I need to run multiple instances of a C program in VxWorks (VxWorks has a global namespace). The problem is that the C program defines global variables (which are intended for use by a specific instance of that program) which conflict in the global namespace. I would like to make minimal changes to the program in order to make this work. All ideas welcomed!
Regards
By the way ... This isn't a good time to mention that global variables are not best practice!
The easiest thing to do would be to use task Variables (see taskVarLib documentation).
When using task variables, the variable is specific to the task now in context. On a context switch, the current variable is stored and the variable for the new task is loaded.
The caveat is that a task variable can only be a 32-bit number.
Each global variable must also be added independently (via its own call to taskVarAdd?) and it also adds time to the context switch.
Also, you would NOT be able to share the global variable with other tasks.
You can't use task variables with ISRs.
Another Possibility:
If you are using Vxworks 6.x, you can make a Real Time Process application.
This follows a process model (similar to Unix/Windows) where each instance of your program has it's own global memory space, independent of any other instance.
I had to solve this when integrating two third-party libraries from the same vendor. Both libraries used some of the same symbol names, but they were not compatible with each other. Because these were coming from a vendor, we couldn't afford to search & replace. And task variables were not applicable either since (a) the two libs might be called from the same task and (b) some of the dupe symbols were functions.
Assume we have app1 and app2, linked, respectively, to lib1 and lib2. Both libs define the same symbols so must be hidden from each other.
Fortunately (if you're using GNU tools) objcopy allows you to change the type of a variable after linking.
Here's a sketch of the solution, you'll have to modify it for your needs.
First, perform a partial link for app1 to bind it to lib1. Here, I'm assuming that you've already partially linked *.o in app1 into app1_tmp1.o.
$(LD_PARTIAL) $(LDFLAGS) -Wl,-i -o app1_tmp2.o app1_tmp1.o $(APP1_LIBS)
Then, hide all of the symbols from lib1 in the tmp2 object you just created to generate the "real" object for app1.
objcopymips `nmmips $(APP1_LIBS) | grep ' [DRT] ' | sed -e's/^[0-9A-Fa-f]* [DRT] /-L /'` app1_tmp2.o app1.o
Repeat this for app2. Now you have app1.o and app2.o ready to link into your final application without any conflicts.
The drawback of this solution is that you don't have access to any of these symbols from the host shell. To get around this, you can temporarily turn off the symbol hiding for one or the other of the libraries for debugging.
Another possible solution would be to put your application's global variables in a static structure. For example:
From:
int global1;
int global2;
int someApp()
{
global2 = global1 + 3;
...
}
TO:
typedef struct appGlobStruct {
int global1;
int global2;
} appGlob;
int someApp()
{
appGlob.global2 = appGlob.global1 + 3;
}
This simply turns into a search & replace in your application code. No change to the structure of the code.
Related
I'm using Chisel and blackbox to run my chisel logic against a verilog register file.
The registerfile does not have reset signal so I expect the register to be randomly initialized.
I passed the --x-initial unique to verilator,
Basically this is how I launch the test:
private val backendName = "verilator"
"NOCDMA" should s" do blkwrite and blkread correctly (with $backendName)" in {
Driver.execute(Array("--fint-write-vcd","--backend-name",s"$backendName",
"--more-vcs-flags","--trace-depth 1 --x-initial unique"),
()=>new DMANetworkWithMem(memAddrWidth,memDataWidth)(nocDataWidth)(nNodesX,nNodesY)){
c => new DMANetworkRWTest(c)
}
}
But The data I read from the register file is all zero before I wrote anything to it.
The read data is correct after I wrote to it.
So, is there anything inside chisel that I need to tune or I did not do everything properly ?
Any suggestions?
I'm not certain, but I found the following issue on Verilator with a similar issue: https://github.com/verilator/verilator/issues/1399.
From skimming the above issue, I think you also need to pass +verilator+seed+<value> and +verilator+rand+reset+<value> at runtime. I am not an expert in the iotesters, but I believe you can add these runtime values through the iotesters argument: --more-vcs-c-flags.
Side note, I would also set --x-assign unique in Verilator if there are cases in the Verilog where runtime would otherwise inject an X (eg. out-of-bounds index).
I hope this helps!
I am having some confusion between when to use a scoped variable. When you declare it in a function like this.
int main(){
int x;
}
And when to use a public variable like this.
int x;
int main(){
}
The scoped variable being the one only available in the function it is declared in and the public variable being the one available to the entire file. Could you help me understand when to use this?
Ask these questions to you,
Do you intent to use x in main function only?
Are you going to pass x as parameter to mains subfunctions?
Then it should be scoped.
Createors of modular programming will be happy to see this
Does your app consist of many files?
Is x is something (like global state) which your app needs in all those files?
Then x should be kept global (in header file , as best practice) so it can be used as extern in other files.
If you are just starting to write your app:
If you start x as a scope varible and end up passing it in every function across all files then you should change it as global scope
If your app is already developed and x is being added as a new functionality:
Then you should be already knowing x represents global state or not.
Here's a simple rule of thumb: declare a variable in the narrowest possible scope in which you'll be using it.
As for an explanation of why: in C and C++ (and other languages), variables essentially "cease to exist" when they go out of scope. If you declare a variable outside of a function, that variable gets processed and stored in memory before the function is called. Each time you call the function and use that variable, the same bit of memory is accessed, and as a result the variable maintains its value between calls.
Meanwhile, if you declare a variable inside a function (for example; in C/C++, I think anything with curly brackets in it defines a narrower scope), it gets allocated and stored in memory only when it comes into scope. When that scope ends (e.g. with a return statement at the end of a method), all the memory that was in that scope is released.
This all ties into the stack, which is one of the two main ways that C and C++ handle dynamic memory. Here's a serviceable overview of how C programs lay out memory; suffice it to say that the reasons for the rule of thumb above are that
you don't want to consume any more memory than you need at any given time. In other words, you don't want a variable sitting around that you're never going to use.
It's much easier to debug a problem when the variable has a limited scope, and you know everything that could be affecting it, than when it's in the global scope and everything could be affecting it
First, here the way i'm calling the function :
eval([functionName '(''stringArg'')']); % functionName = 'someStringForTheFunctionName'
Now, I have two functionName functions in my path, one that take the stringArg and another one that takes something else. I'm getting some errors because right now the first one it finds is the function that doesn't take the stringArg. Considering the way i'm calling the functionName function, how is it possible to call the correct function?
Edit:
I tried the function which :
which -all someStringForTheFunctionName
The result :
C:\........\x\someStringForTheFunctionName
C:\........\y\someStringForTheFunctionName % Shadowed
The shadowed function is the one i want to call.
Function names must be unique in MATLAB. If they are not, so there are duplicate names, then MATLAB uses the first one it finds on your search path.
Having said that, there are a few options open to you.
Option 1. Use # directories, putting each version in a separate directory. Essentially you are using the ability of MATLAB to apply a function to specific classes. So, you might set up a pair of directories:
#char
#double
Put your copies of myfun.m in the respective directories. Now when MATLAB sees a double input to myfun, it will direct the call to the double version. When MATLAB gets char input, it goes to the char version.
BE CAREFUL. Do not put these # directories explicitly on your search path. DO put them INSIDE a directory that is on your search path.
A problem with this scheme is if you call the function with a SINGLE precision input, MATLAB will probably have a fit, so you would need separate versions for single, uint8, int8, int32, etc. You cannot just have one version for all numeric types.
Option 2. Have only one version of the function, that tests the first argument to see if it is numeric or char, then branches to perform either task as appropriate. Both pieces of code will most simply be in one file then. The simple scheme will have subfunctions or nested functions to do the work.
Option 3. Name the functions differently. Hey, its not the end of the world.
Option 4: As Shaun points out, one can simply change the current directory. MATLAB always looks first in your current directory, so it will find the function in that directory as needed. One problem is this is time consuming. Any time you touch a directory, things slow down, because there is now disk input needed.
The worst part of changing directories is in how you use MATLAB. It is (IMHO) a poor programming style to force the user to always be in a specific directory based on what code inputs they wish to run. Better is a data driven scheme. If you will be reading in or writing out data, then be in THAT directory. Use the MATLAB search path to categorize all of your functions, as functions tend not to change much. This is a far cleaner way to work than requiring the user to migrate to specific directories based on how they will be calling a given function.
Personally, I'd tend to suggest option 2 as the best. It is clean. It has only ONE main function that you need to work with. If you want to keep the functions district, put them as separate nested or sub functions inside the main function body. Inside of course, they will have distinct names, based on how they are driven.
OK, so a messy answer, but it should do it. My test function was 'echo'
funcstr='echo'; % string representation of function
Fs=which('-all',funcstr);
for v=1:length(Fs)
if (strcmp(Fs{v}(end-1:end),'.m')) % Don''t move built-ins, they will be shadowed anyway
movefile(Fs{v},[Fs{v} '_BK']);
end
end
for v=1:length(Fs)
if (strcmp(Fs{v}(end-1:end),'.m'))
movefile([Fs{v} '_BK'],Fs{v});
end
try
eval([funcstr '(''stringArg'')']);
break;
catch
if (strcmp(Fs{v}(end-1:end),'.m'))
movefile(Fs{v},[Fs{v} '_BK']);
end
end
end
for w=1:v
if (strcmp(Fs{v}(end-1:end),'.m'))
movefile([Fs{v} '_BK'],Fs{v});
end
end
You can also create a function handle for the shadowed function. The problem is that the first function is higher on the matlab path, but you can circumvent that by (temporarily) changing the current directory.
Although it is not nice imo to change that current directory (actually I'd rather never change it while executing code), it will solve the problem quite easily; especially if you use it in the configuration part of your function with a persistent function handle:
function outputpars = myMainExecFunction(inputpars)
% configuration
persistent shadowfun;
if isempty(shadowfun)
funpath1 = 'C:\........\x\fun';
funpath2 = 'C:\........\y\fun'; % Shadowed
curcd = cd;
cd(funpath2);
shadowfun = #fun;
cd(curcd); % and go back to the original cd
end
outputpars{1} = shadowfun(inputpars); % will use the shadowed function
oupputpars{2} = fun(inputparts); % will use the function highest on the matlab path
end
This problem was also discussed here as a possible solution to this problem.
I believe it actually is the only way to overload a builtin function outside the source directory of the overloading function (eg. you want to run your own sum.m in a directory other than where your sum.m is located.)
EDIT: Old answer no longer good
The run command won't work because its a function, not a script.
Instead, your best approach would be honestly just figure out which of the functions need to be run, get the current dir, change it to the one your function is in, run it, and then change back to your start dir.
This approach, while not perfect, seems MUCH easier to code, to read, and less prone to breaking. And it requires no changing of names or creating extra files or function handles.
As of now I use 3 Notebook :
Functions
Where I have all the functions I created and call in the other Notebooks.
Transformation
Based on the original data, I compute transformations and add columns/List
When data is my raw data, I then call :
t1data : the result of the first transformation
t2data : the result of the second transformation
and so on,
I am yet at t20.
Display & Analysis
Using both the above I create Manipulate object that enable me to analyze the data.
Questions
Is there away to save the results of the Transformation Notebook such that t13data for example can be used in the Display & Analysis Notebooks without running all the previous computations (t1,t2,t3...t12) it is based on ?
Is there a way to use my Functions or transformed data without opening the corresponding Notebook ?
Does my separation strategy make sense at all ?
As of now I systematically open the 3 and have to run them all before being able to do anything, and it takes a while given my poor computing power and yet inefficient codes.
Saving variable states: can be done using DumpSave, Save or Put. Read back using Get or <<
You could make a package from your functions and read those back using Needs or <<
It's not something I usually do. I opt for a monolithic notebook containing everything (nicely layered with sections and subsections so that you can fold open or close) or for a package + slightly leaner analysis notebook depending on the weather and some other hidden variables.
Saving intermediate results
The native file format for Mathematica expressions is the .m file. This is human readable text format, and you can view the file in a text editor if you ever doubt what is, or is not being saved. You can load these files using Get. The shorthand form for Get is:
<< "filename.m"
Using Get will replace or refresh any existing assignments that are explicitly made in the .m file.
Saving intermediate results that are simple assignments (dat = ...) may be done with Put. The shorthand form for Put is:
dat >> "dat.m"
This saves only the assigned expression itself; to restore the definition you must use:
dat = << "dat.m"
See also PutAppend for appending data to a .m file as new results are created.
Saving results and function definitions that are complex assignments is done with Save. Examples of such assignments include:
f[x_] := subfunc[x, 2]
g[1] = "cat"
g[2] = "dog"
nCr = #!/(#2! (# - #2)!) &;
nPr = nCr[##] #2! &;
For the last example, the complexity is that nPr depends on nCr. Using Save it is sufficient to save only nPr to get a fully working definition of nPr: the definition of nCr will automatically be saved as well. The syntax is:
Save["nPr.m", nPr]
Using Save the assignments themselves are saved; to restore the definitions use:
<< "nPr.m" ;
Moving functions to a Package
In addition to Put and Save, or manual creation in a text editor, .m files may be generated automatically. This is done by creating a Notebook and setting Cell > Cell Properties > Initialization Cell on the cells that contain your function definitions. When you save the Notebook for the first time, Mathematica will ask if you want to create an Auto Save Package. Do so, and Mathematica will generate a .m file in parallel to the .nb file, containing the contents of all Initialization Cells in the Notebook. Further, it will update this .m file every time you save the Notebook, so you never need to manually update it.
Sine all Initialization Cells will be saved to the parallel .m file, I recommend using the Notebook only for the generation of this Package, and not also for the rest of your computations.
When managing functions, one must consider context. Not all functions should be global at all times. A series of related functions should often be kept in its own context which can then be easily exposed to or removed from $ContextPath. Further, a series of functions often rely on subfunctions that do not need to be called outside of the primary functions, therefore these subfunctions should not be global. All of this relates to Package creation. Incidentally, it also relates to the formatting of code, because knowing that not all subfunctions must be exposed as global gives one the freedom to move many subfunctions to the "top level" of the code, that is, outside of Module or other scoping constructs, without conflicting with global symbols.
Package creation is a complex topic. You should familiarize yourself with Begin, BeginPackage, End and EndPackage to better understand it, but here is a simple framework to get you started. You can follow it as a template for the time being.
This is an old definition I used before DeleteDuplicates existed:
BeginPackage["UU`"]
UnsortedUnion::usage = "UnsortedUnion works like Union, but doesn't \
return a sorted list. \nThis function is considerably slower than \
Union though."
Begin["`Private`"]
UnsortedUnion =
Module[{f}, f[y_] := (f[y] = Sequence[]; y); f /# Join###] &
End[]
EndPackage[]
Everything above goes in Initialization Cells. You can insert Text cells, Sections, or even other input cells without harming the generated Package: only the contents of the Initialization Cells will be exported.
BeginPackage defines the Context that your functions will belong to, and disables all non-System` definitions, preventing collisions. (There are ways to call other functions from your package, but that is better for another question).
By convention, a ::usage message is defined for each function that it to be accessible outside the package itself. This is not superfluous! While there are other methods, without this, you will not expose your function in the visible Context.
Next, you Begin a context that is for the package alone, conventionally "`Private`". After this point any symbols you define (that are not used outside of this Begin/End block) will not be exposed globally after the Package is loaded, and will therefore not collide with Global` symbols.
After your function definition(s), you close the block with End[]. You may use as many Begin/End blocks as you like, and I typically use a separate one for each function, though it is not required.
Finally, close with EndPackage[] to restore the environment to what it was before using BeginPackage.
After you save the Notebook and generate the .m package (let's say "mypackage.m"), you can load it with Get:
<< "mypackage.m"
Now, there will be a function UnsortedUnion in the Context UU` and it will be accessible globally.
You should also look into the functionality of Needs, but that is a little more advanced in my opinion, so I shall stop here.
Is there any way to define an Erlang function from within the Erlang shell instead of from an erl file (aka a module)?
Yes but it is painful. Below is a "lambda function declaration" (aka fun in Erlang terms).
1> F=fun(X) -> X+2 end.
%%⇒ #Fun <erl_eval.6.13229925>
Have a look at this post. You can even enter a module's worth of declaration if you ever needed. In other words, yes you can declare functions.
One answer is that the shell only evaluates expressions and function definitions are not expressions, they are forms. In an erl file you define forms not expressions.
All functions exist within modules, and apart from function definitions a module consists of attributes, the more important being the modules name and which functions are exported from it. Only exported functions can be called from other modules. This means that a module must be defined before you can define the functions.
Modules are the unit of compilation in erlang. They are also the basic unit for code handling, i.e. it is whole modules which are loaded into, updated, or deleted from the system. In this respect defining functions separately one-by-one does not fit into the scheme of things.
Also, from a purely practical point of view, compiling a module is so fast that there is very little gain in being able to define functions in the shell.
This depends on what you actually need to do.
There are functions that one could consider as 'throwaways', that is, are defined once to perform a test with, and then you move on. In such cases, the fun syntax is used. Although a little cumbersome, this can be used to express things quickly and effectively. For instance:
1> Sum = fun(X, Y) -> X + Y end.
#Fun<erl_eval.12.128620087>
2> Sum(1, 2).
3
defines an anonymous fun that is bound to the variable (or label) Sum. Meanwhile, the following defines a named fun, called F, that is used to create a new process whose PID (<0.80.0>) is bound to Pid. Note that F is called in a tail recursive fashion in the second clause of receive, enabling the process to loop until the message stop is sent to it.
3> Pid = spawn(fun F() -> receive stop -> io:format("Stopped~n"); Msg -> io:format("Got: ~p~n", [Msg]), F() end end).
<0.80.0>
4> Pid ! hello.
hello
Got: hello
5> Pid ! stop.
Stopped
stop
6>
However you might need to define certain utility functions that you intend to use over and over again in the Erlang shell. In this case, I would suggest using the user_default.erl file together with .erlang to automatically load these custom utility functions into the Erlang shell as soon as this is launched. For instance, you could write a function that compiles all the Erlang files in living in the current directory.
I have written a small guide on how to do this on this GitHub link. You might find it helpful and instructive.
If you want to define a function on the shell to use it as macro (because it encapsulates some functionality that you need frequently), have a look at
https://erldocs.com/current/stdlib/shell_default.html