You perform a command. Your CPU begins the fetch, decode, and execution process to achieve that command. The thread is the sequence of instructions that tell your computer what it has to do to perform that command. They work in conjunction to open programs, use apps, play videos, and do whatever you ask your computer to do. Your processor will determine which process gets handled by the CPU and which gets handled by a thread.
Every time your processor loads a new thread, the original thread gets saved in the main memory. The new thread then embarks on the first step of the three-step fetch, decode, and execution process. To date, these CPUs offer some of the best performance and the most amount of threads. It boasts a With a 2. With 14 cores and 28 threads, the Intel Core iX features a max turbo frequency of 4. If you want the best processor and the most amount of threads, check out the Intel Xeon Platinum series.
Intel CPUs are well-known as the best in the business, and for good reason. The Platinum , F, and models boast 28 cores with 56 threads. The Platinum and feature 26 cores and 52 threads. But if you want to know and understand exactly how your computer operates, understanding threads is key. You need some understanding of the fetch, decode, and execute cycle.
But the most important thing to know is that threads affect how quickly and efficiently your computer can multiple instructions at the same time. Within Windows, all threads are actively operated on for some period of time.
To have a functioning system, you need the right CPU and the right amount of threads. Together, they are crucial elements that allow your computer to function. You need the CPU to power the other components and send instructions to the right elements of your computer. You need the threads to perform many functions at a time and allow your computer to run efficiently. If you want to make sure your CPU offers enough threads, do your research to know the difference and know what various CPUs are capable of.
Compare costs, compare function, and compare performance. Invest a bit of time doing research. Take the time to read reviews. What Are Threads in a Processor? By Randy.
Table of Contents. If you run two processes on a single core, less frequency is available for each process, when compared to running each process on its own core. It is a very basic and simplistic statement, but the OP never requested any detail about hyper-threading or how it works. Though you are correct, hyper-threading has come a long way and with 48 cores i am sure they would not want to turn it off.
This is basically the whole point of HT, to expose more instruction-level parallelism to the out-of-order core. See agner. Finally, you should test to get the best number based on your specific tasks.
Qinsi Qinsi 5 5 silver badges 6 6 bronze badges. Piotr Lenarczyk Piotr Lenarczyk 11 2 2 bronze badges. The output says "Thread s per core: 2" — committedandroider. You can use man page about 'ps' command.
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Now live: A fully responsive profile. Linked 0. EDIT: Thank you all for your responses, it seems like I am just going to have to test it to find out my thread count ceiling. Improve this question. Community Bot 1 1 1 silver badge. Don't forget that Python is by nature, not really multi-thread friendly. At any point of time, a single bytecode opcode is being executed. This is because Python employs Global Interpreter Lock.
Jay D: I'd say the moment you've hit the ceiling is when your performance starts to drop. Fixed-size thread pools have the benefits of graceful degradation and scalability.
A fixed-size pool acts like a pipe valve by disallowing your server from trying to bite off more than it can chew. Show 3 more comments. Active Oldest Votes. Some people would say that two threads is too many - I'm not quite in that camp :- Here's my advice: measure, don't guess. For clarification and elaboration: I'm not advocating rolling your own thread pooling subsystem, by all means use the one you have. I've written thread and database connection pooling code and they have the following features which I believe are essential for performance : a minimum number of active threads.
In response to the "what exactly should I measure? Improve this answer. If threads are spawned on incoming requests then thread-usage will mirror the number of unserviced requests.
There's no way to determine the "optimal" number from this. Indeed you will find more threads cause more resource contention and thus the number of active threads will increase. Where is this data on 'thread creation' causing a performance problem when using a thread pool?
A good thread pool would not be creating and destroying threads in between tasks. Pax If all your threads are waiting on the same semaphores to run DB queries then that's the very definition of contention. It's also not true to say threads don't cost anything if they're waiting on a semaphore. Andrew, I can't see why'd you'd semaphore-block the DB queries, any decent DB will allow concurrent access, with many threads waiting on the responses.
And threads shouldn't cost any execution time while semaphore-blocked, they should sit in the blocked queue until the semaphore is released. Show 1 more comment. Max Virtual memory that a given OS variant supports.
Linux Kernel 2. For 2. What kindda kernel scheduler you have. Comparing Linux 2. So also the SMP Capabilities of the kernel schedule also play a good role in max number of sustainable threads in a system. Jay D Jay D 3, 3 3 gold badges 29 29 silver badges 47 47 bronze badges. Note that these virtual memory limits only apply to bit systems. On 64 bits you won't run out of virtual memory. Add a comment. Andrew Grant Andrew Grant Yes, and it should be used in conjunction with a queue or pool of requests.
Andrew: Why? It should add a task to the thread pool each time it receives a request. It is up to the thread pool to allocate a thread for the task when there is one available.
So what do you do when you have hundreds of requests coming in and are out of threads? Create more? Return an error? Place your requests in a pool that can be as large as need be, and then feed these queued requests to your thread pool as threads become free. Typically, there are many more tasks than threads. As soon as a thread completes its task, it will request the next task from the queue until all tasks have been completed.
Andrew: I am not sure what python thread pool the OP is using, but if you want a real world example of this functionality I am describing: msdn. Chad Okere Chad Okere 4, 1 1 gold badge 19 19 silver badges 19 19 bronze badges.
After reading this, I tried running sieve of Eratosthenes tasks on three threads. Thanks for the heads up. Next, I'll try a scenario that involves some database calls. There are two at least types of tasks: CPU bound e. If your tasks are CPU bound then you should consider multiprocessing instead of multithreading. Of course, it depends on many things, that's why you must measure yourself.
That's a tad higher than I would have expected as well. Still, if that's what you got, then that's what you got, I can't argue with that. For this specific application, most threads are just waiting a response from the DNS server. So, the more parallelism, the better, in wall-clock time. I speak from experience here. Matthew Lund Matthew Lund 3, 6 6 gold badges 27 27 silver badges 37 37 bronze badges. Can you mention some of the numbers you've seen for thread count?
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