Today we are proud to announce the release of VisualGDB 5.3 Preview 3 that introduces a new improved engine for toolchains and BSPs. The new engine completely decouples project settings from toolchain settings, letting you easily switch between different toolchain options and seamlessly open projects on machines that have different toolchain/BSP installation directories.
Clang IntelliSense Improvements in VisualGDB 5.3 Preview 2
Today we are excited to announce the second preview of VisualGDB 5.3 that introduces several improvements to the Clang IntelliSense engine. In this post I will show you the highlights of the new engine. Continue reading Clang IntelliSense Improvements in VisualGDB 5.3 Preview 2
Introducing the new Advanced CMake Project Subsystem
CMake has been getting increasingly popular over the past years due to its simplicity and integration with the modern IDEs. The recently added CMake Server mode made it even more usable, allowing it to share the precise project structure with different IDEs, but if you wanted to actively edit a large project, you would still inevitably have to edit the CMakeLists.txt files manually, making it less intuitive than working with regular Visual Studio projects.
So we decided to bridge this gap and designed a new VisualGDB CMake Project subsystem that lets Visual Studio open Linux CMake projects and treat them just like the normal Visual C++ projects. Continue reading Introducing the new Advanced CMake Project Subsystem
Extracting mbed build settings for offline builds
ARM Mbed is a powerful embedded framework that supports many modern devices and allows creating complex firmware (like USB devices or Bluetooth LE beacons) using easy high-level C++ API. Although mbed comes with a powerful build system that makes sense of the numerous targets and features, it is optimized for the online compiler, so building the projects offline (and debugging them) could be tricky.
So we decided to make a tool that integrates into the Python-based mbed build system, polls it for supported targets, features and libraries and stores the recovered information in a structured XML file that can be used to create Visual Studio projects for various mbed targets. Continue reading Extracting mbed build settings for offline builds
Announcing mbed 5.2 support
Today we are proud to announce full mbed 5.4.2 support in VisualGDB. It comes with a significantly improved integration level compared to the previous beta package:
- Features like Bluetooth LE area can now be easily enabled via the Embedded Frameworks page of VisualGDB Project Properties:
- Softdevices and bootloaders for Nordic nRF5x devices are now seamlessly integrated into the build process.
- Various configurable properties (like the default baud rate) are no longer hardcoded and can be conveniently edited via VisualGDB GUI:
- The codebase is updated to the latest 5.4.2 release.
- We have also added an example for Nordic nRF5x UART-over-Bluetooth LE that works out-of-the-box.
You can download the new mbed package via Tools->VisualGDB Package Manager->Updates.
How We Turned 8 Popular STM32 Boards into Powerful Logic Analyzers
The idea of making a “soft logic analyzer” that will run on top of popular prototyping boards has been crossing my mind since we first got acquainted with the STM32 Discovery and Nucleo boards. The STM32 GPIO is blazingly fast and the built-in DMA controller looks powerful enough to handle high bandwidths. So having that in mind, we spent several months perfecting both software and firmware side and here is what we got in the end.
Capturing the signals
The main challenge when using a microcontroller like STM32 as a core of a logic analyzer is dealing with sampling irregularities. Unlike FPGA-based analyzers, the microcontroller has to share the same resources to load instructions from memory, read/write the program state and capture the external inputs from the GPIO. Given that, it could be tricky for the microcontroller to keep up the sampling frequency perfectly straight and could make the capture very innaccurate. To quantify that, I designed a simple test. The on-board timer was configured to generates series of signals with different characteristics and the DMA was used to record their parameters and compare them with the expected ones:The general idea is that if a test signal is sampled with regular intervals (A), it will always appear as the same repeating sequence of zeroes and ones, while if the sampling becomes sporadic (B), it will quickly introduce observable distortions. Having this methodology mind, we conducted several tests and discovered a few interesting results:
- The STM32 DMA was unexpectedly fast. It can reliably read GPIO inputs every 3th or 4th clock cycle on many devices. For fast boards like STM32F746-Nucleo this means sampling frequencies up to 72 MHz.
- If the CPU is properly stalled for the duration of the sampling, it is extremely precise given that it is configured properly.
Compressing the signals
Sampling the inputs at the maximum speed imposes an important limitation. Once the on-board RAM is filled with the data, the sampling needs to be stopped to transfer the data to the computer. While capturing ~1ms at 72MHz could be sufficient for fast and periodic signals, it could be hard to catch the interesting part if the signal is sparse. To support that, we experimented with doing double-buffered compression: while the DMA was filling half of the buffer with raw samples, the CPU was reading through the other half and doing a very basic compression.
This brought back the challenge of uniform sampling: if the CPU was not just waiting, but actively accessing the memory, the DMA controller had to compete with the CPU for the RAM access and could not keep up the sampling uniform. The key to resolving this was to optimize the memory access patterns of the compression algorithm. Having them spaced far enough apart and lowering the sampling frequency to allow the CPU to keep up brought back very precise sampling at a rate of 6.2-8.4MHz for most boards.
Something in-between
Using the CPU to compress the signal in real time took a heavy toll on the sampling frequency, so we decided to add a mode that will combine the fast sampling frequency and the ability to capture the interesting part of the signal. The classical triggered mode (capturing the data around a chosen event) solved the problem but presented new challenges:
Checking for the trigger would mean not stalling the CPU while the capture was active, and that undoubtedly disrupted the uniform capture pattern. The solution here was to use the external interrupt controller and carefully timing the memory access patterns of the interrupt-related code to avoid interference with the sampling. The result was worth the effort: for most of the boards the triggered mode was significantly faster than the compressed mode. We also added trigger support for the compressed mode that works with slightly lower sampling frequencies.
Continuous mode
Being inspired by the sampling quality in the compressed mode, we decided to try another idea: how far can we go if we setup 3 processes in parallel: sampling the data, compressing it and transferring the compressed part to the computer non-stop? The result was surprisingly good: lowering the sampling frequency to ~6MHz for the fastest boards and playing around with memory access patterns got precise non-stop sampling, so we could record hours of non-stop activity on slower buses like I2C not being limited by the on-chip RAM anymore.
Usability
Having the capture modes figured out and the firmware optimized, we faced the final challenge: how to make a logic analyzer software that will be intuitive, easy to use and scalable at the same time. So we created an tool for viewing the captured signals and started analyzing some real-world hardware interactions and figuring out how to make the process as user-friendly as possible. So here’s what we have found:
Setup and Live Streaming
We wanted to make the process of starting the analyzer and beginning to view signals as easy as possible. If you are concerned why your SPI is not working properly, you probably don’t want to be distracted by downloading the board schematics to figure out how to connect it, or seeing why the ST-Link driver is not being recognized. So we designed the viewer application to be as straight-forward as possible. So after the board is connected and selected in the list, it shows the picture of the board and highlights the signals that can be used as inputs:
Clicking at the signals immediately adds them to the live view, beginning to show the current signal. The frequency is chosen automatically (unless set manually) by first trying to sample the signal as fast as possible, and if it looks slow enough, retrying in the compressed mode.
Viewing Data
One of the first important things we figured out was the importance of easy signal labeling. Having to keeping mind that PB0 is the red cable connected to the SCK signal does not make things easy. So we have added an intuitive way of specifying the signal colors and labels:
We also added a “trigger” column that allows enabling and disabling triggers by just clicking on the corresponding signal as a quick alternative to going deep into capture settings.
While trying to explore several real-world bus interactions, we quickly found that while the clocked buses are easy to observe, counting the pulses and translating the signal view to ones and zeroes is annoying, so we added a special clocked view mode that is activated by selecting a signal that looks like a clock and clicking on the “set as primary clock” button:
This will split the selection into intervals aligned at the clock edges and will automatically annotate all other signals with ‘0’, ‘1’ or ‘X’ depending on their value during that clock cycle:
We also added a similar mode for the asynchronous signals where the selection is split based on time instead of clock edges.
Notes
Another time-consuming process while trying to understand some complex bus interactions was to keep track when one of the transaction ends and another part begins. If the captured frame contained several similar packets, navigating between them and keeping in mind where each part starts could be tricky. So we added a mechanism for annotating arbitrary points in time with color-coded labels and arbitrary descriptions:
Notes can also be used to quickly navigate between events in a large capture file:
Protocol Analyzers
We have also added automatic analyzers for commonly used protocols like UART, SPI, I2S and I2C. Dragging them to the protocol analyzer panel and connecting the inputs automatically replaces the raw view with a higher-level view showing the decoded data:Playing around with the protocol analyzers, we quickly discovered another challenge: displaying the decoded bytes in place of the original signals can only show a small amount of text before it gets zoomed out too much and decoding everything as text makes it hard to see the timings and values of other signals.
So we have combined the best of both approaches by adding the “text view” pane:
The pane shows all the decoded output from the entire frame (or file), allows browsing through it and doing full-text searches and it’s automatically synchronized with the timing view: selecting some characters in the text view will automatically select the corresponding time range and selecting a time range will highlight the characters belonging to it.
Continuous Capture Files
Being able to capture data continuously at ~600KB/s was great, but it presented another challenge. Several minutes of capturing can produce hundreds of megabytes of data and instantly navigating through it, zooming in and out, especially while the recording is still in progress, is tricky. So we designed a special capture file format using a technique roughly resembling image thumbnails that allows looking (and searching) through a huge file while it’s being captured, instantly opening and analyzing large files and remembering notes and protocol analyzer settings when you reopen the file later:
Try it out
After months of resolving hardware and software challenges and tweaking the usability, Analyzer2Go was born. It currently supports 8 popular boards from ST and runs on Windows. Support for more boards and other operating systems is coming soon.
The next step
The hardware is capable. The software is mighty. So go ahead and send us your feedback and suggestions for new boards to support and we will turn your board into a reliable and easy-to-use logic analyzer next!
Introducing Analyzer2Go
Today we are excited to announce a new product that makes embedded development a bit easier.
It is the further evolution of the real-time watch feature that allowed the users of VisualGDB to see the precise timings of their code by automatically instrumenting it. With Analyzer2Go we took this approach even further – now you can use your development board to record, save and analyze digital signals in your design without no special logic analyzer hardware.
We designed Analyzer2Go to be extremely easy-to-use. It will automatically locate your board, install the necessary drivers and upload the necessary firmware. All you need to do is click on the signals on the board picture to immediately see a live data feed:
The Analyzer2Go firmware uses a thoroughly optimized DMA-based capture mode that allows sampling signals at high speeds (e.g. up to 72 MHz on STM32F746-Nucleo) and ran rigorous tests to ensure that the sampling is always properly timed.
We have designed Analyzer2Go to be intuitive and help you focus on the signals you are exploring instead of fighting the tools. Easy navigation for sparse signals, automatic zooming, powerful preview bar, previous frame history, so you can always roll a few frames back if your eye caught something suspicious… We have even added a note mechanism that allows you to easily place color-coded notes attached to different events and time spans, so you can keep a track of the meaning of the observed signals and not just their shape:
For slower signals we added a special continuous capture mode that can record gigabytes of logs continuously into a special optimized format that allows opening and browsing through them quickly no matter how large the log is.
To make it even more fun, we added easy-to-use drag-and-drop protocol analyzers for the UART, SPI, I2S and I2C protocols that support full-text search (optimized fur huge files, of course) and can automatically synchronize the timing view with the decoded data view:Analyzer2Go currently supports 8 popular development boards from ST and we are planning to add support for more.
You can download it here and browse through some step-by-step tutorials on this page.
As always, we will be happy to hear your feedback and suggestions, so feel free to reach as via our support page. Enjoy!
Limitations of the ESP32 debugging
We have just added support for the new ESP32 chip to VisualGDB. While VisualGDB allows building projects, setting breakpoints and debugging your ESP32 code out-of-the-box, the ESP32 tools come with a few known limitations that may interfere with debugging. In this post I will summarize them and show known workarounds.
Exploring advanced STM32 code samples with VisualGDB
Today we have released VisualGDB 5.2 Beta 4. Among various small improvements and optimizations it now allows automatically browsing and experimenting with over 3000 detailed code samples for the STM32 microcontrollers included in the STM32 CubeMX software libraries.
Continue reading Exploring advanced STM32 code samples with VisualGDB
VisualGDB 5.2 Beta 1 is out
Today we are proud to release VisualGDB 5.2 Beta 1. Aside from seamless unit test support for Embedded, Linux and Android projects, better Clang IntelliSense engine, Real-time Watch and a new MSBuild backend, it includes numerous usability improvements that make the development experience more streamlined and removes some annoying distractions. Let’s have a quick look through the main changes.