Hi I am studying computer architecture. We learned that we usually use temporary registser($t) to temporarily store values in registers. However, I saw a data that uses the stack pointer ($sp) to temporarily store the value of the saved register ($s) in the function. Can't we just use temporary register($t) instead of this? I think the stack pointer and the temporary register do the same thing, but I'm curious what exactly is the difference between the two.
Related
I was wondering,
Is there anyway to force writing on a 'Read-Only' Modbus Register?
Does defining a Register as a 'Read-Only' is secure enough or can be bypassed??
Thanks for the answers!
The correct way to define a "read-only" analog variable in Modbus is to map it as an input register. There is no function code defined in Modbus to write to an input register.
For historical reasons, several vendors maps all their variables as holding registers, which are theoretically read/write, i.e, there's a Write Multiple Registers function. Whenever they map a read only variable as a holding register, they must assert that the write functions fail. However, there's no standard exception code for this, as a holding register should be read/write. This is only one of Modbus' idiosyncrasies.
Getting back to your question, if you map your variable as an input register, you can be sure that the protocol will not allow a master to write to it. If, for interoperability issues you map it as a holding register, the protocol will allow the master to use a write funcion to change its value, and it is up to you to block in your device implementation.
Say I have a project which is comprised of:
A main script that handles all of the running of my simulation
Several smaller functions
A couple of structs containing the data
Within the script I will be accessing the functions many times within for loops (some over a thousand times within the minute long simulation). Each function is also looking for data contained with a struct files as part of their calculations, which are usually parameters that are fixed over the course of the simulation, however need to be varied manually between runs to observe the effects.
As typically these functions form the bulk of the runtime I'm trying to save time, as my simulation can't quite run at real-time as it stands (the ultimate goal), and I lose alot of time passing variables/parameters around functions. So I've had three ideas to try and do this:
Load the structs in the main simulation, then pass each variable in turn to the function in the form of a large argument (the current solution).
Load the structs every time the function is called.
Define the structs as global variables.
In terms of both the efficiency of the system (most relevent as the project develops), and possibly as I'm no expert programmer from a "good practise" perspective what is the best solution for this? Is there another option that I have not considered?
As mentioned above in the comments - the 1st item is best one.
Have you used the profiler to find out where you code takes most of its time?
profile on
% run your code
profile viewer
Note: if you are modifying your input struct in your child functions -> this will take more time, but if you are just referencing them then that should not be a problem.
Matlab does what's known as a "lazy copy" when passing arguments between functions. This means that it passes a pointer to the data to the function, rather than creating a new instance of that data, which is very efficient memory- and speed-wise. However, if you make any alteration to that data inside the subroutine, then it has to make a new instance of that argument so as to not overwrite the argument's value in the main function. Your response to matlabgui indicates you're doing just that. So, the subroutine may be making an entire new struct every time it's called, even though it's only modifying a small part of that struct's values.
If your subroutine is altering a small part of the array, then your best bet is to just pass that small part to it, then assign your outputs. For instance,
[modified_array] = somesubroutine(struct.original_array);
struct.original_array=modified_array;
You can also do this in just one line. Conceptually, the less data you pass to the subroutine, the smaller the memory footprint is. I'd also recommend reading up on in-place operations, as it relates to this.
Also, as a general rule, don't use global variables in Matlab. I have not personally experienced, nor read of an instance in which they were genuinely faster.
I need to increment an integer value each time the PLC program is updated to track changes.
There are system events like online_change and before_download, but I have no idea how to implement their functions.
Also I need to save value between updates. I think the tracking variable should be created as RETAIN but not sure.
The variable declaration type should be VAR RETAIN PERSISTENT in your case. Variables declared under RETAIN only will lose their values (intentionally) with a program change.
I believe the builtin Codesys library SysLibProjectInfo.lib has what you are looking for with the function SysGetProjectID. If you store SysGetProjectID as a RETAIN PERSISTENT and then compare against it, you can track changes (or, this unique value may be exactly what you wanted in the first place, without manually creating an ID).
Note: Depending on how you declare your variables, changing the I/O configuration can have unexpected changes even on VAR RETAIN PERSISTENT variables (as all dynamically allocated addresses are shifted and may not point where they used to).
If I understand you you only want to know like what version is running on the PLC and you want to track changes that you make? You can do it two ways:
Since it's a constant each time you make a change external to the PLC you roll the rev of a variable that is declared like SoftwareVersion :WORD := 100; and keep it in a Revision global list that you can add your notes to and change the version before downloading to PLC.
You can also use the PLC summary area that has fields to enter the values and then you can read them through CoDeSys without software upload.
And of course the suggestion above can work.
I recently wrote some code using Matlab's OOP. In each class object I save some measurement data as a property and define the methods for evaluating them. With an average data set one single class object uses about 32 MB of memory.
Now I am writing a GUI that should process these objects.
In the first step I load a set of objects from a saved .mat-file (about 200 objects, 2GB on harddisk) and store them in the handles struct. They fill the RAM and use about 6-7 GB, when loaded. This is no problem.
But if I close the GUI, it seems that I can't free the used memory.
I tried different approaches with no success.
Setting the data fields to "empty" in the destructor of the class:
function delete(obj)
obj.timeVector = [];
obj.valueVector = [];
end
Trying to free it in the figure_CloseRequestFcn:
function figure_CloseRequestFcn(hObject, eventdata, handles)
handles.data = [];
handles = rmfield(handles,'data');
guidata(hObject,handles);
clear handles;
pack; %Matlab issues a warning, that pack could only
%be used from the command line, but that did
%not work either
delete(hObject);
end
Any ideas, besides closing Matlab every time after working with the GUI?
I found the answer in the Matlab Bug Report Center. Seems to exist since R2011b.
Summary
Storing objects in MAT-files can cause a memory leak and prevent the object class from being cleared
Description
After storing an instance of a class, 'MyClass', in a MAT-file, calling clear classes may result in the warning:
Warning: Objects of 'MyClass' class exist. Cannot clear this class or any of its superclasses.
This warning persists, even if you have cleared all instances of the class in the workspace.
The warning may occur for one MAT-file format, and not for another.
Workaround
Under some circumstances, switching to a different MAT-file format may eliminate the warning.
http://www.mathworks.ch/support/bugreports/857319
Edit:
I tried older formats for saving, but this does not work either. I get an "Error closing file" (http://www.mathworks.ch/matlabcentral/answers/18098-error-using-save-error-closing-file). So Matlab does not support saving class objects that well. I will have to live with the memory issues then and restart Matlab after every use of the GUI.
Based on your memory screenshots, there is definitely memory that is not being cleared. There is a small chance that you have found a fundamental flaw in Matlab's garbage collection, but it is much more likely that the ~6Gigs of memory resident data is still actually available via some series of links. Based on personal experience, here are a few ways that memory which you thought was cleared can still be available:
Timer objects: If one of the callback functions of a timer references a this data (or a copy), then that data is still available. You need to call deleted(t) on that timer.
Persistent variables in functions: I often cache data in a persistent variable within a function, this clearly allows access to that data in the future, so it will not be cleared. You need to call clear FUNCTIONNAME to clear associated persistent variables.
In GUI objects, as either data or within callback functions: The figures and any persistents need to be cleared.
Any static methods or constant attributes in classes which can retain data. These can either be cleared individually within the class, or by force using clear CLASSNAME.
Some tips for finding stale link to data (again, based on personal mistakes)
Look at the exact number of bytes being lost after each call, using the x=memory; call to get an exact count. Is it consistent? Is it a number that you recognize? Sometimes I can find the leak after realizing that it is exactly 238263232 bytes, therefore a 29782904 double array, which must be from function xyz.
See which classes are actually being deleted. Within your delete(obj) function add a detailed display or which objects are being deleted, and by inference, which are not. For a given non-deleted object, where could it be reference from? You should not need to clear data in the delete(obj) function like you are doing, Matlab should handle that for you. Use the delete function instead as a debugging tool.
Matlab has a garbage collector so you don't need to manually manage memory. After closing the GUI, all the memory will be freed except for what is in your workspace. You can clear the workspace variables using clear.
One thing I've noticed on Windows (not sure about other platforms) is that Matlab's GUI sometimes retains extra memory (maybe 100 MB, but not multiple GB like you are seeing). Simply minimizing and then restoring the GUI will free this excess memory.
I'm looking at a crash dump. Some variables seem perfectly viewable in windbg, while others just say "memory access error". What causes this? Why do some variables have sensical values while others simply list ?
It appears that all the problems are associated with following pointers. I'm certain that while many of these pointers are uninitialized the vast majority of them should be pointing somewhere valid. Based on the nature of this crash (a simple null ptr dereference) I'm fairly certain the whole process hasn't gone out to lunch.
Mini-dumps are fairly useless, they don't contain a snapshot of all in use memory. Instead, all they contain are some critical structures/lists (e.g. the loaded module list) and the contents of the crashing stack.
So, any pointer that you try to follow in the dump will just give you question marks. Grab a full memory dump instead and you'll be able to see what these buffers point to.
-scott
If they are local pointer variables, what is most likely happening is that the pointers are not initialized, or that stack location has been reused to contain another variable, that may not be a pointer. In both cases, the pointer value may point to a random, unreadable portion of memory.