Over the last few years the open-source RISC-V microprocessor has moved from existing only on FPGAs into real silicon, and right now you can buy a RISC-V microcontroller with all the bells and whistles you would ever want. There’s an interesting chip from China called the Sipeed M1 that features a dual-core RISC-V core running at 600MHz, a bunch of I/Os, and because it’s 2019, a neural network processor. We’ve seen this chip before, but now Seeed Studios is selling it as a Raspberry Pi Hat. Is it an add-on board for a Pi, or is it its own standalone thing? Who knows.
The Grove AI Hat for Edge Computing, as this board is called, is built around the Sipeed MAix M1 AI Module with a Kendryte K210 processor. This is a dual-core 64-bit RISC-V chip and it is obviously the star of the show here. In addition to this chip you’ve also got a few Grove headers for digital I/O, I2C, PWM, and a UART. There’s a a USB Type C for power (finally we’re getting away from USB micro power plugs), and of course a 40-pin Raspberry Pi-style header.
This board is essentially a breakout board for the Sipeed M1 chip, which is one of the most interesting new microcontrollers we’ve seen since it launched late last year. There’s a lot of power here, and already people are emulating the Nintendo Entertainment System on this chip with great success. The problem with this chip is that apart from making your own breakout board, there aren’t many options to get it up and running quickly. This is the solution to that; at the very least it’s a Sipeed chip on a board with a power supply, and it’s also a co-processor that can be accessed with Linux and a Raspberry Pi.
Espressif, the company behind the extremely popular ESP8266 and ESP32 microcontrollers has just announced their latest chip. It’s the ESP32-S2. It’s a powerful WiFi-enabled microcontroller, and this one has support for USB OTG.
Compared to the ESP32 we know and love, there are a few differences. The ESP32-S2 uses a single core Xtensa LX7 core running at up to 240 MHz, where the current ESP32 uses either a single or dual core LX6. The differences between these cores is hidden away in marketing speak and press releases, but it appears the LX7 core is capable of many more floating point operations per cycle: apparently 2 FLOPS / cycle for the LX6, but 64 FLOPS / cycle for the LX7. This is fantastic for DSP and other computationally heavy applications. Other features on the chip include 320 kB SRAM, 128 kB ROM, and 16 kB of RTC memory.
Connectivity for the ESP32-S2 is plain WiFi; Bluetooth is not supported. I/O includes 42 GPIOs, 14 capacitive touch sensing IOs, the regular SPI, I2C, I2S, UART, and PWM compliment, support for parallel LCDs, a camera interface, and interestingly full-speed USB OTG support. Yes, the ESP32-S2 is getting USB, let us all rejoice.
Other features include an automatic power-down of the RF circuitry when it isn’t needed, support for RSA and AES256, and plenty of support for additional Flash and SRAMs should you need more memory. The packaging is a 7 mm x 7 mm QFN, so get out the microscope, enhance your calm, and bust out the flux for this one. Engineering samples will be available in June, and if Espressif’s past performance in supplying chips to the community holds true, we should see some projects using this chip by September or thereabouts.
(Banner image is of a plain-old ESP32, because we don’t have any of the new ones yet, naturally.)
Google has promised us new hardware products for machine learning at the edge, and now it’s finally out. The thing you’re going to take away from this is that Google built a Raspberry Pi with machine learning. This is Google’s Coral, with an Edge TPU platform, a custom-made ASIC that is designed to run machine learning algorithms ‘at the edge’. Here is the link to the board that looks like a Raspberry Pi.
This new hardware was launched ahead of the TensorFlow Dev Summit, revolving around machine learning and ‘AI’ in embedded applications, specifically power- and computationally-limited environments. This is ‘the edge’ in marketing speak, and already we’ve seen a few products designed from the ground up to run ML algorithms and inference in embedded applications. There are RISC-V microcontrollers with machine learning accelerators available now, and Nvidia has been working on this for years. Now Google is throwing their hat into the ring with a custom-designed ASIC that accelerates TensorFlow. It just so happens that the board looks like a Raspberry Pi.
We all know CERN as that cool place where physicists play with massive, superconducting rings to smash atoms and subatomic particles to uncover secrets of matter in the Universe. To achieve this aim, they need to do a ton of research in other areas, such as development of special particle detectors.
While such developments are essential to the core research needs of the Centre, they also lead to spinoff applications for the benefit of society at large. One such outcome has been the Medipix Collaborations – a family of read-out chips for particle imaging and detection that can count single photons, allowing X-rays and gamma rays to be converted to electrical signals. It may not be possible for us hackers to get our hands on these esoteric sensors, but these devices are pretty interesting and deserve a closer look. Medipix sensors work like a camera, detecting and counting each individual particle hitting the pixels when its electronic shutter is open. This enables high-resolution, high-contrast, noise hit free images – making it unique for imaging applications.
Some months back, CERN announced the first 3D color X-ray of a human made possible using the Medipix devices. The result is a high-resolution, 3D, color image of not just living structures like bones, muscular tissues and vessels, but metal objects too like the wrist watch, seen in the accompanying photograph. The Medipix sensors have been in development since the 1990’s and are presently in their 4th “generation”. Each chip consists of a top semiconducting sensor array, made from gallium arsenide or cadmium telluride. The charge collected by each pixel is transported to the CMOS ASIC electronics via “bump bonds”. The integration is vertical, with each sensing pixel connected via the bump bond to an analog section followed by a digital processing layer. Earlier versions were limited, by technology, in their tiling ability for creating larger matrices of multiple sensors. They could be abutted on three sides only, with the fourth being used for on-chip peripheral logic and wire-bond pads that permit electronic read-out. The latest Medipix4 Collaboration, still under some development, eliminates this short coming. Through-silicon-via (TSV) technology provides the possibility of reading the chips through copper-filled holes that bring the signals from the front side of the chip to its rear. All communication with the pixel matrix flows through the rear of the chip – the peripheral logic and control elements are integrated inside the pixel matrix.
The Analog front end consists of a pre-amplifier followed by a window discriminator which has upper and lower threshold levels. The discriminator has four bits for threshold adjustment as well as polarity sensing. This allows the capture window to be precisely set. The rest of the digital electronics – multiplexers, shift registers, shutter and logic control – helps extract the data.
Further development of the Medipix (Tech Brief, PDF) devices led to a separate version called Timepix (Tech Brief, PDF). These new devices, besides being able to count photons, are capable of two additional modes. The first mode records “Time-Over-Threshold”, providing rough analog information about the energy of the photon. It does this by counting clock pulses for the duration when the signal stays above the discrimination levels. The other mode, “Time of Arrival”, measures arrival time of the first particle to impinge on the pixel. The counters record time between a trigger and detection of radiation quanta with energy above the discrimination level, allowing time-of-flight applications in imaging.
Besides medical imaging, the devices have applications in space, material analysis, education and of course, high energy physics. Hopefully, in a few years, hackers will lay their hands on these interesting devices and we can get to know them better. At the moment, the Medipix website has some more details and data sheets if you would like to dig deeper. For an overview on the development of such single photon detectors, check out this presentation from CERN – “Single X-Ray Photon Counting Systems: Existing Systems, Systems Under Development And Future Trends” (PDF).
Fully autonomous cars might never pan out, but in the meantime we’re getting some really cool hardware designed for robotic taxicab prototypes. This is the Livox Mid-40 Lidar, a LIDAR module you can put on your car or drone. The best part? It only costs $600 USD.
The Livox Mid-40 and Mid-100 are two modules released by Livox, and the specs are impressive: the Mid-40 is able to scan 100,000 points per second at a detection range of 90 m with objects of 10% reflectivity. The Mid-40 sensor weighs 710 grams and comes in a package that is only 88 mm x 69 mm x 76 mm. The Mid-100 is basically the guts of three Mid-40 sensors stuffed into a larger enclosure, capable of 300,000 points per second, with a FOV of 98.4° by 38.4°.
The use case for these sensors is autonomous cars, (large) drones, search and rescue, and high-precision mapping. These units are a bit too large for a skateboard-sized DIY Robot Car, but a single Livox Mid-40 sensor, pointed downward on a reasonably sized drone could perform aerial mapping
There is one downside to the Livox Mid sensors — while you can buy them direct from the DJI web site, they’re not in production. These sensors are only, ‘Mass-Production ready’. This might be just Livox testing the market before ramping up production, a thinly-veiled press release, or something else entirely. That said, you can now buy a relatively cheap LIDAR module that’s actually really good.
Last year, Jiangsu Yuheng Co., Ltd introduced a new microcontroller. The CH554 is a microcontroller with an E8051 core with a 24 MHz clock, a little more than 1 kB of RAM, and a bit more than 14 kB split between the code and data Flash. In short, it’s nothing too spectacular, but it makes up for that with peripherals. It’s got SPI and ADCs and PWM, UARTs, and even a few capacitive touch channels. It’s also a USB device, with some chips in the series able to function as a USB host. You can buy this chip for a quarter through the usual retailers.
Normally, this isn’t huge news. The 8051 is the most copied microcontroller on the planet, and there are probably billions produced each year. Cheap parts are only cheap if your time is free; you’ll usually spend ages trying to digest the datasheet and get a toolchain up and running. That’s where this chip is a little different. There are multiple efforts to bring an Open Source toolchain to this chip. And they’re doing it in Windows and Linux. Someone really cares about this chip.
The current best option for an SDK for this chip comes from Blinkinlabs, with a port of the CH554 SDK from Keil to SDCC. There are real, working code examples for this chip using an Open Source toolchain. Sure, it might just blink a LED, but it’s there. If you can blink a LED, you can do just about anything from there. Programming the chip happens over USB with the ‘official’ WCHISPTool (Windows) or LibreCH551 (command line). The end result is a completely Open Source toolchain to program and upload a hex file to a cheap chip.
There are a few more chips in the CH554 series, ranging from the CH551 in an SOP-16 package to the CH559 in an LQFP48 package, with more features available as the chips get bigger. It’s an interesting chip, with some somehow implementing a USB hub, and could be a very cool chip for some low-level USB hacking.
After exploring a few random online shops one day, [David] (thanks for sending this in, by the way) ran across a very interesting chip. It’s a dual-core, RISC-V chip running at 400MHz. There’s 6 MB of SRAM on the CPU, and there’s 2MB for convolutional neural network acceleration. There is, apparently, WiFi on some versions. There are already SDKs available on GitHub, and a bare chip costs a dollar or two. Interested? Log in to Taobao, realize Taobao does pre-orders, and all this can be yours.
This is a preorder — because apparently you can do that as a seller on TaoBao, but the Sipeed M1 K210 is available as a ‘core’ board with 72 pins in a one-inch square package, a version with WiFi, or as a complete development board with an OV2640 camera, 2.4 inch LCD, microphone, and onboard USB. There are videos of this chip running a face detection routine. It found Obama.
Over the years we’ve seen a few RISC-V chips given development boards, and you can buy them right now. The HiFive 1 is an exceptionally powerful microcontroller with processing power that puts it right up against the Teensy (which is built around a Freescale chip), but it’s also fairly expensive. We’re not sure the Arduino Cinque (also RISC-V) ever made it to production, but again, expensive. The idea that a RISC-V microcontroller could be available for just a few dollars is very interesting, it even comes with SDKs and utilities to make the chip useful.