HeliOS | A community delivered, open source embedded operating system project
kandi X-RAY | HeliOS Summary
kandi X-RAY | HeliOS Summary
HeliOS is an open source embedded operating system that is free for everyone to use. While called an operating system, HeliOS is a multitasking kernel for use in embedded applications. Its rich, fully documented, API allows the user to control every aspect of the system and access kernel services (syscalls) for task (process) management, scheduler management, inter-process communication, memory management, device management (i.e., device drivers) and more while maintaining a tiny footprint for a broad range of low-power embedded devices. HeliOS is also easily customized to fit the user’s specific needs through a single header file /src/config.h. HeliOS supports two multitasking models that can be leveraged concurrently within the same application. The first multitasking model is event-driven. When a task is placed in the "waiting" state, the task will only respond to task events. HeliOS supports two types of task events. The first is direct-to-task notifications, which allow one task to send a notification to another task. In this scenario, the HeliOS scheduler will wake the recipient task and schedule it for execution. After the recipient task clears the direct-to-task notification, the recipient task will returning to "waiting" until another notification is received. The second type of task event is timer based. Task timers can be configured to tell HeliOS to schedule the task to run every so many ticks (typically milliseconds), though task timers should not be confused with application timers (or simply timers) as HeliOS supports both. The second model for multitasking is a conventional cooperative model. In this model, cooperative tasks are always scheduled to run, unless suspended. Additionally, the cooperative model in HeliOS contains a unique scheduler feature that builds on the traditional cooperative model. In most cooperatively scheduled multitasking models, a simple round-robin approach is used (i.e., each task is executed consecutively). However, the HeliOS scheduler uses a “runtime balanced” algorithm for scheduling cooperative tasks. In other words, tasks that consume more runtime are deprioritized (i.e., executed less frequently) in favor of tasks that consume less runtime. This design prevents long running tasks from monopolizing the system’s execution time. Event-driven and cooperatively scheduled tasks run together seamlessly, although event-driven tasks always receive execution priority over cooperatively scheduled tasks. One important aspect of multitasking in HeliOS is it does not rely on context switching. This reduces the need for the user to manage access to shared resources in a “thread safe” way using mutexes and semaphores. This also eliminates the need for the “port” or portability code required to save the context during a context switch. As a result, the user can focus his or her development effort on their specific application without having to contend with concurrent access to shared resources. Like everything in life, there are drawbacks. While a conventional cooperative model spares the user from contending with concurrent access to shared resources, if a task does not relinquish control to the HeliOS scheduler, it will monopolize all available runtime. This also means that the HeliOS scheduler does not enforce hard-timing (i.e., real-time). The HeliOS scheduler enforces soft-timing so if a waiting task timer has elapsed, the scheduler will prioritize the task but may miss the "deadline". HeliOS also provides services for three inter-process communication models. The first, as discussed previously, is direct-to-task notifications. Direct-to-task notifications are an efficient communication channel between tasks that prevent a task from consuming runtime when there is nothing for the task to process. The second model is message queues. Message queues can be created at runtime and can be shared among any number of tasks. Queues are highly flexible FIFO communication channels that require very little code to implement. The third model is stream buffers. Stream buffers are very much like message queues with one important difference. While queues operate on multi-byte messages, stream buffers operate similarly on single-byte streams. Finally, while technically not one of HeliOS’s models for inter-process communication, HeliOS supports task parameters that can be leveraged for rudimentary inter-process communication if so desired. The HeliOS kernel includes built-in memory management that improves the safety margin of dynamically allocated memory. While HeliOS’s dynamic memory allocation allocates “heap” memory, the heap in HeliOS is not a true heap. HeliOS uses a private heap that is implemented as static memory allocated at compile time. HeliOS does not use the standard library malloc() and free() functions and it is recommended that the user also avoid those functions in favor of HeliOS’s memory management syscalls. HeliOS also maintains a separate memory region for kernel objects which reduces the risk that memory access, in the user's application, would corrupt critical kernel objects. As of kernel 0.4.0, HeliOS also supports sophisticated memory defragmentation and consistency checking to ensure memory is utilized efficiently and with a high degree of integrity. HeliOS also supports a kernel mode device driver model. Device drivers for virtually any feature or peripheral can be easily developed using the provided device driver template. While device drivers are not needed in most applications, when the microcontroller's MMU or MPU is enabled it may not be possible to access memory mapped registers and I/O from the user's code. While implementation of the ARM MMU and MPU in HeliOS is forthcoming, device driver support had to be added to HeliOS first. Information about the device driver system calls can be found in the HeliOS Developer's Guide. A device driver template can be found here /drivers/template/driver.c and here /drivers/template/driver.h. HeliOS is built to be robust. HeliOS (0.3.0 and later) has undergone static analysis testing using a commercially licensed static analysis tool as well as MISRA C:2012 checks. While HeliOS is NOT certified for nor should be used (in full or in part) in any safety-critical application where a risk to life exists, user’s can be confident they are building their embedded application on a robust embedded operating system. Lastly, for PlatformIO and Arduino users, HeliOS is easily added to their embedded application. The latest release of HeliOS is available directly through the PlatformIO Registry and the Arduino Library Manager. For users of other embedded platforms and/or tool-chains, simply download the latest release of HeliOS from GitHub and add the sources to your project.
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Trending Discussions on Embedded System
QUESTION
I'm currently writing some code for embedded systems (both in c and c++) and in trying to minimize memory use I've noticed that I used a lot of code that relies on integer promotions. For example (to my knowledge this code is identical in c and c++):
...ANSWER
Answered 2022-Mar-31 at 19:52Your question raises an important issue in C programming and in programming in general: does the program behave as expected in all cases?
The expression (brightness * maxval) / 100
computes an intermediary value brightness * maxval
that may exceed the range of the type used to compute it. In Python and some other languages, this is not an issue because integers do not have a restricted range, but in C, C++, java, javascript and many other languages, integer types have a fixed number of bits so the multiplication can exceed this range.
It is the programmer's responsibility to ascertain that the range of the operands ensures that the multiplication does not overflow. This requires a good understanding of the integer promotion and conversion rules, which vary from one language to another and are somewhat tricky in C, especially with operands mixing signed and unsigned types.
In your particular case, both brightness
and maxval
have a type smaller than int
so they are promoted to int
with the same value and the multiplication produces an int
value. If brightness
is a percentage in the range 0
to 100
, the result is in the range 0
to 25500
, which the C Standard guarantees to be in the range of type int
, and dividing this number by 100
produces a value in the range 0
to 100
, in the range of int
, and also in the range of the destination type uint8_t
, so the operation is fully defined.
Whether this process should be documented in a comment or verified with debugging assertions is a matter of local coding rules. Changing the order of the operands to maxval * brightness / 100
and possibly using more explicit values and variable names might help the reader:
QUESTION
Coming from C/C++ background, I am aware of coding standards that apply for Safety Critical applications (like the classic trio Medical-Automotive-Aerospace) in the context of embedded systems , such as MISRA, SEI CERT, Barr etc.
Skipping the question if it should or if it is applicable as a language, I want to create Python applications for embedded systems that -even vaguely- follow some safety standard, but couldn't find any by searching, except from generic Python coding standards (like PEP8)
Is there a Python coding guideline that specificallly apply to safety-critical systems ?
...ANSWER
Answered 2022-Feb-02 at 08:46Top layer safety standards for "functional safety" like IEC 61508 (industrial), ISO 26262 (automotive) or DO-178 (aerospace) etc come with a software part (for example IEC 61508-3), where they list a number of suitable programming languages. These are exclusively old languages proven in use for a long time, where all flaws and poorly-defined behavior is regarded as well-known and execution can be regarded as predictable.
In practice, for the highest safety levels it means that you are pretty much restricted to C with safe subset (MISRA C) or Ada with safe subset (SPARK). A bunch of other old languages like Modula-2, Pascal and Fortran are also mentioned, but the tool support for these in the context of modern safety MCUs is non-existent. As is support for Python for such MCUs.
Languages like Python and C++ are not even mentioned for the lowest safety levels, so between the lines they are dismissed as entirely unsuitable. Even less so than pure assembler, which is actually mentioned as something that may used for the lower safety levels.
QUESTION
I've been developing in C using eclipse as my IDE in my virtual machine with ubuntu, I've made some progress and I wanted to test them in the real product which is an embedded system using powerpc.
In order to compile that program for our product I use Code::Blocks in Windows but the compiler is a powerpc version of the gcc.
The same code is giving me an error in the powerpc version that doesn't appear in the ubuntu version.
I have two header files gral.h and module_hand.h as follows:
The gral.h file:
...ANSWER
Answered 2022-Mar-17 at 18:30In the gral.h header file, you define profile_t
using typedef
, then you redefine profile_t
with another typedef
in module_hand.h. You should just define the struct PROFILE
in gral_h and include gral.h in module_hand.h.
gral.h:
QUESTION
I'm working on some Linux embedded system at the moment and using Yocto to build Linux distribution for a board.
I've followed Yocto build flow:
- download layers sources
- build image
- flash image into the board or generate SDK.
Everything works great. However I was required to add some changes to local.conf, probably add some *.bbapend files, systemd services and so forth. So, I'm wondering how can save that local changes in case if I'll want to setup a new build machine or current one will be corrupted.
Should I create a custom image or layer that will inherit everything from a board manufacturer one and add changes and functionalities that are needed to me? Or something else?
...ANSWER
Answered 2022-Mar-11 at 08:27Generally when working on a custom project with Yocto, here is what possibly you will need:
First of all, you need to create your custom layer
QUESTION
I have a few large static arrays that are used in a resource constrained embedded system (small microcontroller, bare metal). These are occasionally added to over the course of the project, but all follow that same mathematical formula for population. I could just make a Python script to generate a new header with the needed arrays before compilation, but it would be nicer to have it happen in the pre-processor like you might do with template meta-programming in C++. Is there any relatively easy way to do this in C? I've seen ways to get control structures like while
loops using just the pre-processor, but that seems a bit unnatural to me.
Here is an example of once such map, an approximation to arctan
, in Python, where the parameter a
is used to determine the length and values of the array, and is currently run at a variety of values from about 100 to about 2^14:
ANSWER
Answered 2022-Mar-08 at 22:33Is there any relatively easy way to do this in C?
No.
Stick to a Python script and incorporate it inside your build system. It is normal to generate C code using other scripts. This will be strongly relatively easier than a million lines of C code.
Take a look at M4 or Jinja2 (or PHP) - these macro processors allow sharing code with C source in the same file.
QUESTION
I'm trying to build libc6 with a custom prefix by modifying the prefix=/usr
line in debian/rules
. However, this fails because the patch is applied multiple times. Curiously, patching another file does not result in the same error. I've distilled the failure down to this script:
ANSWER
Answered 2022-Mar-07 at 18:33The debian/rules
directory is special [citation needed] and shouldn't be patched using the usual quilt
commands. You can modify them directly before building the package or use the patch
command (patch -p1
in this case).
QUESTION
This is a time table, columns=hour, rows=weekday, data=subject [weekday x hour]
...ANSWER
Answered 2022-Mar-05 at 16:06Use melt
to flatten your dataframe then pivot_table
to reshape your dataframe:
QUESTION
I need to run numpy in an embedded system that has an ARM SoC, so I cross-compiled Python 3.8.10 and Numpy using arm-linux-gnueabihf-gcc. Then I copied both executables and libraries to the embedded system. But when I try to import numpy I get the following error:
...ANSWER
Answered 2022-Jan-30 at 13:03I found the problem, it was a Python compilation issue. I used the following commands to compile Python and the problem was solved.
QUESTION
I am trying to write a special type handling for array data redundancy. The idea is to define and declare an array globally at compile time with fixed size, but the size is different to each declared array. This is the idea:
...ANSWER
Answered 2022-Jan-28 at 00:00I feel like a solution to this would be one of those macros that consists of two dozen sub-macros, and those solutions always make me decide to solve the problem some other way. Macros can do some things, but they're not a full programming language and so they're limited in what they can do.
I would just write a small utility to convert the raw data to C code and then #include that. You can compile the utility as part of your compilation process and then use it to compile the rest of your code. So your data.txt could just say "test 1 2 3 4 5 6 7" and your utility would output whatever declarations you need.
QUESTION
I am looking for an efficient way of pixel manipulation in python. The goal is to make a python script that acts as virtual desktop for embedded system. I already have one version that works, but it takes more than a second to display single frame (too long).
Refreshing display 5 times per second would be great.
How it works:
- There is an electronic device with microcontroller and display (128x64px, black and white pixels).
- There is a PC connected to it via RS-485.
- There is a data buffer in microcontroller, that represents every single pixel. Lets call it diplay_buffer.
- Python script on PC downloads diplay_buffer from microcontroller.
- Python script creates image according to data from diplay_buffer. (THIS I NEED TO OPTIMIZE)
diplay_buffer is an array of 1024 bytes. Microcontroller prepares it and then displays its content on the real display. I need to display a virtual copy of real display on PC screen using python script.
How it is displayed:
Single bit in diplay_buffer represents single pixel. display has 128x64 pixels. Each byte from diplay_buffer represents 8 pixels in vertical. First 128 bytes represent first row of pixels (there is 64px / 8 pixels in byte = 8 rows).
I use python TK and function img.put() to insert pixels. I insert black pixel if bit is 1 and white if bit is 0. It is very ineffective. Meybe there is diffrent class than PhotoImage, with better pixel capability?
I attach minimum code with sample diplay_buffer. When you run the script, you will see the frame and execution time.
Meybe there would be somebody so helpful to try optimize it? Could you tell me faster way of displaying pixels, please?
denderdale
Sample frame downloaded from uC
And the code (you can easily run it)
...ANSWER
Answered 2022-Jan-22 at 14:05I don't really use Tkinter, but I have read that using put()
to write individual pixels into an image is very slow. So, I adapted your code to put the pixels into a Numpy array instead, then use PIL to convert that to a PhotoImage
.
The conversion of your byte buffer into a PhotoImage
takes around 1ms on my Mac. It could probably go 10-100x faster if you wrapped the three for
loops into a Numba-jitted function but it doesn't seem worth it as it is probably fast enough.
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