All-Programmable SoC Solution

Anyone creating a complex, powerful digital design may want to turn to a single device that integrates high-speed processing and programmable logic.

In Circuit Cellar’s April issue, columnist Colin O’Flynn explores using the Xilinx Zynq  Z-7020 All Programmable SoC (system-on-a-chip) as part of the Avnet ZedBoard development board.

“I used a Xilinx Zynq SoC device, although Altera offers several flavors of a similar device (e.g., the Cyclone V SoC, the Arria V SoC, and the Arria 10 SoC), and Microsemi offers the SmartFusion2 SoC FPGA,” O’Flynn says in his article. “The Xilinx and Altera devices feature a dual-core ARM Cortex-A9 processor, whereas the Microsemi devices feature a less powerful Cortex-M3 processor. You may not need a dual-core A9 processor, so ‘less powerful’ may be an advantage.”

While O’Flynn’s article introduces the ZedBoard, he notes many of its specifics also apply to the MicroZed board, a less expensive option with a smaller SoC. Xilinx’s Zynq device has many interesting applications made highly accessible through the ZedBoard and MicroZed boards, he says.

O’Flynn’s discussion of the Zynq SoC device includes the following excerpt. (The April issue, which includes O’Flynn’s full article, is available for membership download or single-issue purchase.)

WHERE’S THE BEEF?
Originally, I had planned to describe a complete demo project in this article. I was going to demonstrate how to use a combination of a custom peripheral and some of the hard cores to stream data from a parallel ADC device into DDR memory. But there wasn’t enough room to introduce the tools and cover the demo, so I decided to introduce the Zynq device (using the ZedBoard).

A demo project is available at ProgrammableLogicInPractice.com. Several tutorials for the Zynq device are available at xilinx.com and zedboard.org, so there isn’t any point in duplicating work! I’ve linked to some specific tutorials from the April 2014 post on ProgrammableLogicInPractice.com. Photo 1 shows the hardware I used, which includes a ZedBoard with my custom OpenADC board connected through the I/O lines.

An Avnet ZedBoard is connected to the OpenADC. The OpenADC provides a moderate-speed ADC (105 msps), which interfaces to the programmable logic (PL) fabric in Xilinx’s Zynq device via a parallel data bus. The PL fabric then maps itself as a peripheral on the hard-core processing system (PS) in the Zynq device to stream this data into the system DDR memory.

Photo 1: An Avnet ZedBoard is connected to the OpenADC. The OpenADC provides a moderate-speed ADC (105 msps), which interfaces to the programmable logic (PL) fabric in Xilinx’s Zynq device via a parallel data bus. The PL fabric then maps itself as a peripheral on the hard-core processing system (PS) in the Zynq device to stream this data into the system DDR memory.

FPGA PROCESSOR DESIGN 101
Even if you’re experienced in FPGA design, you may not have used Xilinx tools for processor-specific design. These tools include the Xilinx Platform Studio (XPS) and the Xilinx Software Development Kit (SDK). Before the advent of hard-core processors (e.g., Zynq), there have long existed soft-core processors, including the popular Xilinx MicroBlaze soft processor. The MicroBlaze system is completely soft core, so you can use the XPS tool to define the peripherals you wish to include. For the Zynq device, several hard-core peripherals are always present and you can choose to add additional soft-core (i.e., use the FPGA fabric) peripherals.

In a future article I will discuss different soft-core processor options, including some open-source third-party ones that can be programmed from the Arduino environment. For now, I’ll examine only the Xilinx tools, which are applicable to the Zynq device, along with the MicroBlaze core.

The ARM cores in the Zynq device are well suited to run Linux, which gives you a large range of existing code and tools to use in your overall solution. If you don’t need those tools, you can always run on “bare metal” (e.g., without Linux), as the tools will generate a complete base project for you that compiles and tests the peripherals (e.g., printing “Hello World” out the USART). To give you a taste of this, I’ve posted a demo video of bringing up a simple “Hello World” project in both Linux and bare metal systems on ProgrammableLogicInPractice.com.

The FPGA part of the Zynq device is called the programmable logic (PL) portion. The ARM side is called the processing system (PS) portion. You will find a reference to the SoC’s PL or PS portion throughout most of the tutorials (along with this article), so it’s important to remember which is which!

For either system, you’ll be starting with the XPS software (see Photo 2). This software is used to design your hardware platform (i.e., the PL fabric), but it also gives you some customization of the PS hard-core peripherals.

This is the main screen of the Xilinx Platform Studio (XPS) when configuring a Zynq design. On the left you can see the list of available soft-core peripherals to add to the design. You can configure any of the hard-core peripherals by choosing to enable or disable them, along with selecting from various possible I/O connections. Additional screens (not shown) enable you to configure peripherals addressing information, configure I/O connections for the soft-core peripherals, and connect peripherals to various available extension buses.

Photo 2: This is the main screen of the Xilinx Platform Studio (XPS) when configuring a Zynq design. On the left you can see the list of available soft-core peripherals to add to the design. You can configure any of the hard-core peripherals by choosing to enable or disable them, along with selecting from various possible I/O connections. Additional screens (not shown) enable you to configure peripherals addressing information, configure I/O connections for the soft-core peripherals, and connect peripherals to various available extension buses.

MAKING THE CONNECTION
For example, clicking on the list of hard-core peripherals opens the options dialogue so you can enable or disable each peripheral along with routing the I/O connections. The ZedBoard’s Zynq device has 54 multipurpose I/O (MIO) lines that can be used by the peripherals, which are split into two banks. Each bank can use different I/O standards (e.g., 3.3 and 1.5 V).

Enabling all the peripherals would take a lot more than 54 I/O lines. Therefore, most of the I/O lines share multiple functions on the assumption that every peripheral doesn’t need to be connected. Many of the peripherals can be connected to several different I/O locations, so you (hopefully) don’t run into two peripherals needing the same I/O pin.

Almost all of the peripheral outputs can be routed to the PL fabric as well under the name EMIO, which is a dedicated 64-bit bus that connects to the PL fabric. If you simply wish to get more I/O pins, you can configure these extra pins from within XPS. But you can also use this EMIO bus to control existing cores in your FPGA fabric using peripherals on the Zynq device.

Assume you had an existing FPGA design where you had an FPGA core doing some processing connected to a microcontroller or computer via I2C, SPI, or serial. You could simply connect this core to the appropriate PS peripheral and port the existing code onto the Zynq processor by changing the low-level calls to use the Zynq peripherals. You may eventually wish to change this interface to the peripheral bus, the AMBA Advanced eXtensible Interface (AXI), for better performance. However, using standard peripherals to interface to a PL design can still be useful for many cores for which you have extensive existing code.

The MIO/EMIO pins can even be used in a bit-banging fashion, so if you need a special device or core control logic, it’s possible to quickly develop this in software. You can then move to a hardware peripheral for considerably better performance.

O’Flynn’s article goes on to discuss in greater detail the internal buses, peripherals, and taking a design from hardware to software. For more, refer to Circuit Cellar‘s  April issue and related application notes posted at O’Flynn’s companion site ProgrammableLogicInPractice.com.

Embedded Programming: Rummage Around In This Toolbox

Circuit Cellar’s April issue is nothing less than an embedded programming toolbox. Inside you’ll find tips, tools, and online resources to help you do everything from building a simple tracing system that can debug a small embedded system to designing with a complex system-on-a-chip (SoC) that combines programmable logic and high-speed processors.

Article contributor Thiadmer Riemersma describes the three parts of his tracing system: a set of macros to include in the source files of a device under test (DUT), a PC workstation viewer that displays retrieved trace data, and a USB dongle that interfaces the DUT with the workstation (p. 26).

Thaidmer Riemersma's trace dongle is connected to a laptop and device. The dongle decodes the signal and forwards it as serial data from a virtual RS-232 port to the workstation.

Thaidmer Riemersma’s trace dongle is connected to a laptop and DUT. The dongle decodes the signal and forwards it as serial data from a virtual RS-232 port to the workstation.

Riemersma’s special serial protocol overcomes common challenges of tracing small embedded devices, which typically have limited-performance microcontrollers and scarce interfaces. His system uses a single I/O and keeps it from bottlenecking by sending DUT-to-workstation trace transmissions as compact binary messages. “The trace viewer (or trace “listener”) can translate these message IDs back to the human-readable strings,” he says.

But let’s move on from discussing a single I/0 to a tool that offers hundreds of I/0s. They’re part of the all-programmable Xilinx Zynq SoC, an example of a device that blends a large FPGA fabric with a powerful processing core. Columnist Colin O’Flynn explores using the Zynq SoC as part of the Avnet ZedBoard development board (p. 46). “Xilinx’s Zynq device has many interesting applications,” O’Flynn concludes. “This is made highly accessible by the ZedBoard and MicroZed boards.”

An Avnet ZedBoard is connected to the OpenADC. The OpenADC provides a moderate-speed ADC (105 msps), which interfaces to the programmable logic (PL) fabric in Xilinx’s Zynq device via a parallel data bus. The PL fabric then maps itself as a peripheral on the hard-core processing system (PS) in the Zynq device to stream this data into the system DDR memory.

An Avnet ZedBoard is connected to the OpenADC. (Source: C. O’Flynn, Circuit Cellar 285)

Our embedded programming issue also includes George Novacek’s article on design-level software safety analysis, which helps avert hazards that can damage an embedded controller (p. 39). Bob Japenga discusses specialized file systems essential to Linux and a helpful networking protocol (p. 52).

One of the final steps is mounting the servomotor for rudder control. Thin cords connect the servomotor horn and the rudder. Two metal springs balance mechanical tolerances.

Jens Altenburg’s project

Other issue highlights include projects that are fun as well as instructive. For example, Jens Altenburg added an MCU, GPS, flight simulation, sensors, and more to a compass-controlled glider design he found in a 1930s paperback (p. 32). Columnist Jeff Bachiochi introduces the possibilities of programmable RGB LED strips (p. 66).

ARM mbed Platform for Bluetooth Smart Applications

OLYMPUS DIGITAL CAMERAThe nRF51822-mKIT simplifies and accelerates the prototyping process for Bluetooth Smart sensors connecting to the Internet of Things (IoT). The platform is designed for fast, easy, and flexible development of Bluetooth Smart applications.

The nRF51822 system-on-chip (SoC) combines a Bluetooth v4.1-compliant 2.4-GHz multiprotocol radio with an ARM Cortex-M0 CPU core on a single chip optimized for ultra-low-power operation. The SoC simplifies and accelerates the prototyping process for Bluetooth Smart sensors connecting to the IoT.

The nRF51822-mKIT’s features include a Bluetooth Smart API, 31 pin-assignable general-purpose input/output (GPIO), a CMSIS-DAP debugger, Programmable Peripheral Interconnect (PPI), and the ability to run from a single 2032 coin-cell battery.

Through mbed, the kit is supported by a cloud-based approach to writing code, adding libraries, and compiling firmware. A lightweight online IDE operates on all popular browsers running on Windows, Mac OSX, iOS, Android, and Linux OSes. Developers can use the kit to access a cloud-based ARM RVDS 4.1 compiler that optimizes code size and performance.

The nRF51822-mKIT costs $59.95.

Nordic Semiconductor ASA
www.nordicsemi.com

AMD Embedded G-Series SoC Solution

AvalueThe ECM-KA SBC is powered by the AMD Embedded G-Series 1st generation system-on-chip (SoC) accelerated processing unit (APU) based on 28-nm design technology. The AMD processors are built on Jaguar microarchitecture and integrate Quad-core CPU and next-generation graphics core.

The small-footprint ECM-KA provides extremely low power consumption, high graphic performance, multimedia, and I/O. The SBC is designed for embedded applications including industrial controls and automation, gaming, thin clients, retail/digital signage, SMB storage server, surveillance, medical, communication, entertainment, and data acquisition.

The ECM-KA supports one 204-pin DDR3 SODIMM socket that supports up to 8 GB DDR3 1600 SDRAM. It also supports dual-channel 18-/24-bit LVDS as well as HDMI, LVDS, and VGA multi-display configurations. The I/O deployment includes two SATA III, one mini PCIe, one CF, two USB 3.0, six USB 2.0, two COM, 8-bit DIO, and 2-Gb Ethernet. Multiple OS support including Windows 8, Windows 7, and Linux can be used in various embedded designs.

Contact Avalue for pricing.

Avalue Technology, Inc.
www.avalue.com.tw

A Love of Teaching, a Lifetime of Robotics: An Interview with John Blankenship

John Blankenship

John Blankenship

John Blankenship has spent decades teaching robotics—and written many books on the subject. His love of teaching inspired him to co-develop the RobotBASIC robot programming language. I recently caught up with John to discuss some highlights from his teaching career and what’s next for RobotBASIC—Nan Price, Associate Editor

 NAN: How did you become interested in robotics?

JOHN: As a child, I often saw robots on television but was fully aware that there were no computers capable of making such fictional creations a reality. In the 1970s, microprocessors such as Intel’s 8080 and MOS Technology’s 6502 gave me hope that real robots would eventually become part of our future.

I found I could motivate my students by linking lab projects to robotic topics. For example, instead of just graphing the output from an active filter, I had my students use op-amps to detect an ultrasonic wave so they could later build a ranging sensor. I firmly believe that if you want to motivate students, you must give them projects with a purpose.

 NAN: You spent more than 30 years teaching programming, electronics, and robotics. What did you gain from that experience?

 JOHN: I enjoyed teaching electronics, but I loved teaching programming. Nothing else even comes close to develop critical thinking skills in students. Watching those skills develop was the reason I taught.

After seeing how my hardware robotic projects motivated students, I knew I wanted something similar for my programming classes. Eventually I developed a library of C routines that simulated a simple on-screen robot. What made the simulated robot special is that it supported numerous sensors (an electronic compass, two levels of proximity sensors, a ranging sensor, line detection, beacon detection, color tracking, and more) that enabled students to solve relatively complex, real-world robotics problems without building any hardware.

This structure made programming fun because it gave programming assignments a purpose. Students no longer had to be convinced that it was important to learn the syntax for a loop or how “if” statements controlled flow to make decisions—they wanted to learn details so they could use them to solve the exciting problems being proposed for them. Which would you find more exciting: writing a program to count the number of words in a string or teaching a robot to follow a line? Better yet, imagine motivating students by having a contest to see whose robot could follow a line the fastest.

NAN: How and why did you develop the RobotBASIC programming language?

MINOLTA DIGITAL CAMERA

RobotBASIC can control real robots just as easily as the simulation.

 JOHN: When I retired from teaching I wanted a way for other teachers to utilize a simulated robot to motivate their students. I could have just published my C libraries, but that generally would have limited their use to college classes where C is usually taught. I felt strongly that much younger students needed to be introduced to programming so they could develop not just logical thought, but also an appreciation for math and engineering.

I love the C language (RobotBASIC is written in C), but in my opinion, it is far too cryptic to be used as a first language. I wanted to encase my routines in a BASIC-like language that would enable nearly anyone to program a simulated robot.

I began writing my own language and was reasonably pleased with the initial efforts. I demonstrated the program to a good friend of mine, Samuel Mishal, who is easily the greatest programmer I have ever known. After politely applauding my efforts, he showed me an interpreter he had been working on to help him with a DSP project. His language was very polished and far superior to my work. He integrated my simulator with his interpreter and we named it RobotBASIC.

Even though we planned from start to freely distribute RobotBASIC, we knew teachers could not devote time to learning a language that was just a robot simulator. We began adding new features and capabilities. The more we added, the more excited we became. We started testing the new language by developing robotic behaviors and writing simple video games. Every time we needed something special, we added it to the language.

Figure3

RobotBASIC has all the commands necessary to write simple video games.

RobotBASIC currently has nearly 900 commands and functions—far more than most languages. More importantly though, since there are built-in functions to handle many things programmers normally have to do themselves, the language is very fast for an interpreter.

We felt RobotBASIC was an ideal language for introducing high school students to programming, but we wanted more. We added hardware I/O capabilities and created a wireless protocol that enabled RobotBASIC to control real robots with the same programs that control the simulation. At that point, the language could easily handle college-level projects but we knew the BASIC stigma would be a problem. To help with this, we added the option to use a modified C-style syntax, making it easier for students to transition to C or even Java.

Figure4

This simulation shows the effects of friction on a spring’s movement.

We also decided to address some backward capability by adding legacy-style I/O commands, making it easy to teach basic programming skills to even fifth graders. This enables school systems to utilize RobotBASIC from lower grades through high school without having to teach a new environment when new capabilities are needed. And if the C-style syntax is introduced in the upper grades, students will be better prepared for college programming courses.

 NAN: What are some uses for RobotBASIC?

JOHN: Even though students’ needs were a driving force in our development process, RobotBASIC’s I/O capabilities make it a great language for hobbyists involved with robotics or other electronic-oriented projects. For example, it only takes a few lines of code to gather data from a remote temperature sensor using a wireless link and to transmit that information to another user over the Internet.

RobotBASIC also has many commands that facilitate flicker-free animation and simulation. This means teachers have the option of motivating students by teaching how to write simple video games.

As much as I love the robot simulator, I have to admit that many students get even more excited about animation than they do about robots. The point is that RobotBASIC provides many options.

Figure2

The simulated robot can be programmed to solve a maze.

 NAN: You offer several types of RobotBASIC seminars geared toward children, university students, and robot clubs. You also lead seminars introducing programming and robotics. What do you enjoy most about teaching? What do attendees gain from your seminars?

 JOHN: I love teaching and I especially love showing teachers new ways to motivate their students. I understand that every school and teacher is different and I make sure I satisfy their goals by customizing each and every presentation based on their individual needs. I am always amazed that schools can’t believe that RobotBASIC is totally free. There are no acquisition costs, no upgrade fees, and no licenses—ever! RobotBASIC is free for hobbyists too. Circuit Cellar readers can download a copy from RobotBASIC.org.

 NAN: Are you currently working on or planning any robotics-related projects?

Figure6

The speed and flight path of these darts is controlled with finger movements on a tablet’s touchscreen.

JOHN: Many RobotBASIC users have been asking for a more advanced book on animation and video games. Unfortunately, my work on our new RobotBASIC Robot Operating System (On a Chip) has been monopolizing all my time for the last couple of years. Now that it is finally finished, I have started writing again.  I think the new book will be worth the wait because it also discusses how RobotBASIC can interact with the new Windows 8 sensors (e.g., cameras, compass, accelerometer, touchscreen, etc.) The chapter I am currently working on enables darts to be thrown using finger movements on a tablet’s touchscreen.

NAN: Do you have any advice for Circuit Cellar readers who are considering building their own autonomous robots?

 JOHN: I think the biggest mistake most robot hobbyists make is they spend far too much time constructing a robot before having a detailed understanding of its sensory needs and the algorithms necessary to accomplish their goals. If they would test their ideas first with our simulator, they would have the information necessary to build a platform that can actually meet their needs. Furthermore, they could control their real robot with the very same programs they developed on the simulator.