mct | Open MCT has moved to https : //github.com/nasa/openmct | Data Visualization library

Saturating RAM is not as simple as is seems.

First of all, at first glance here is the apparent throughput we can compute from the provided numbers:

• Fill: 1 / 0.4263950000 = 2.34 GB/s (1 GB is read);
• Memcpy: 2 / 0.6350150000 = 3.15 GB/s (1 GB is read and 1 GB is written).

The thing is that the pages allocated by malloc are not mapped in physical memory on Linux systems. Indeed, malloc reserve some space in virtual memory, but the pages are only mapped in physical memory when a first touch is performed causing expensive page faults. AFAIK, the only way speed up this process is to use multiple cores or to prefill the buffers and reuse them later.

Additionally, due to architectural limitations (ie. latency), one core of a Xeon processor cannot saturate the RAM. Again, the only way to fix that is to use multiple cores.

If you try to use multiple core, then the result provided by the benchmark will be surprising since clock does not measure the wall-clock time but the CPU time (which is the sum of the time spent in all threads). You need to use another function. In C, you can use gettimeofday (which is not perfect as it is not monotonic) but certainly good-enough for your benchmark (related post: How can I measure CPU time and wall clock time on both Linux/Windows?). In C++, you should use std::steady_clock (which is monotonic as opposed to std::system_clock).

In addition, the write-allocate cache policy on x86-64 platform force cache lines to be read when they are written. This means that to write 1 GB, you actually need to read 1 GB! That being said, x86-64 processors provide non-temporal store instructions that does not cause this issue (assuming your array is aligned properly and big enough). Compilers can use that but GCC and Clang generally does not. memcpy is already optimized to use non-temporal stores on most machines. For more information, please read How do non temporal instructions work?.

Finally, you can parallelize the benchmark easily using OpenMP with simple #pragma omp parallel for directives on loops. Note that is also provide a user-friendly function for computing the wall-clock time correctly: omp_get_wtime. For the memcpy, the best is certainly to write a loop doing memcpy by (relatively big) chunks in parallel.

For more information about this subject, I advise you to read the great famous document: What Every Programmer Should Know About Memory. Since the document is a bit old, you can check the updating information about this here. The document also describe additional important things to understand why you may still not succeed saturate the RAM with the above information. One critical topic is NUMA.

The ruamel.yaml documentation states that it should be installed using:

I figured out the answer. I found this reference, which was much more helpful in terms of pseudocode than the NIST reference: https://www.ipa.go.jp/security/jcmvp/jcmvp_e/documents/atr/atr01b_en.pdf section 3.4.3.2.2

Here is the working decrypt code:

It's not working because you already have a column with that name. If you are ok with having duplicate columns then, you can pass allow_duplicates=True.

df.insert(len(df.columns),"Trigger_Type", cat_1, allow_duplicates=True)

Otherwise, you will have to rename the column to something else.

If you want to completely replace the column, you can also use:

df['Trigger_Type'] = cat1

The easiest way is to leverage the session equivalence library that is included with qiskit (at qiskit.circuit.equivalence_library.SessionEquivalenceLibrary) which is a prebuilt equivalence library which includes all the standard library gates. You can use it with something like:

I believe something like this will do the job for you, as you want to retrieve all the categories for an ambulance id as long as at least one of the categories match.

The telecom and address fields are lists. So if you have existing data and you do pat.Address.Add, it will add a new item to the existing list - keeping the already existing address. You will actually have to update your Telecom/Address field first, before sending the updated data to the server.

For example - between client.Read and client.Update, using System.Linq:

The underlying issue was a second DB named "OLD" in REDHAT_2 node that was trying to sync with "MCT" in all nodes and was taking the ownership of replication slots so the real "MCT" nodes can't really open a connection.

Taking BDR down in the "OLD" Database and restarting PSQL solved the issue. Thanks

A Gemfile declares a dependency on a Ruby version, with or without semantic versioning constraints. It is not meant to control multiple build targets for your application. It simply enforces that the Ruby version available to your app/gem is whatever you've defined. For example: