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https://descargatelo.net/uncategorized/hitman-absolution-highly-compressed-10mbgolkes-top-free/.Some time ago I discovered the existence of the CTetra library on the net. I gave a little project to do some experimentation with it as an addition to some personal stuff I’m making. After some time I decided to open source it. I’ve renamed it CTetraSlammer to avoid confusion with existing CTetra libraries. Some documentation is included in the package and many samples are available from the main page. I’ll make a list of all the stuff needed to compile CTetra from source: Qt PThread x86_64 assembly that is compatible with masm, binutils, Windows SDK and Linux userland (at least GCC 4.6) I’ve made a simple sample in which I wanted to test CPU affinity, so to say the amount of cores a process can access at once. I wanted to do this because recently I have to deal with some customers that tell me the process that consumes too much resources is infrequent, and I wanted to check if using a process with a high affinity would make the OS do more work in it, thus depleting more available CPU time for other processes. After all they are on a shared server that has a lot of resources, I think I can save some CPU time for the OS without touching anything else. Before doing this I have checked if the result would be different for Linux and Windows, thinking that was already taken care of, and it was not. Windows generally uses a fixed number of processor cores. You can do a lot of local analysis of your processes in the context of each one of them but this is one of the very few areas where there is a general rule and this rule is the rule of Windows. You can think about it as a little bit of a queue, where all threads should get their time of execution in the same order they are running. A thread will be blocked as long as there are other ones already at the head of the queue. So, if there are enough cores the probability that the queue for a thread should not be blocked is as higher as it is for others, and therefore the thread will be run with less priority. As it can be seen, very different behavior can be achieved depending on the “smaller” number of cores available. Example of this is running a game or doing a repetitive task for a short amount of time, where the probability of not being blocked is higher. Running some long task is a good example of this, because it is usually executed by the OS for an amount of time long enough to not be completed before another task is run. There is a certain point where the probability is always zero. In order to make the task done as fast as possible, the most suitable solution is to release the cores as soon as a thread is completed. This obviously does not apply for the operations that can be done by a single core instead. You can use the tool Process Explorer by sysinternals to get a quick view of the amount of real cores available in a Windows machine: The left side is the block/unblock list, the right side is the list of all tasks and threads. I’ve made a simple test script in C++ to iterate over the number of cores in the system and the next one gets released. The next task is to make sure the task will take less time to execute and less RAM. I’ve done it by putting the code in a loop that will continuously ask for a new thread.
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