How does multithreading utilizes multiple cores? - multithreading

So recently I've learned some basic knowledge about multithreading. What I've understood is that thread is a lightweight process that runs under processes by sharing memory, while one process is running under one CPU core.
Yet by this perspective I couldn't understand some saying that threads utilizes multiple cores and make the whole program executes more effective. From what I've known, threads created by one process should run only under that specific process, which means that it should only run under that very one CPU core. If we want to utilize multiple cores, we should actually use multiprocess to run parallelly. Most of what I've researched is only about the conclusion, i.e multithreading utilizes multiple cores, but none of them explains my question. Did I think anything wrong? Thanks!

Your confusion lies here:
[...] while one process is running under one CPU core.
[...] threads created by one process should run only under that specific process, which means that it should only run under that very one CPU core.
This is not true. I think what the various explanations you have read meant that any process have at least one thread (where a 'thread' is a sequence of instructions ran by a CPU core).
If you have a multithreaded program, the process will have several threads (sequences of instructions ran by a CPU core) that can run concurrently on different CPU cores.
There are many processes executing on your computer at any given time. The Operating System (OS) is the program that allocates the hardware resources (CPU cores) to all these processes and decides which process can use which cores for what amount of time before another process gets to use the CPU. Whether or not a process gets to use multiple cores is not entirely up to the process. More confusing still, multithreaded programs can use more threads than there are cores on the computer's CPU. In that case you can be certain that all your threads do not run in parallel.
One more thing:
[...] threads utilizes multiple cores and make the whole program executes more effective
I am going to sound very pedantic, but it is more complicated than that. It depends on what you mean by "effective". Are we talking about total computation time, energy consumption ..?
A sequential (1 thread) program may be very effective in terms of power consumption but taking a very long time to compute. If you are able to use multiple threads, you may be able to reduce that computation time but it will probably incur new costs (synchronization between threads, additional protection mechanisms against concurrent accesses ...).
Also, multithreading cannot help for certain tasks that fall outside of the CPU realm. For example, unless you have some very specific hardware support, reading a file from the hard-drive with 2 or more concurrent threads cannot be parallelized efficiently.

Related

Process vs thread with example

I read articles on processes vs threads, but I am still not clear on the difference.
Suppose a process is using the CPU/Processor, doing some big calculation that takes 10 minutes. How will another process run at the same time in parallel? In a single core vs a dual core processor?
Same thing for threads, how will another thread run in parallel when the CPU/Processor is engaged with another thread?
How is context switching different for threads and for processes? I mean both process and threads use the same RAM memory, so what's the difference?
From my vague memory of Operating Systems I can offer you a little bit of help. First you have to know the difference between concurrent and simultaneous. They are not the same thing; simultaneous means both things occur at the same time and concurrent means they appear to be running simultaneously but in reality they're switching so fast you can't tell.
Processes and threads can be considered similar, but a big difference is that a process is much larger than a thread. For that reason, it is not good to have switching between processes. There is too much information in a process that would have to be saved and reloaded each time the CPU decides to switch processes.
A thread on the other hand is smaller and so it is better for switching. A process may have multiple threads that run concurrently, meaning not at the same exact time, but run together and switch between them. The context switching here is better because a thread won't have as much information to store/reload.
If you only have a single core then you can only do concurrent execution, for the most part. Once you have multiple cores you can have threads run on both cores and thus have simultaneous execution. It is up to the Operating System to schedule when threads run, when processes get to run, when to switch, how to switch them, etc. The Operating System gives you the illusion that work is being done simultaneously when this is not always the case.
If you have more confusion feel free to comment.
A process is a thing very related to the Operating System (OS). The thread is in the simplest terms, is an executing program. One or more threads run in the context of the process. The Java Virtual Machine (JVM) is a process in your OS.
And inside the JVM you can have multiple threads running concurrently.
The processor is a resource of your machine, like the memory. Your OS let your process to share the available resources, in our simple case processors and memory.
When you develop in Java, all processor in your machine are available resources.
When you develop your solution, you can have even multiple Java processes (i.e. multiple JVM) running a single or multiple thread each. But this mostly depends by your problem.
The real difference between a process and a thread is that both have an executing program, but threads share the same memory. This let your threads to theoretically work on the same data, but you have pay the complexity of concurrency and synchronisation.
Each CPU only runs one thread in a process at a time. However the OS can stop and save a thread and load and run another quickly (as little as 0.0001 seconds) This gives the illusion that many threads are running at once, even though only one is running.

fork vs thread on one single core

Imagine that I have two tasks, each of them needs 2 seconds to finish its job.
In this case, if I create two threads for each of them and my PC is single-core, this won't save any time. Am I right ?
What if I use fork to create two processes (the machine is still single-core) and each process takes charge of one task ? Can this save any time ?
If not, I have a question:
In current modern machine (including multi-core), if I have several heavy tasks, which method should I use ?
fork ?
thread ?
fork + thread, meaning that create some processes and
each process contains more than one thread ?
Even with a single core having two threads may speed up execution. If your routine is purely CPU bound then two threads won't improve anything, indeed the performance will be worse because of context switching overhead. But if the routine has to wait for memory, disk or or network (which is usually the case) then two threads will provide performance gains even with a single core.
About fork vs threads, threads require less resources so, in principle, should be the first choice. But there are two caveats: 1) maybe you want to be able to terminate a parallel routine, this is much safer to do with processes than with threads and 2) some languages (notably Python and Ruby) provide pseudo-thread libraries which do not use real threads but switch between routines using the same thread. This simulated threading can be very useful for example when waiting for network requests but it must be taken into account that it's not real multithreading.
Amendment: As commented by Sergio Tulentsev, Ruby and Python do indeed provide real threads and not only coroutines.
"job takes 2 seconds" - If those 2 seconds are fully occupying the CPU (100% load), you won't gain anything with either thread nor fork if you have no cores to share. The single-core CPU is simply busy and you cannnot make it more busy.
In case this 2 seconds include waiting time (for example on I/O, storage, whatever) you could gain something, even with a single core. The amount of gain depends on the CPU working vs. CPU waiting ratio and the overhead of your multiprocessing. Most non-trivial programs have at least some amount of "CPU waiting", so multithreading is often useful even on single-core CPUs.
This overhead for setting up a coroutine and context switching can be considerable and needs to be measured. Obviously, the shorter the run time of your actiual task is, the larger will be the ratio of overhead (for setting up a thread or process, etc.) and the smaller will be you multi-processing gain.
Traditionally, threads used to have considerably less overhead than processes (after all, that was why they were invented), but the "considerably" has maybe vanished over time - On modern Linux systems, processes are only a tad slower to set up than threads (actually, both use the same system calls). You rather decide between thread or process based on the requirements related to amount of protection (or sharing) of data than execution speed.

How are multiple CPU cores used by the OS

There are a lot of articles that discuss multi-core myth. That, in order to really benefit from multiple cores, one needs to write parallel algorithms. Many of them mention Amdahl's law.
Lets assume for simplicity that we have a desktop computer with a 4-core commodity CPU. And assume that the goal is to improve our application performance, as well as overall system performance.
I wonder how CPU cores are used to perform tasks.
Whether threads from a single process are allocated all cores
Or threads from different processes are scheduled to run on different cores.
If the latter is the case, then why is the myth even discussed? Won't multitasking OSes always benefit from multi-core CPUs, even if all the processes are single threaded? Are threads from the same process more likely to be scheduled at the same time on multiple cores?
What are some factors that matter? CPU cache maybe? Some application related maybe? Why?
Why would you ever want to use parallel libraries/algorithms? After all, CPU resources are shared between all running processes and there are always enough of them.
Is there an "active process" notion? i.e. process that gets most attention from the scheduler. If so, then how much more attention does this process usually get?
Whether threads from a single process are allocated all cores
Yes.
Or threads from different processes are scheduled to run on different cores.
Yes, that too.
If the latter is the case, then why is the myth even discussed? Won't multitasking OSes always benefit from multi-core CPUs, even if all the processes are single threaded?
To some extent, yes. But if that process is doing a lot of computation and the only one we care about at some particular time, the benefit will be pretty low.
On the other hand, it also means the process won't be as likely to be interrupted just because the OS has to do something like handle a disk interrupt, an arriving network packet, or something like that. Interrupting a process to handle some hardware task not only reduce the CPU time the process gets but it also pollutes the CPU caches causing the process to run more slowly when it resumes. So multi-core CPUs can allow a single-threaded process to command a core for a higher percentage of the time and in longer bursts.
Are threads from the same process more likely to be scheduled at the same time on multiple cores?
Typically no. Why would you want to do that? That would tend to degrade overall system performance as threads from the same process are more likely to step on each other's toes. You want the system to get other process' work done efficiently so you get the CPU back.
Is there an "active process" notion?
To some extent. Windows has precisely such a notion -- a "foreground process". Most OSes don't. But they do have a "dynamic priority boost" feature. Basically, if a process is sitting around doing nothing and then needs to do something, it is given some priority as a "reward". This allows a process that sits around waiting for work to be done to get its work done quickly and makes the system feel more interactive and responsive. It often makes little sense on servers, but it's helpful on desktops. Whether this is implemented on threads individually or on all the threads of a process as a group is implementation specific.
If you run separate processes or threads that doesn't needs to interact each others then it will be far better having 4 cores rather then having just 1.
As soon as the processes or threads needs to share some data, you will get the overhead to serialize the access to the shared data.
A lot depends on how good an application is written to run on a multi-core CPU. It may happen in the worst case that trying to run an application on a 4-core CPU is slower than running it on a single core CPU; more likely the increase in performance would be far less than 100%.

Considerate, dynamic CPU load management

I am writing a CPU-intensive image processing library. To make best use of available CPU, I can detect the total number of cores on my machine and have my library run with that number of threads. When my library to allocate one thread for each core it performs optimally using 100% available processor time.
The above approach works fine when mine is the only CPU-heavy process running. If another CPU-intensive process is running, or even another instance of my own code, then the OS allocates us only a fraction of the available cores and my library then has too many threads running which is both inefficient and inconsiderate to other processes.
So I would like to find a way to determine the "fair share" number of threads to run given a specific load. For example, if two instances of my process are running on an 8-core machine, each would run with 4 threads. Each would need a way to adapt thread count dynamically according to fluctuations in machine load.
So, my question:
Is there any OS feature or third-party library which allows my process to adapt thread count dynamically to use its fair share of the CPU?
My focus is Windows but interested in non-Windows solutions too.
Edit: to be clear, this is about optimization. I am trying to achieve peak efficiency by running the optimal number of threads appropriate to my fair share of the CPU.
In my eyes, the application shouldnt decide how many threads to spawn. This is an information, that the caller should know. In linux, the "-j" or "--jobs" parameter is widely used (Default: 1).
What about also setting the priority of the processing tasks. So if the caller knows, the processing is mission-critical, he can increase the prio (with the knowledge of maybe blocking the (whole) system). Your processing lib would never know, how important the processing of this image would be.
If the caller doesnt care, then the default low-prio is used, which shouldnt affect the rest of the system. If it does, you should look to what is exactly blocking the system (maybe writing image files to the hdd, reduce ram size to prevent swapping, ...). If you figured out that, you can optimize exactly that point.
If you start the processing with (cpu-cores)*2 on low till normal priority, your system should be useable. No one would expect, that this will kill the system.
Just my 2 cents.
Actually it's not a problem of multithreading but a problem of executing many programs simultaneously. This is hard on most PC's operating systems because it conflicts to the idea of time-sharing.
Let's assume some workflow.
Suppose we have 8 cores and we create 8 threads to feed them; ok, that's easy. Next we choose to monitor core loading to summary how many tasks running on a certain core; well, that needs some statistical assumptions, e.g on Linux you can get a 1/5/15-mins load average chart, but that could be done. The statistical chart is clear and now we get a plot about how many CPU-bound processes are running, say, seeing other 3 CPU-intensive processes.
Then we come to the point: we have to make 3 redundant threads to sleep, but which 3?
Usually we choose 3 threads arbitrarily because the scheduler arranges the other 8 CPU-bound threads automatically. In some cases, we explicitly put threads on high load cores to sleep, assign other threads to certain low load cores, and let the scheduler do the rest things. Most scheduling policies also try to "keep CPU cache hot", which means they tend to forbid transferring threads between cores. We reasonably expect our CPU-intensive threads can utilize the core cache since other processes are scheduled to the 3 crowded cores. Everything looks good.
However this could fail in tightly synchronized computation. In this scenario we need to run our 5 threads simultaneously. Simultaneity here means the 5 threads have to gain CPU and run at almost the same time. I don't know if there's any scheduler on PC could do this for us. In most low-load cases, things still work fine because costs to wait for simultaneity is trivial. But when the load of a core is high and even 1 of our 5 threads is disturbed, occasionally we'll find we spend many life cycles in waiting.
It may help to schedule your program as a real-time program but it's not a perfect solution. Statistically it leads to a wider time window for simultaneity when it gains more CPU control priority. I have to say, it's not guaranteed.

Threads & Processes Vs MultiThreading & Multi-Core/MultiProcessor : How they are mapped?

I was very confused but the following thread cleared my doubts:
Multiprocessing, Multithreading,HyperThreading, Multi-core
But it addresses the queries from the hardware point of view. I want to know how these hardware features are mapped to software?
One thing that is obvious is that there is no difference between MultiProcessor(=Mutlicpu) and MultiCore other than that in multicore all cpus reside on one chip(die) where as in Multiprocessor all cpus are on their own chips & connected together.
So, mutlicore/multiprocessor systems are capable of executing multiple processes (firefox,mediaplayer,googletalk) at the "sametime" (unlike context switching these processes on a single processor system) Right?
If it correct. I'm clear so far. But the confusion arises when multithreading comes into picture.
MultiThreading "is for" parallel processing. right?
What are elements that are involved in multithreading inside cpu? diagram? For me to exploit the power of parallel processing of two independent tasks, what should be the requriements of CPU?
When people say context switching of threads. I don't really get it. because if its context switching of threads then its not parallel processing. the threads must be executed "scrictly simultaneously". right?
My notion of multithreading is that:
Considering a system with single cpu. when process is context switched to firefox. (suppose) each tab of firefox is a thread and all the threads are executing strictly at the same time. Not like one thread has executed for sometime then again another thread has taken until the context switch time is arrived.
What happens if I run a multithreaded software on a processor which can't handle threads? I mean how does the cpu handle such software?
If everything is good so far, now question is HOW MANY THREADS? It must be limited by hardware, I guess? If hardware can support only 2 threads and I start 10 threads in my process. How would cpu handle it? Pros/Cons? From software engineering point of view, while developing a software that will be used by the users in wide variety of systems, Then how would I decide should I go for multithreading? if so, how many threads?
First, try to understand the concept of 'process' and 'thread'. A thread is a basic unit for execution: a thread is scheduled by operating system and executed by CPU. A process is a sort of container that holds multiple threads.
Yes, either multi-processing or multi-threading is for parallel processing. More precisely, to exploit thread-level parallelism.
Okay, multi-threading could mean hardware multi-threading (one example is HyperThreading). But, I assume that you just say multithreading in software. In this sense, CPU should support context switching.
Context switching is needed to implement multi-tasking even in a physically single core by time division.
Say there are two physical cores and four very busy threads. In this case, two threads are just waiting until they will get the chance to use CPU. Read some articles related to preemptive OS scheduling.
The number of thread that can physically run in concurrent is just identical to # of logical processors. You are asking a general thread scheduling problem in OS literature such as round-robin..
I strongly suggest you to study basics of operating system first. Then move on multithreading issues. It seems like you're still unclear for the key concepts such as context switching and scheduling. It will take a couple of month, but if you really want to be an expert in computer software, then you should know such very basic concepts. Please take whatever OS books and lecture slides.
Threads running on the same core are not technically parallel. They only appear to be executed in parallel, as the CPU switches between them very fast (for us, humans). This switch is what is called context switch.
Now, threads executing on different cores are executed in parallel.
Most modern CPUs have a number of cores, however, most modern OSes (windows, linux and friends) usually execute much larger number of threads, which still causes context switches.
Even if no user program is executed, still OS itself performs context switches for maintanance work.
This should answer 1-3.
About 4: basically, every processor can work with threads. it is much more a characteristic of operating system. Thread is basically: memory (optional), stack and registers, once those are replaced you are in another thread.
5: the number of threads is pretty high and is limited by OS. Usually it is higher than regular programmer can successfully handle :)
The number of threads is dictated by your program:
is it IO bound?
can the task be divided into a number of smaller tasks?
how small is the task? the task can be too small to make it worth to spawn threads at all.
synchronization: if extensive synhronization is required, the penalty might be too heavy and you should reduce the number of threads.
Multiple threads are separate 'chains' of commands within one process. From CPU point of view threads are more or less like processes. Each thread has its own set of registers and its own stack.
The reason why you can have more threads than CPUs is that most threads don't need CPU all the time. Thread can be waiting for user input, downloading something from the web or writing to disk. While it is doing that, it does not need CPU, so CPU is free to execute other threads.
In your example, each tab of Firefox probably can even have several threads. Or they can share some threads. You need one for downloading, one for rendering, one for message loop (user input), and perhaps one to run Javascript. You cannot easily combine them because while you download you still need to react to user's input. However, download thread is sleeping most of the time, and even when it's downloading it needs CPU only occasionally, and message loop thread only wakes up when you press a button.
If you go to task manager you'll see that despite all these threads your CPU use is still quite low.
Of course if all your threads do some number-crunching tasks, then you shouldn't create too many of them as you get no performance benefit (though there may be architectural benefits!).
However, if they are mainly I/O bound then create as many threads as your architecture dictates. It's hard to give advice without knowing your particular task.
Broadly speaking, yeah, but "parallel" can mean different things.
It depends what tasks you want to run in parallel.
Not necessarily. Some (indeed most) threads spend a lot of time doing nothing. Might as well switch away from them to a thread that wants to do something.
The OS handles thread switching. It will delegate to different cores if it wants to. If there's only one core it'll divide time between the different threads and processes.
The number of threads is limited by software and hardware. Threads consume processor and memory in varying degrees depending on what they're doing. The thread management software may impose its own limits as well.
The key thing to remember is the separation between logical/virtual parallelism and real/hardware parallelism. With your average OS, a system call is performed to spawn a new thread. What actually happens (whether it is mapped to a different core, a different hardware thread on the same core, or queued into the pool of software threads) is up to the OS.
Parallel processing uses all the methods not just multi-threading.
Generally speaking, if you want to have real parallel processing, you need to perform it in hardware. Take the example of the Niagara, it has up to 8-cores each capable of executing 4-threads in hardware.
Context switching is needed when there are more threads than is capable of being executed in parallel in hardware. Even then, when executed in series (switching between one thread to the next), they are considered concurrent because there is no guarantee on the order of switching. So, it may go T0, T1, T2, T1, T3, T0, T2 and so on. For all intents and purposes, the threads are parallel.
Time slicing.
That would be up to the OS.
Multithreading is the execution of more than one thread at a time. It can happen both on single core processors and the multicore processor systems. For single processor systems, context switching effects it. Look!Context switching in this computational environment refers to time slicing by the operating system. Therefore do not get confused. The operating system is the one that controls the execution of other programs. It allows one program to execute in the CPU at a time. But the frequency at which the threads are switched in and out of the CPU determines the transparency of parallelism exhibited by the system.
For multicore environment,multithreading occurs when each core executes a thread.Though,in multicore again,context switching can occur in the individual cores.
I think answers so far are pretty much to the point and give you a good basic context. In essence, say you have quad core processor, but each core is capable of executing 2 simultaneous threads.
Note, that there is only slight (or no) increase of speed if you are running 2 simultaneous threads on 1 core versus you run 1st thread and then 2nd thread vertically. However, each physical core adds speed to your general workflow.
Now, say you have a process running on your OS that has multiple threads (i.e. needs to run multiple things in "parallel") and has some kind of stack of tasks in a queue (or some other system with priority rules). Then software sends tasks to a queue and your processor attempts to execute them as fast as it can. Now you have 2 cases:
If a software supports multiprocessing, then tasks will be sent to any available processor (that is not doing anything or simply finished doing some other job and job send from your software is 1st in a queue).
If your software does not support multiprocessing, then all of your jobs will be done in a similar manner, but only by one of your cores.
I suggest reading Wikipedia page on thread. Very first picture there already gives you a nice insight. :)

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