usm | A concise & flexible state model for Redux/MobX/Vuex , etc | State Container library

I'm unfamiliar with SNMP4J, but this block of code may need to have the security level defined as authPriv or however SNMP4J refers to it:

Disclaimer I am not expert so take the following with a pinch of salt.

I cannot say for the library you are using but regarding the SNMP v3 flow:

In SNMPv3 exchanges, the USM is responsible for validation only on the SNMP authoritative engine side, the authoritative role depending of the kind of message.

• Agent authoritative for : GET / SET / TRAP
• Receiver authoritative for : INFORM

The RFC 3414 describes the reception of message in section 3.2 :

1. If the information about the user indicates that it does not support the securityLevel requested by the caller, then the usmStatsUnsupportedSecLevels counter is incremented and an error indication (unsupportedSecurityLevel) together with the OID and value of the incremented counter is returned to the calling module.

2. If the securityLevel specifies that the message is to be authenticated, then the message is authenticated according to the user’s authentication protocol. To do so a call is made to the authentication module that implements the user’s authentication protocol according to the abstract service primitive

So in the step 6, the securityLevel is the one from the message. This means the TRAP is accepted by the USM layer on the receiver side even if the authentication is not provided.

It is then the task of the user of the TRAP to decide if the message must be interpreted or not.

By default most of the compilers take integers ( 'int' for C or C++ / 'INTEGER' for Fortran) as 32-bit length. So most applications need to be linked with LP64 MKL libraries. (https://www.intel.com/content/www/us/en/develop/documentation/onemkl-linux-developer-guide/top/linking-your-application-with-onemkl/linking-in-detail/linking-with-interface-libraries/using-the-ilp64-interface-vs-lp64-interface.html)

So try linking against LP64 interface and see if it works. Additionally, I would suggest you set MKL_VERBOSE=1 (https://www.intel.com/content/www/us/en/develop/documentation/onemkl-linux-developer-guide/top/managing-output/using-onemkl-verbose-mode.html) and then run your code so that you can see what parameters are passed to the function (as your error message says so).

You can also refer to the examples which comes with oneMKL.There is a similar example under the mkl directory location in your system as below \oneAPI\mkl\2022.0.2\examples\examples_dpcpp\dpcpp\blas\source with usm_gemm.cpp file name which I presume should help you.

pd.DataFrame.from_dict ?

error: redefinition of 'n' with a different type: 'range<1>' vs 'int'

Two variables with the same name within the same scope create confusion to the compiler, so it might be the reason for the error which you are getting. You can try defining the value of n globally say for eg: #define N 100 in this case, set

The syntax for memcpy() is

You are missing a barrier between the submission of the queue and the for loop in the host code.

Although it is true that an USM shared memory allocation is visible on the host and the device, there is no guarantees that the command group you have submitted to the queue will execute before the for loop in the host: Submissions to queues execute asynchronously w.r.t to the calling thread. Updated code below:

UsageStatsManager doesn't update the unless the app goes in background. You can archive this by adding the difference of current time and timestamp of current running app going foreground.
Refer to this answer for details : How to count app usage time while app is on foreground?

First of all, judging by the artefacts that Photoshop left on the borders of the petals, I'd say that it applies the mask by using a weighted sum between the original image and the mask, as in the answer you tried first.

I modified your code to implement this scheme and I tried to tweak the parameters to get as close as the Photoshop result, but I couldn't without creating a lot of noise. I wouldn't try to guess what Photoshop is exactly doing (I would definitely like to know), however I discovered that it is fairly reproducible by applying some filter on the mask to reduce the noise. The algorithm scheme would be: