Tag Archives: ARM based Cortex M7

Digital audio recording “you” with quality and ease


Instamic wants to do for microphones what the GoPro did for cameras. 


Many analog years ago, digital recorded audio won the popularity contest. Nowadays, whether it’s from your mobile phone, infotainment system or personal audio device, every sound you hear is from digitally encoded bits.

Digital audio has eliminated all of the analog audio’s distortions and noise-related problems. Quite simply, people are shaped and drawn to recorded audio, ranging from music producers, to creative artist, to the everyday consumer. It’s in these moments for the user, high-quality audio conveys clarity in the recording moments. In today’s user interfaces, from media and podcasts to tablets, many whizzing bits are streaming a world of information including audio — readily available at every reach of a finger or ear.

The Miracle of Sound all Around US

More and more, we are seeing the prolific expansion and seamless integration of the stack. What does this all mean, though? Screen time now captivates us, while voice recognition and audio are blended into the user pathways of UX. Spurring from technology, we see popular apps like Evernote and iOS/Android natively adopting audio recording right within its inherent interface. These apps are taking in the voice user input to also drive UX — cleverly weaving experience, intention, outcome, commenting and moments.

Almost every sound you hear coming out of a speaker is digitally sampled and encoded.  Moment upon moment of keynotes stored are recorded more, albeit in the format of video or audio, we are seeing an increasing number of unique use cases to why one would want to capture a particular moment. These moments offer an on-demand periscope — referencing a historic timeline of ripples in our experience, memory, and journey through work, life, play, and what matters most to us.

referencing a historic timeline of ripples in our experience

For much of our pleasures, sound is always in digital — whether it’s on your smartphone, computer, radio, television, home theater or in a concert hall. Today, across many electronic devices, audio recording is integral transition to many advanced features applied toward enhancing old ways of doing things. Just take a look at visual voicemail, and how recording voicemails took the next leap once UX and advance playback was offered. Visual and digital voice recording meshed with non-linear play, took voice playback to the next level. I’d go so far as to point out that most people never hear analog recordings anymore.

Unless you’re a musician, or live with one, virtually all the music you hear live or recorded is digital. We now see the integration of audio and voice recording into all forms of day-to-day activity. Audio with depth is helping bring back some of those analog qualities where the shape and length of a sound wave can be more defined by bit depth and bit sampling rate. With these 24-bit audio embedded designs and digital audio recordings, we can also achieve better sound quality more akin to what our ear can register and decode, help bringing forth the finer granular details of high fidelity. But it’s not all about just emitting fidelity via the digital audio recording. The use cases and need to record audio, albeit ourselves or surrounding interactions, is helpful for many use cases (musician during creative process, senior suffering stages of memory loss, students seeking catalog of lectures, author recalling and commenting wiring plots during writing process, etc.)lectures and applications for audio recording
Why does bit depth matter, you ask? Bit depth refers to the number of bits you have when a device is capturing audio. Below is a graph showing a series of levels in how bit depth works. There are 65,536 possible levels for 16-bit audio. As for 24-bit, there are 16,777,216 levels. Now, let’s see how the depth is explained. The capturing of audio can be sliced in partitions at any moment in time such as shown in this  graph. To move to higher resolution in audio, every bit added counts toward greater resolution. The deeper the bit depth, the number of levels stack greater audio information, layering richer context to the profile of the audio being recorded. Altogether, what’s said describes a segment of audio frozen in a single slice or moment of time.

The second integral “high quality” factor is called sample rate. Together, bit depth and sample rate complete the higher resolution audio model. The sample rate represents the number of times your audio is measured or “sampled” per second. The typical standard for CDs, the sample rate is 44.1 kHz or 44,100 slices every second.
bit depth and sample rate explained

Digital audio eliminated all of analog audio’s distortions and noise-related problems. In that sense digital is “perfect.” When analog recordings are copied, there are significant generation-to-generation losses, added distortion and noise; digital-to-digital copies are perfect clones. Some recording engineers believe digital doesn’t have a sound per se, and that it’s a completely transparent recording medium. Analog, with its distortions, noise and speed variations imparts its own sound. Arguably, perfect, it is not. This is why high resolution in audio paired with the best form factor and ease and usability go hand in hand.

As to whether digital composes sounds with better quality than analog, that’s merely a moot point. Digital audio recording and its very nature of having the ability to slice into segments and layer, then import into other applications and change into enhanced or analyzed into wave forms has been remarkable and pivotal for many industries. In fact, we now see results of digital audio having a significant impact when having the ability to vector to angular and distinct wave form shapes as to help identify voices and interpret intelligent voice recognition. These encoding factors coupled with deep learning programmatic layers are ushering in a new era of digital interpretation and digital recognition.Instamic-every-day-use
Despite such a proposal of questionable technical and audible merits, founder of Instamic Michelle Baggio apparently moved ahead with the idea and recently launched a well-funded Indiegogo campaign for a new audio and player designed to revive factors of instant usability and simplicity that has been squeezed out of digital recording. Thoughts and experience can now be easily captured or reduced to a series of moments, but it is in this very reason for being captured that one can traverse thoughts by memorable experience to episode, so we as users can stitch what’s most meaningful to formulate a mosaic of audio recordings to help serve a purpose.  Whether it’s for applications in medical, academics, business, music or film, the list goes on and on… even a victim of memory impairment can find good use for Instamic.

Instamic isn’t just an ordinary microphone. It happens to be the smartest, smallest and most affordable digital audio recorder that is also easy to operate, combining usability with the smartphone. It attained over 2,500+ backers and crowdfunding exceeding 539% its original campaign goal. With that many backers and goals funded beyond expectations, there are good market/application factors yielding wider acceptance and adoption of more and more of these audio recording tools. Instamic can function as the day-to-day voice logging tool of choice.go-pro-likeness-recording-revolution
We have now leaped into the “Recording Revolution.” GoPro had an effect on the video revolution, opening up a periscope and view into so many never before seen vantage points. Previously, only a number of people had access to seeing. Adventures and passions of people, shared from around the world into showcases for all to experience what they had seen. Giving an eagle’s eye into the experience of many, providing a viewport into those that would never have seen amazing video capture. The recording revolution is upon us and will grow. Instamic is a mic build and made for everyone. Not only is this recording device at 24-bit, the sample rate matches industry high resolution standards at 96khz sample rate. That’s right, based on the aforementioned bit sampling description, that puts the recording at high resolution of 96,000 slices of audio sampled per second.

Instamic Pro and Instamic

Instamic records at 96khz/24-bit, having both mono and dual-mono while its Pro version even boasts stereo recording. This simple but advance digital recorder features omnidirectional polar pattern. Omnidirectional polar pattern records and performs ideally based on its small form factor. A peek inside reveals the architecture of quickly including minimal-phase digital filtering, zero-feedback circuitry, one of the “best sounding” DAC -nabled chips available with dual 2Msps, 12-bit DAC and analog comparator, and an all-discrete output buffer.

Instamic has the ideal form factor — it’s tiny and can be virtually attached to anything. As a standalone recorder, given the right price and origin of this idea, it can very well replace conventional handheld and lavaliere microphones. Packed with mounting options (magnet, velcro and tape) and a quick release clip, the super portable gadget can register hours of 48khz/24-bit sound in mono and dual mono mode, as well as in stereo quality with its Pro variant. A built-in, rechargeable battery allows for roughly four hours of uncompressed audio recording, with duration varying slightly depending on charge time, temperature and storage conditions.

Instamic has a frequency response of 50 to 18,000Hz. Try doing this with current smartphones or other devices, and batteries will drain quick. Then, recording is sensitive having a frequency response of 50 to 18,000Hz. Instamic crams big recording power into a small form factor which is highly usable because it can be tucked into anything. Simplicity seems to always rule the day especially when it comes to electronic devices looking to shape or better the way we do things in a day to day basis. What the GoPro did for cameras, this gadget wants to do for microphones.

What the GoPro did for cameras, this gadget wants to do for microphones

Given its compact design and minimal setup, Instamic is the perfect accessory for filmmakers, journalists and musicians as they will no longer need to lug around all that bulky, obtrusive equipment. Eliminating the need for cables, the wearable unit connects to its accompanying app over Bluetooth and enables users to control it remotely within a 30-foot radius, as well as simultaneously record with multiple Instamics. What’s more, the mic has been designed with the latest Atmel | SMART SAM 70S MCU, comprising 2GB to 8GB internal memory.

Turning on the pocket-sized device requires a single tap of its logo, while another touch will begin the recording. From there, Instamic will automatically adjust the gain on its own in the first 10 seconds and will ensure that it remains at the optimal level. Tap and hold again for a second and it will stop. If paired with a smartphone, Instamic can also be controlled through its app. When a user needs to transfer a recording to their desktop, its microUSB charging port doubles as the file transfer system. Instamic comes in two models: Pro and Go. The Pro version’s waterproof, black shell makes it a suitable instrument for indoor filming sets, darker environments and even in five feet of water. Meanwhile, the splash-resistant, white Instamic exterior of the Go can remain inconspicuous in most bright, day-lit settings. Both can camouflage easily with custom design covers and handle the most windy conditions wearing Instamic Windshield.Easy USB Charging and 4 hour use and recording
How is this being done inside? Intrigued? You can head over to its Indiegogo page to delve a bit deeper. This Bay Area-based startup has already met its crowdfunding goals and now quickly developing their products with the Atmel SMART | SAM S70, a high-performance ARM Cortex-M7 core-based MCU running up to 300MHz. The MCU comes with analog capability, fitting 12-bit ADCs of up to 24 channels with analog front end, offering offset error correction and gain control, as well as hardware averaging up to 16-bit resolution. SAM S70 also includes 2-channel, 2Msps, 12-bit DAC.

But that’s not all. It’s combined with high-capacity memory with up to 2MB Flash and 384kB SRAM and DSP encoding capabilities (DSP functionality that can be further grown into its roadmap). DSP features can be broadly extended well into its product roadmap. Even more is to happen, inclusive in the roadmap is the SAM S70 MCU doing the encoding and decoding of the audio signals, enhanced with its ability to process deterministic code execution and truly expand on the stereo quality functionality packed with Omnidirectional polar pattern, providing the best quality mapping and single processing for an mcu, outputting workhorse processing power of an MPU.  This 32-bit ARM Cortex M7 processor also features a floating point unit (FPU).  Now with quality mapped to bit depth and bit sampling, the number crunching math required to compute an enormous layers of bits is astounding

The FPU further bolsters high quality audio by executing float point processing to render audio temporarily in a 32 bit floating point format. The recorders will render audio temporarily while the extra bits are added onto the file after recording to allow generous headroom for audio mathematics in the digital domain in memory.  Before the file is output it will go through the 24 bit converters. “Floating point” scales the decimal point in a calculation and processing even more so. Furthermore, having 32 rather than 24 registers for calculations is going to render increasingly accurate result. With strings of only 24 numbers, it would be theoretically impossible to allow for other extensive calculations. Yet, when the data hits the 24-bit converter 8 bits are “truncated” or cut off.  The said mathematical result is simply more accurate and as a result, we get high resolution output of the audio.

Instamic’s MEMS microphones offer a breakthrough innovation in sound sensing. Having sound recorded with an omnidirectional microphone response (similar to sound studio environments) is generally considered to be a perfect sphere in three dimensions. The smallest diameter gives the best omni-directional characteristics at high frequencies. Yes, indeed there’s always something new to learn. This is the compelling reason that makes the MEMS microphone the best mmni-directional microphone. Industry wise, MEMS microphones are entering new application areas such as voice-enabled gaming, automotive voice systems, acoustic sensors for industry and security applications, and medical telemetry. What was once unthinkable early on, the unique construction of the MEMs microphone combined with performance and form factor make it all possible.

Instamic Pro Features and Functionality

instamic-pro-spec

MEMS Microphone Specifications

instamic-mems-microphone

Recorder Specifications

spec-recorder-instamic

Frequency Response Specifications

spec-frequency-instamic

Comparison Specifications

spec-specification-table-instamic-comparison

Comparisons at Scale

spec-comparisons-scale

Once again, Instamic originally stems from the well-funded pool of contributing patrons. The community has supported and validated this product’s potential for an ideal application to market fit. With this said, the demand is real. Shoot for the stars, right? Powered by Atmel’s latest Cortex-M7, Instamic is looking to become a household name when it comes to capturing high-quality sound anywhere, at anytime, on anything.

Are you designing for the latest automotive embedded system?


Eventually, self-driving cars will arrive. But until then, here’s a look at what will drive that progression.


The next arrow of development is set for automotive

We all have seen it. We all have read about it in your front-center technology news outlets. The next forefront for technology will take place in the vehicle. The growing market fitted with the feature deviation trend does not appeal to the vision of customizing more traditional un-connected, oiled and commonly leveraged chassis vehicles of today. Instead, ubiquity in smartphones have curved a design trend, now mature while making way for the connected car platform. The awaiting junction is here for more integration of the automotive software stack.  Opportunities for the connected car market are huge, but multiple challenges still exist. Life-cycles in the development of automotive and the mobile industry are a serious barrier for the future of connected cars. Simply, vehicles take much longer to develop than smartphones other portable gadgetry. More integration from vendors and suppliers are involved with the expertise to seamlessly fit the intended blueprint of the design. In fact, new features such as the operating system are becoming more prevalent, while the demand for sophisticated and centrally operated embedded systems are taking the height of the evolution. This means more dependence on integration of data from various channels, actuators, and sensors — the faculty to operate all the new uses cases such as automatic emergency response systems are functionality requiring more SoC embedded system requirements.

A step toward the connected car - ecall and how it works

What is happening now?

People. Process. Governance. Adoption. Let’s look at the similarities stemmed from change. We are going to witness new safety laws and revised regulations coming through the industry. These new laws will dictate the demand for connectivity. Indeed, drawing importance this 2015 year with the requirement set by 2018, European Parliament voted in favor of eCall regulation. Cars in Europe must be equipped with eCall, a system that automatically contacts emergency services directing them to the vehicle location in the event of an emergency. The automotive and mobile industries have different regional and market objectives. Together, all the participants in both market segments will need to find ways to collaborate in order to satisfy consumer connectivity needs. Case in point, Chrysler has partnered with Nextel to successfully connect cars like their Dodge Viper, while General Motors uses AT&T as its mobile development partner.

General Motors selected AT&T as its mobile partner

What is resonating from the sales floor and customer perspective?

The demand is increasing for more sophistication and integration of software in the cabin of cars. This is happening from the manufacturer to the supplier network then to the integration partners — all are becoming more engaged to achieve the single outcome, pacing toward the movement to the connected car. Stretched as far as the actual retail outlets, auto dealers are shifting their practice to be more tech savvy, too. The advent of the smart  vehicle has already dramatically changed the dealership model, while more transformation awaits the consumer.

On the sales floor as well as the on-boarding experience, sales reps must plan to spend an hour or more teaching customers how to use their car’s advanced technology. But still, these are only a few mentioned scenarios where things have changed in relation to cars and how they are sold and even to the point of how they are distributed, owned, and serviced. One thing for certain, though, is that the design and user trend are intersecting to help shape the demand and experience a driver wants in the connected car. This is further bolstered by the fast paced evolution of smartphones and the marketing experiences now brought forth by the rapid adoption and prolific expansion of the mobile industry tethered by their very seamless and highly evolved experiences drawn from their preferred apps.

Today, customer experiences are becoming more tailored while users, albeit on the screen or engaged with their mobile devices are getting highly acquainted with the expectation of “picking up from where I left off” regardless of what channel, medium, device, or platform.  Seamless experiences are breaking through the market.  We witness Uber, where users initialize their click on their smartphone then follows by telemetry promoted from Uber drivers and back to the users smart phone.  In fact, this happens vis versa, Uber driver’s have information on their console showing customer location and order of priority.  Real life interactions are being further enhanced by real-time data, connecting one device to draw forth another platform to continue the journey.  Transportation is one of the areas where we can see real-time solutions changing our day-to-day engagement.  Some of these are being brought forth by Atmel’s IoT cloud partners such as PubNub where they leverage their stack in devices to offer dispatch, vehicle state, and geo fencing for many vehicle platforms.  Companies like Lixar, LoadSmart, GetTaxi, Sidecar, Uber, Lyft are using real-time technologies as integral workings to their integrated vehicle platforms.

The design trajectory for connected cars continues to follow this arrow forward

Cars are becoming more of a software platform where value chain add-ons tied to an ecosystem are enabled within the software tethered by the cloud where data will continue to enhance the experience. The design trajectory for connected cars follow this software integration arrow.  Today, the demand emphasizes mobility along with required connectivity to customer services and advanced functions like power management for electric vehicles, where firmware/software updates further produce refined outcomes in the driver experience (range of car, battery management, other driver assisted functionalities).

Carmakers and mobile operators are debating the best way to connect the car to the web. Built-in options could provide stronger connections, but some consumers prefer tethering their existing smartphone to the car via Bluetooth or USB cable so they can have full access to their personal contacts and playlists. Connected car services will eventually make its way to the broader car market where embedded connections and embedded systems supporting these connections will begin to leverage various needs to integrate traditional desperate signals into a more centrally managed console.

Proliferation of the stack

The arrow of design for connected cars will demand more development, bolstering the concept that software and embedded systems factored with newly-introduced actuators and sensors will become more prevalent. We’re talking about “software on wheels,” “SoC on wheels,” and “secured mobility.”

Design wise, the cost-effective trend will still remain with performance embedded systems. Many new cars may have extremely broad range of sensor and actuator‑based IoT designs which can be implemented on a single compact certified wireless module.

The arrow for connected cars will demand more development bolstering the concept that software and embedded systems factored with newly introduced actuators & sensors will become more prevalent; “software on wheels”, “SoC on wheels” and “secured mobility”.

Similarly, having fastest startup times by performing the task with a high-performance MCU vs MPU, is economic for a designer. It can not only reduce significant bill of materials cost, development resources, sculpted form factor, custom wireless design capabilities, but also minimize the board footprint. Aside from that, ARM has various IoT device development options, offering partner ecosystems with modules that have open standards. This ensures ease of IoT or connected car connectivity by having type approval certification through restrictive access to the communications stacks.

Drivers will be prompted with new end user applications — demand more deterministic code and processing with chips that support the secure memory capacity to build and house the software stack in these connected car applications.

Feature upon feature, layer upon layer of software combined with characteristics drawn from the events committed by drivers, tires, wheels, steering, location, telemetry, etc. Adapted speed and braking technologies are emerging now into various connected car makes, taking the traditional ABS concept to even higher levels combined with intelligence, along with controlled steering and better GPS systems, which will soon enable interim or cruise hands-free driving and parking.

Connected Car Evolution

Longer term, the technological advances behind the connected car will eventually lead to self-driving vehicles, but that very disruptive concept is still far out.

Where lies innovation and change is disruption

Like every eventual market disruption, there will be the in-between development of this connected car evolution. Innovative apps are everywhere, especially the paradigm where consumers have adopted to the seamless transitional experiences offered by apps and smartphones. Our need for ubiquitous connectivity and mobility, no matter where we are physically, is changing our vehicles into mobile platforms that want us users to seamlessly be connected to the world. This said demand for connectivity increases with the cost and devices involved will become more available. Cars as well as other mobility platforms are increasingly becoming connected packages with intelligent embedded systems. Cars are offering more than just entertainment — beyond providing richer multimedia features and in-car Internet access.  Further integration of secure and trusted vital data and connectivity points (hardware security/processing, crypto memory, and crypto authentication) can enable innovative navigation, safety and predictive maintenance capabilities.

Carmakers are worried about recent hacks,  especially with issues of security and reliability, making it unlikely that they will be open to every kind of app.  They’ll want to maintain some manufactured control framework and secure intrusion thwarting with developers, while also limiting the number of apps available in the car managing what goes or conflicts with the experience and safety measures.  Importantly, we are taking notice even now. Disruption comes fast, and Apple and others have been mentioned to enter this connected car market. This is the new frontier for technological equity scaling and technology brand appeal. Much like what we seen in the earlier models of Blackberry to smartphones, those late in the developmental evolution of their platforms may be forced adrift or implode by the market.

No one is arguing it will happen. Eventually, self-driving cars will arrive.  But for now, it remains a futuristic concept.

What can we do now in the invention, design and development process?

The broader output of manufactured cars will need to continue in leveraging new designs that take in more integration of traditional siloed integration vendors so that the emergence of more unified and centrally managed embedded controls can make its way. Hence, the importance now exists in the DNA of a holistically designed platform fitted with portfolio of processors and security to take on new service models and applications.

This year, we have compiled an interesting mixture of technical articles to support the development and engineering of car access systems, CAN and LIN networks, Ethernet in the car, capacitive interfaces and capacitive proximity measurement.

In parallel to the support of helping map toward the progress and evolution of the connected car, a new era of design exists. One in which the  platform demands embedded controls to evenly match their design characteristics and application use cases. We want to also highlight the highest performing ARM Cortex-M7 based MCU in the market, combining exceptional memory and connectivity options for leading design flexibility. The Atmel | SMART ARM Cortex-M7 family is ideal for automotive, IoT and industrial connectivity markets. These SAM V/E/S family of microcontrollers are the industry’s highest performing Cortex-M microcontrollers enhancing performance, while keeping cost and power consumption in check.

So are you designing for the latest automotive, IoT, or industrial product? Here’s a few things to keep in mind:

  • Optimized for real-time deterministic code execution and low latency peripheral data access
  • Six-stage dual-issue pipeline delivering 1500 CoreMarks at 300MHz
  • Automotive-qualified ARM Cortex-M7 MCUs with Audio Video Bridging (AVB) over Ethernet and Media LB peripheral support (only device in the market today)
  • M7 provides 32-bit floating point DSP capability as well as faster execution times with greater clock speed, floating point and twice the DSP power of the M4

We are taking the connected car design to the next performance level — having high-speed connectivity, high-density on-chip memory, and a solid ecosystem of design engineering tools. Recently, Atmel’s Timothy Grai added a unveiling point to the DSP story in Cortex-M7 processor fabric. True DSPs don’t do control and logical functions well; they generally lack the breadth of peripherals available on MCUs. “The attraction of the M7 is that it does both — DSP functions and control functions — hence it can be classified as a digital signal controller (DSC).” Grai quoted the example of Atmel’s SAM V70 and SAM V71 microcontrollers are used to connect end-nodes like infotainment audio amplifiers to the emerging Ethernet AVB network. In an audio amplifier, you receive a specific audio format that has to be converted, filtered, and modulated to match the requirement for each specific speaker in the car. Ethernet and DSP capabilities are required at the same time.

“The the audio amplifier in infotainment applications is a good example of DSC; a mix of MCU capabilities and peripherals plus DSP capability for audio processing. Most of the time, the main processor does not integrate Ethernet AVB, as the infotainment connectivity is based on Ethernet standard,” Grai said. “Large SoCs, which usually don’t have Ethernet interface, have slow start-up time and high power requirements. Atmel’s SAM V7x MCUs allow fast network start-up and facilitate power moding.”

Atmel has innovative memory technology in its DNA — critical to help fuel connected car and IoT product designers. It allows them to run the multiple communication stacks for applications using the same MCU without adding external memory. Avoiding external memories reduces the PCB footprint, lowers the BOM cost and eliminates the complexity of high-speed PCB design when pushing the performance to a maximum.

Importantly, the Atmel | SMART ARM Cortex-M7 family achieves a 1500 CoreMark Score, delivering superior connectivity options and unique memory architecture that can accommodate the said evolve of the eventual “SoC on wheels” design path for the connected car.

How to get started

  1. Download this white paper detailing how to run more complex algorithms at higher speeds.
  2. Check out the Atmel Automotive Compilation.
  3. Attend hands-on training onboard the Atmel Tech on Tour trailer. Following these sessions, you will walk away with the Atmel | SMART SAM V71 Xplained Ultra Evaluation Kit.
  4. Design the newest wave of embedded systems using SAM E70, SAM S70, or SAM V70 (ideal for automotive, IoT, smart gateways, industrial automation and drone applications, while the auto-grade SAM V70 and SAM V71 are ideal for telematics, audio amplifiers and advanced media connectivity).

IMG_3659

[Images: European Commission, GSMA]

How to prevent execution surprises for Cortex-M7 MCU


We know the heavy weight linked with software development, in the 60% to 70% of the overall project cost.


The ARM Cortex-A series processor core (A57, A53) is well known in the high performance market segments, like application processing for smartphone, set-top-box and networking. If you look at the electronic market, you realize that multiple applications are cost sensitive and don’t need such high performance processor core. We may call it the embedded market, even if this definition is vague. The ARM Cortex-M family has been developed to address these numerous market segments, starting with the Cortex-M0 for lowest cost, the Cortex-M3 for best power/performance balance, and the Cortex-M4 for applications requiring digital signal processing (DSP) capabilities.

For the audio, voice control, object recognition, and complex sensor fusion of automotive and higher-end Internet of Things sensing, where complex algorithms for audio and video are needed for rich audio and visual capabilities, Cortex-M7 is required. ARM offers the processor core as well as the Tightly Coupled Memory (TCM) architecture, but ARM licensees like Atmel have to implement memories in such a way that the user can take full benefit from the M7 core to meet system performance and latency goals.

Figure 1. The TCM interface provides a single 64-bit instruction port and two 32-bit data ports.

The TCM interface provides a single 64-bit instruction port and two 32-bit data ports.

In a 65nm embedded Flash process device, the Cortex-M7 can achieve a 1500 CoreMark score while running at 300 MHz, offering top class DSP performance: double-precision floating-point unit and a double-issue instruction pipeline. But algorithms like FIR, FFT or Biquad need to run as deterministically as possible for real-time response or seamless audio and video performance. How do you best select and implement the memories needed to support such performance? If you choose Flash, this will require caching (as Flash is too slow) leading to cache miss risk. Whereas SRAM technology is a better choice since it can be easily embedded on-chip and permits random access at the speed of processor.

Peripheral data buffers implemented in general-purpose system SRAM are typically loaded by DMA transfers from system peripherals. The ability to load from a number of possible sources, however, raises the possibility of unnecessary delays and conflicts by multiple DMAs trying to access the memory at the same time. In a typical example, we might have three different entities vying for DMA access to the SRAM: the processor (64-bit access, requesting 128 bits for this example) and two separate peripheral DMA requests (DMA0 and DMA1, 32-bit access each). Atmel has get round this issue by organizing the SRAM into several banks as described in this picture:

Figure 2. By organizing the SRAM into banks, multiple DMA bursts can occur simultaneously with minimal latency.

By organizing the SRAM into banks, multiple DMA bursts can occur simultaneously with minimal latency.

For a chip maker designing microcontrollers, licensing ARM Cortex-M processor core provides numerous advantages. The very first is the ubiquity of the ARM core architecture, being adopted in multiple market segments to support variety of applications. If this chip maker wants to design-in a new customer, the probability that such OEM has already used ARM-based MCU is very high, and it’s very important for this OEM to be able to reuse existing code (we know the heavy weight linked with software development, in the 60% to 70% of the overall project cost). But this ubiquity generates a challenge: how do you differentiate from the competition when competitors can license exactly the same processor core?

Selecting a more aggressive technology node and providing better performance at lower cost are an option, but we understand that this advantage can disappear as soon as the competition also move to this node. Integrating larger amount of Flash is another option, which is very efficient if the product is designed on a technology that enables it to keep the pricing low enough.

If the chip maker has designed on an aggressive technology node for higher performance and offers a larger amount of Flash than the competition, it may be enough differentiation. Completing with the design of a smarter memory architecture unencumbered by cache misses, interrupts, context swaps, and other execution surprises that work against deterministic timing allow bringing strong differentiation.

Pic

If you want to more completely understand how Atmel has designed this SMART memory architecture for the Cortex-M7, I encourage you to read this white paper from Jacko Wilbrink and Lionel Perdigon entitled “Run Blazingly Fast Algorithms with Cortex-M7 Tightly Coupled Memories.” (You will have to register.) This paper describes MCUs integrating SRAM organized into four banks that can be used as general SRAM and for TCM, showing one example of a Cortex-M7 MCU being implemented in the Atmel | SMART SAM S70, SAM E70 and SAM V70/V71 families.


This post has been republished with permission from SemiWiki.com, where Eric Esteve is a principle blogger, as well as one of the four founding members of the site. This blog was originally shared on August 6, 2015.

4 designs tips for AVB in-car infotainment


AVB is clearly the choice of several automotive OEMs, says Gordon Bechtel, CTO, Media Systems, Harman Connected Services.


Audio Video Bridging (AVB) is a well-established standard for in-car infotainment, and there is a significant amount of activity for specifying and developing AVB solutions in automobiles. The primary use case for AVB is interconnecting all devices in a vehicle’s infotainment system. That includes the head unit, rear-seat entertainment systems, telematics unit, amplifier, central audio processor, as well as rear-, side- and front-view cameras.

The fact that these units are all interconnected with a common, standards-based technology that is certified by an independent market group — AVnu — is a brand new step for the automotive OEMs. The AVnu Alliance facilitates a certified networking ecosystem for AVB products built into the Ethernet networking standard.

Figure 1 - AVB is an established technology for in-car infotainmentAccording to Gordon Bechtel, CTO, Media Systems, Harman Connected Services, AVB is clearly the choice of several automotive OEMs. His group at Harman develops core AVB stacks that can be ported into car infotainment products. Bechtel says that AVB is a big area of focus for Harman.

AVB Design Considerations

Harman Connected Services uses Atmel’s SAM V71 microcontrollers as communications co-processors to work on the same circuit board with larger Linux-based application processors. The software firm writes codes for customized reference platforms that automotive OEMs need to go beyond the common reference platforms.

Based on his experience of automotive infotainment systems, Bechtel has outlined the following AVB design dos and don’ts for the automotive products:

1. Sub-microsecond accuracy: Every AVB element on the network is hooked to the same accurate clock. The Ethernet hardware should feature a time stand to ensure packet arrival in the right order. Here, Bechtel mentioned the Atmel | SMART SAM V71 MCU that boasts screen registers to ensure advanced hardware filtering of inbound packets for routing to correct receive-end queues.

2. Low latency: There is a lot of data involved in AVB, both in terms of bit rate and packet rate. AVB allows low latency through reservations for traffic, which in turn, facilitate faster packet transfer for higher priority data. Design engineers should carefully shape the data to avoid packet bottlenecks as well as data overflow.

Figure 2 - Bechtel

Bechtel once more pointed to Atmel’s SAM V71 microcontrollers that provide two priority queues with credit-based shaper (CBS) support that allows the hardware-based traffic shaping compliant with 802.1Qav (FQTSS) specifications for AVB.

3. 1588 Timestamp unit: It’s a protocol for correct and accurate 802.1 AS (gPTP) support as required by AVB for precision clock synchronization. The IEEE 802.1 AS carries out time synchronization and is synonymous with generalized Precision Time Protocol or gPTP.

Timestamp compare unit and a large number of precision timer counters are key for the synchronization needed in AVB for listener presentations times and talker transmissions rates as well as for media clock recovery.

4) Tightly coupled memory (TCM): It’s a configurable high-performance memory access system to allow zero-wait CPU access to data and instruction memory blocks. A careful use of TCM enables much more efficient data transfer, which is especially important for AVB class A streams.

It’s worth noting that MCUs based on ARM Cortex-M7 architecture have added the TCM capability for fast and deterministic code execution. TCM is a key enabler in running audio and video streams in a controlled and timely manner.

AVB and Cortex-M7 MCUs

The Cortex-M7 is a high-performance core with almost double the power efficiency of the older Cortex-M4. It features a six-stage superscalar pipeline with branch prediction — while the M4 has a three-stage pipeline.  Bechtel of Harman acknowledged that M7 features equate to more highly optimized code execution, which is important for Class A audio implementations with lower power consumption.

Again, Bechtel referred to the SAM V71 MCUs — which are based on the Cortex-M7 architecture — as particularly well suited for the smaller ECUs. “Rear-view cameras and power amplifiers are good examples where the V71 microcontroller would be a good fit,” he said. “Moreover, the V71 MCUs can meet the quick startup requirements needed by automotive OEMs.”

Figure 3 - Atmel's V71 is an M7 chip for Ethernet AVB networking and audio processing

The infotainment connectivity is based on Ethernet, and most of the time, the main processor does not integrate Ethernet AVB. So the M7 microcontrollers, like the V71, bring this feature to the main processor. For the head unit, it drives the face plate, and for the telematics control, it contains the modem to make calls so echo cancellation is a must, for which DSP capability is required.

Take the audio amplifier, for instance, which receives a specific audio format that has to be converted, filtered and modulated to match the requirement for each specific speaker in the car. This means infotainment system designers will need both Ethernet and DSP capability at the same time, which Cortex-M7 based chips like V71 provide at low power and low cost.

6 memory considerations for Cortex-M7-based IoT designs


Taking a closer look at the configurable memory aspects of Cortex-M7 microcontrollers.


Tightly coupled memory (TCM) is a salient feature in the Cortex-M7 lineup as it boosts the MCU’s performance by offering single cycle access for the CPU and by securing the high-priority latency-critical requests from the peripherals.

Cortex-M7-chip-diagramLG

The early MCU implementations based on the ARM’s M7 embedded processor core — like Atmel’s SAM E70 and S70 chips — have arrived in the market. So it’d be worthwhile to have a closer look at the configurable memory aspects of M7 microcontrollers and see how the TCMs enable the execution of deterministic code and fast transfer of real-time data at the full processor speed.

Here are some of the key findings regarding the advanced memory architecture of Cortex-M7 microcontrollers:

1. TCM is Configurable

First and foremost, the size of TCM is configurable. TCM, which is part of the physical memory map of the MCU, supports up to 16MB of tightly coupled memory. The configurability of the ARM Cortex-M7 core allows SoC architects to integrate a range of cache sizes. So that industrial and Internet of Things product developers can determine the amount of critical code and real-time data in TCM to meet the needs of the target application.

The Atmel | SMART Cortex-M7 architecture doesn’t specify what type of memory or how much memory should be provided; instead, it leaves these decisions to designers implementing M7 in a microcontroller as a venue for differentiation. Consequently, a flexible memory system can be optimized for performance, determinism and low latency, and thus can be tuned to specific application requirements.

2. Instruction TCM

Instruction TCM or ITCM implements critical code with deterministic execution for real-time processing applications such as audio encoding/decoding, audio processing and motor control. The use of standard memory will lead to delays due to cache misses and interrupts, and therefore will hamper the deterministic timing required for real-time response and seamless audio and video performance.

The deterministic critical software routines should be loaded in a 64-bit instruction memory port (ITCM) that supports dual-issue processor architecture and provide single-cycle access for the CPU to boost MCU performance. However, developers need to carefully calibrate the amount of code that need zero-wait execution performance to determine the amount of ITCM required in an MCU device.

The anatomy of TCM inside the M7 architecture

The anatomy of TCM inside the M7 architecture.

3. Data TCM

Data TCM or DTCM is used in fast data processing tasks like 2D bar decoding and fingerprint and voice recognition. There are two data ports (DTCMs) that provide simultaneous and parallel 32-bit data accesses to real-time data. Both instruction TCM and data TCM — used for efficient access to on-chip Flash and external resources — must have the same size.

4. System RAM and TCM

System RAM, also known as general RAM, is employed for communications stacks related to networking, field buss, high-bandwidth bridging, USB, etc. It implements peripheral data buffers generally through direct memory access (DMA) engines and can be accessed by masters without CPU intervention.

Here, product developers must remember the memory access conflicts that arise from the concurrent data transfer to both CPU and DMA. So developers must set clear priorities for latency-critical requests from the peripherals and carefully plan latency-critical data transfers like the transfer of a USB descriptor or a slow data rate peripheral with a small local buffer. Access from the DMA and the caches are generally burst to consecutive addresses to optimize system performance.

It’s worth noting that while system memory is logically separate from the TCM, microcontroller suppliers like Atmel are incorporating TCM and system RAM in a single SRAM block. That lets IoT developers share general-purpose tasks while splitting TCM and system RAM functions for specific use cases.

A single SRAM block for TCM and system memory allows higher flexibility and utilization

A single SRAM block for TCM and system memory allows higher flexibility and utilization.

5. TCM Loading

The Cortex-M7 uses a scattered RAM architecture to allow the MCU to maximize performance by having a dedicated RAM part for critical tasks and data transfer. The TCM might be loaded from a number of sources, and these sources aren’t specified in the M7 architecture. It’s left to the MCU designers whether there is a single DMA or several data loading points from various streams like USB and video.

It’s imperative that, during the software build, IoT product developers identify which code segments and data blocks are allocated to the TCM. This is done by embedding programs into the software and by applying linker settings so that software build appropriately places the code in memory allocation.

6. Why SRAM?

Flash memory can be attached to a TCM interface, but the Flash cannot run at the processor clock speed and will require caching. As a result, this will cause delays when cache misses occur, threatening the deterministic value proposition of the TCM technology.

DRAM technology is a theoretical choice but it’s cost prohibitive. That leaves SRAM as a viable candidate for fast, direct and uncached TCM access. SRAM can be easily embedded on a chip and permits random accesses at the speed of the processor. However, cost-per-bit of SRAM is higher than Flash and DRAM, which means it’s critical to keep the size of the TCM limited.

Atmel | SMART Cortex-M7 MCUs

Take the case of Atmel’s SMART SAM E70, S70 and V70/71 microcontrollers that organize SRAM into four memory banks for TCM and System SRAM parts. The company has recently started shipping volume units of its SAM E70 and S70 families for the IoT and industrial markets, and claims that these MCUs provide 50 percent better performance than the closest competitor.

SAM-E70_S70_BlockDiagram_Lg_929x516

Atmel’s M7-based microcontrollers offer up to 384KB of embedded SRAM that is configurable as TCM or system memory for providing IoT designs with higher flexibility and utilization. For instance, E70 and S70 microcontrollers organize 384KB of embedded SRAM into four ports to limit memory access conflicts. These MCUs allocate 256KB of SRAM for TCM functions — 128 KB for ITCM and DTCM each — to deliver zero wait access at 300MHz processor speed, while the remaining 128KB of SRAM can be configured as system memory running at 150MHz.

However, the availability of an SRAM block organized in the form of a memory bank of 384KB means that both system SRAM and TCM can be used at the same time.The large on-chip SRAM of 384KB is also critical for many IoT devices, since it enables them to run multiple communication stacks and applications on the same MCU without adding external memory. That’s a significant value proposition in the IoT realm because avoiding external memories lowers the BOM cost, reduces the PCB footprint and eliminates the complexity in the high-speed PCB design.

Why do drones love the Atmel SAM E70?


Eric Esteve explains why the latest Cortex-M7 MCU series will open up countless capabilities for drones other than just flying. 


By nature, avionics is a mature market requiring the use of validated system solution: safety is an absolute requirement, while innovative systems require a stringent qualification phase. That’s why the very fast adoption of drones as an alternative solution for human piloted planes is impressive. It took 10 or so years for drones to become widely developed and employed for various applications, ranging from war to entertainment, with prices spanning a hundreds of dollars to several hundreds of thousands. But, even if we consider consumer-oriented, inexpensive drones, the required processing capabilities not only call for high performance but versatile MCU as well, capable of managing its built-in gyroscope, accelerator, geomagnetic sensor, GPS, rotational station, four to six-axis control, optical flow and so on.

Drone-camera-use-cases-for-atmel-sam-e70

When I was designing for avionics, namely the electronic CFM56 motor control (this reactor being jointly developed by GE in the U.S. and Snecma in France, equipping Boeing and Airbus planes), the CPU was a multi-hundred dollar Motorola 68020, leading to a $20 per MIPS cost! While I may not know the Atmel | SMART SAM E70 price precisely — I would guess that it cost a few dollars — what I do I know is that the MCU is offering an excess of 600 DMIPS. Aside from its high performance, this series boasts a rather large on-chip memory size of up to 384KB SRAM and 2MB Flash — just one of many pivotal reasons that this MCU has been selected to support the “drone with integrated navigation control to avoid obstacle and improve stability.”

In fact, the key design requirements for this application were: +600 DMIPS, camera sensor interface, dual ADC and PWM for motor control and dual CAN, all bundled up in a small package. Looking at the block diagram below helps link the MCU features with the various application capabilities: gyroscope (SPI), accelerator (SPI x2), geomagnetic sensor (I2C x2), GPS (UART), one or two-channel rotational station (UART x2), four or six-axis control communication (CAN x2), voltage/current (ADC), analog sensor (ADC), optical flow sensor (through image sensor Interface or ISI) and pulse width modulation (PWM x8) to support the rotational station and four or six-axis speed PWM control.

For those of you who may not know, the SAM E70 is based on the ARM-Cortex M7 — a principle and multi-verse handling MCU that combines superior performance with extensive peripheral sets supporting multi-threaded processes. It’s this multi-thread support that will surely open up countless capabilities for drones other than simply flying.

Atmel | SMART ARM Cortex M7 SAM E70

Today’s drones already possess the ability to soar through the air or stay stationary, snapping pictures or capturing HD footage. That’s already very impressive to see sub-kilogram devices offering such capabilities! However, the drone market is already looking ahead, preparing for the future, with the desire to get more application stacks into the UAVs so they can take in automation, routing, cloud connectivity (when available), 4G/5G, and other wireless functionalities to enhance data pulling and posting.

For instance, imagine a small town tallying a few thousand habitants, except a couple of days or weeks per year because of a special event or holiday, a hundred thousand people come storming into the area. These folks want to feed their smartphone with multimedia or share live experiences by sending movies or photos, most of them at the same time. The 4G/5G and cloud infrastructure is not tailored for such an amount of people, so the communication system may break. Yet, this problem could be fixed by simply calling in drone backup to reinforce the communication infrastructure for that period of time.

While this may be just one example of what could be achieved with the advanced usage of drones, each of the innovative applications will be characterized by a common set of requirements: high processing performance, large SRAM and flash memory capability, and extensive peripheral sets supporting multi-threaded processes. In this case, the Cortex M7 ARM-based SAM E70 MCU is an ideal choice with processing power in excess of 640 DMIPS, large on-chip SRAM (up to 384 KB) and Flash (up to 2MB) capabilities managing all sorts of sensors, navigation, automation, servos, motor, routing, adjustments, video/audio and more.

Intrigued? You’ll want to check out some of the products and design kits below:


This post has been republished with permission from SemiWiki.com, where Eric Esteve is a principle blogger as well as one of the four founding members of SemiWiki.com. This blog first appeared on SemiWiki on July 18, 2015.

3 design hooks of Atmel MCUs for connected cars


The MPU and MCU worlds are constantly converging and colliding, and the difference between them is not a mere on-off switch — it’s more of a sliding bar. 


In February 2015, BMW reported that it patched the security flaw which could allow hackers to remotely unlock the doors of more than 2 million BMW, Mini and Rolls-Royce vehicles. Earlier, researchers at ADAC, a German motorist association, had demonstrated how they could intercept communications with BMW’s ConnectedDrive telematics service and unlock the doors.

security-needs-for-connected-car-by-atmel

BMW uses SIM card installed in the car to connect to a smartphone app over the Internet. Here, the ADAC researchers created a fake mobile network and tricked nearby cars into taking commands by reverse engineering the BMW’s telematics software.

The BMW hacking episode was a rude awakening for the connected car movement. The fact that prominent features like advanced driver assistance systems (ADAS) are all about safety and security is also a testament is that secure connectivity will be a prime consideration for the Internet of Cars.

Built-in Security

Atmel is confident that it can establish secure connections for the vehicles by merging its security expertise with performance and low-power gains of ARM Cortex-M7 microcontrollers. The San Jose, California-based chip supplier claims to have launched the industry’s first auto-qualified M7-based MCUs with Ethernet AVB and media LB peripherals. In addition, this high-end MCU series for in-vehicle infotainment offers the CAN 2.0 and CAN flexible data rate controller for higher bandwidth requirements.

Nicolas Schieli, Automotive MCU Marketing Director at Atmel, acknowledges that security is something new in the automotive environment that needs to be tackled as cars become more connected. “Anything can connect to the controller area network (CAN) data links.”

Schieli notes that the Cotex-M7 has embedded enhanced security features within its architecture and scalability. On top of that, Atmel is using its years of expertise in Trusted Platform Modules and crypto memories to securely connect cars to the Internet, not to mention the on-chip SHA and AES crypto engines in SAM E70/V70/V71 microcontrollers for encryption of data streams. “These built-in security features accelerate authentication of both firmware and applications.”

Crypto

Schieli notes that the Cotex-M7 has embedded enhanced security features within its architecture and scalability. On top of that, Atmel is using its years of expertise in Trusted Platform Modules and crypto memories to securely connect cars to the Internet, not to mention the on-chip SHA and AES crypto engines in SAM E70/V70/V71 microcontrollers for encryption of data streams. “These built-in security features accelerate authentication of both firmware and applications.”

He explained how the access to the Flash, SRAM, core registers and internal peripherals is blocked to enable security. It’s done either through the SW-DP/JTAG-DP interface or the Fast Flash Programming Interface. The automotive-qualified SAM V70 and V71 microcontrollers support Ethernet AVB and Media LB standards, and they are targeted for in-vehicle infotainment connectivity, audio amplifiers, telematics and head control units companion devices.

Software Support

The second major advantage that Atmel boasts in the connected car environment is software expertise and an ecosystem to support infotainment applications. For instance, a complete automotive Ethernet Audio Video Bridging (AVB) stack is being ported to the SAM V71 microcontrollers.

Software support is a key leverage in highly fragmented markets like automotive electronics. Atmel’s software package encompasses peripheral drivers, open-source middleware and real-time operating system (RTOS) features. The middleware features include USB class drivers, Ethernet stacks, storage file systems and JPEG encoder and decoder.

Next, the company offers support for several RTOS platforms like RTX, embOS, Thread-X, FreeRTOS and NuttX. Atmel also facilitates the software porting of any proprietary or commercial RTOS and middleware. Moreover, the MCU supplier from San Jose features support for specific automotive software such as AUTOSAR and Ethernet AVB stacks.

Atmel supports IDEs such as IAR or ARM MDK and Atmel Studio and it provides a full-featured board that covers all MCU series, including E70, V70 and V71 devices. And, a single board can cover all Atmel microcontrollers. Moreover, the MCU supplier provides Board Support Package for Xplained evaluation kit and easy porting to customer boards through board definition file (board.h).

Beyond that, Atmel is packing more functionality and software features into its M7 microcontrollers. Take SAM V71 devices, for example, which have three software-selectable low-power modes: sleep, wait and backup. In sleep mode, the processor is stopped while all other functions can be kept running. While in wait mode, all clocks and functions are stopped but some peripherals can be configured to wake up the system based on predefined conditions. In backup mode, RTT, RTC and wake-up logic are running. Furthermore, the microcontroller can meet the most stringent key-off requirements while retaining 1Kbyte of SRAM and wake-up on CAN.

Transition from MPU to MCU

Cortex-M7 is pushing the microcontroller performance in the realm of microprocessors. MPUs, which boast memory management unit and can run operating systems like Linux, eventually lead to higher memory costs. “Automakers and systems integrators are increasingly challenged in getting performance point breakthrough because they are running out of Flash capacity,” explained Schieli.

On the other hand, automotive OEMs are trying to squeeze costs in order to bring the connected car riches to non-luxury vehicles, and here M7 microcontrollers can help bring down costs and improve the simplification of car connectivity.

The M7 microcontrollers enable automotive embedded systems without the requirement of a Linux head and can target applications with high performance while running RTOS or bare metal implementation. In other words, M7 opens up avenues for automotive OEMs if they want to make a transition from MPU to MCU for cost benefits.

However, the MPU and MCU worlds are constantly converging and colliding, and the difference between them is not a mere on-off switch. It’s more of a sliding bar. Atmel, having worked on both sides of the fence, can help hardware developers to manage that sliding bar well. “Atmel is using M7 architecture to help bridge the gap between microprocessors and high-end MCUs,” Schieli concludes.


Majeed Ahmad is the author of books Smartphone: Mobile Revolution at the Crossroads of Communications, Computing and Consumer Electronics and The Next Web of 50 Billion Devices: Mobile Internet’s Past, Present and Future.