talked about in an earlier electrical engineering podcast discussing SI units.

23:40

After working with quantum computing, it’s common to walk away feeling a lot less knowledgeable.

24:30

Stupid question section:

“If you had Schrodinger’s cat in a box, would you look or not?”

Lee says the cat’s wave function really collapsed as it started to warm up so the state has already been determined.

 

 

What is Quantum Computing?- #15

Learn about the basics of quantum computing and quantum computers from Dr. Lee Barford. We discuss Schrodinger’s cat and more!

Hosted by Daniel Bogdanoff and Mike Hoffman, EEs Talk Tech is a twice-monthlyelectrical engineering podcast discussing tech trends and industry news from an electrical engineer’s perspective.

What is a quantum computer and what is quantum computing? In this week’s episode, Daniel Bogdanoff and Mike Hoffman are joined by quantum computing expert Lee Barford.

Video Version (YouTube):

Audio Only:

0:45 Intro

Lee Barford helps to guide Keysight into the quantum computing business + enables the quantum computing experts at Keysight

 

2:00 The importance of quantum computing

Clock rates in all types of digital processors stopped going up in 2006 due to heating limits

The processor manufacturers realized the need for more parallelism.

Today, Lee helps engineers at Keysight take advantage of this parallelism.

Graphics processors can be used as vector and matrix machines

Bitcoin utilizes this method.

 

6:00 The implications of advancements in quantum computing

Today, there are parts being made with feature size of the digital transistor that are 10, maybe 7 nanometers (depending on who you believe)

So we are heading below 5 nanometers, and there aren’t many unit cells of silicon left at that point. (a unit cell of silicon is 0.5 nanometer)

The uncertainty principle comes into play since there are few enough atoms where quantum mechanical effects will disturb the electronics.

There are many concerns including a superposition of states (Schrodinger’s cat) and low error tolerance.

 

10:20 Is Moore’s law going to fail? 

Quantum computing is one way of moving the computer industry past this barrier

Taking advantage of quantum mechanical effects, engineering with them, to build a new kind of computers that for certain problems, promise to do better than what we currently do.

 

15:20 Questions for future episodes:

What sort of technology goes into a quantum computer?

What’s the current state of experimentation?

What are some of the motivations for funding quantum computing research?

How is Keysight involved in this industry?

What problems is quantum computing aiming to solve?

 

17:30 Using quantum effects to our advantage

Quantum computers likely be used in consumer devices because there has to be a very low temperature and/or a vacuum.

18:00

A quantum computer’s fundamental storage unit is a qubit (quantum bit).  A quantum bit (qubit) can be either 1 or 0 with some finite probability

19:00
A quantum register can store multiple qubits, and when read, have a probability of being either of these numbers. A quantum register can store more than one state at a time, but only one value can be read from the quantum register.

21:00 How does one get a useful value out of a quantum register? You do as much of the computation before reading the state and then read the quantum computers quantum register.

This works because the quantum computer’s either has such a high probability to be correct that you don’t need to verify it, or it’s simple to double check if the answer is correct.

21:00 How do you get the desired value out of a quantum register? You do as much of the computation ahead of time and then read the quantum computers quantum register.

22:30 Quantum computers can factor very large numbers (breaking RSA in cryptography)