I just learn multiple threading programming, but the question here is a very basic concept need to be clarified first of all.
As I searched from internet, what i understand is Heavyweight is regarding to "process", and Lightweight maps to "thread". However, why process is heavyweight? because of non-sharing memory or something else?
"Heavyweight" concurrency is where each of the concurrent executors is expensive to start and/or has large overheads.
"Lightweight" concurrency is where each of the concurrent executors is cheap to start and/or has small overheads.
Processes are generally more expensive to manage for the OS than threads, since each process needs an independent address space and various management structures, whereas threads within a process share these structures.
Consequently, processes are considered heavyweight, whereas threads are lightweight.
However, in some contexts, threads are considered heavyweight, and the "lightweight" concurrency facility is some kind of "task". In these contexts, the runtime will typically execute these tasks on a pool of threads, suspending them when they block, and reusing the threads for other tasks.
Nowadays the "heavy" classification no longer carries the same weight as it used to while the advantage of process separation has lost none of its potency ;-)
This is all thanks to the copy-on-write semantics; during a fork() the pages from the parent are no longer blindly copied for the child process. Both processes can operate using shared memory until the child process starts to write into one of the shared memory pages.
Of course, creating more processes has a higher tendency of being limited by the operating system as process ids are a more limited resource than threads.
Related
I'm currently learning about actors in Scala. The book recommends using the react method instead of receive, because it allows the system to use less threads.
I have read why creating a thread is expensive. But what are the reasons that, once you have the threads (which should hold for the actor system in Scala after the initialization), having them around is expensive?
Is it mainly the memory consumption? Or are there any other reasons?
Using many threads may be more expensive than you would expect because:
each thread consumes memory outside of heap which places restriction on how many threads can be created at all for JVM;
switch from one thread to another consumes some CPU time, so if you have activity which can be performed in a single thread, you will save CPU cycles;
there's JVM scheduler which has more work to do if there are more threads. Same applies to underlying OS scheduler;
at last, it makes little sense to use more threads than you have CPU cores for CPU-bound tasks and it makes little sense to use more I/O threads than you have I/O activities (e.g., network clients).
Besides the memory overhead of having a thread around (which may or may not be small), having more threads around will also usually mean that the schedule will have more elements to consider when the time comes for it to pick which thread will get the CPU next.
Some Operating Systems / JVMs may also have constraints on the amount of threads that can concurrently exist.
Eventually, it's an accumulation of small overheads that can eventually account to a lot. And none of this is actually specific to Java.
Having threads around is not "expensive". Of course, it kinda depends on how many we're talking about here. I'd suspect billions of threads would be a problem. I think generally speaking, having a lot of threads is considered expensive because you can do more parallel work so CPU goes up, memory goes up, etc... But if they are correctly managed (pooled for example to protect the system resources) then it's ok. The JVM does not necessarily use native threads so a Java thread is not necessarily mapped to an OS native threads (i.e. look at green threads for example, or lightweight threads). In my opinion, there's no implicit cost to threads in the JVM. The cost comes from poor thread management and overuse of the resources by carelessly assigning them work.
What are the main advantages of using a model for concurrency based on processes over one
based on threads and in what contexts is the latter appropriate?
Fault-tolerance and scalability are the main advantages of using Processes vs. Threads.
A system that relies on shared memory or some other kind of technology that is only available when using threads, will be useless when you want to run the system on multiple machines. Sooner or later you will need to communicate between different processes.
When using processes you are forced to deal with communication via messages, for example, this is the way Erlang handles communication. Data is not shared, so there is no risk of data corruption.
Another advantage of processes is that they can crash and you can feel relatively safe in the knowledge that you can just restart them (even across network hosts). However, if a thread crashes, it may crash the entire process, which may bring down your entire application. To illustrate: If an Erlang process crashes, you will only lose that phone call, or that webrequest, etc. Not the whole application.
In saying all this, OS processes also have many drawbacks that can make them harder to use, like the fact that it takes forever to spawn a new process. However, Erlang has it's own notion of processes, which are extremely lightweight.
With that said, this discussion is really a topic of research. If you want to get into more of the details, you can give Joe Armstrong's paper on fault-tolerant systems]1 a read, it explains a lot about Erlang and the philosophy that drives it.
The disadvantage of using a process-based model is that it will be slower. You will have to copy data between the concurrent parts of your program.
The disadvantage of using a thread-based model is that you will probably get it wrong. It may sound mean, but it's true-- show me code based on threads and I'll show you a bug. I've found bugs in threaded code that has run "correctly" for 10 years.
The advantages of using a process-based model are numerous. The separation forces you to think in terms of protocols and formal communication patterns, which means its far more likely that you will get it right. Processes communicating with each other are easier to scale out across multiple machines. Multiple concurrent processes allows one process to crash without necessarily crashing the others.
The advantage of using a thread-based model is that it is fast.
It may be obvious which of the two I prefer, but in case it isn't: processes, every day of the week and twice on Sunday. Threads are too hard: I haven't ever met anybody who could write correct multi-threaded code; those that claim to be able to usually don't know enough about the space yet.
In this case Processes are more independent of eachother, while Threads shares some resources e.g. memory. But in a general case Threads are more light-weight than Processes.
Erlang Processes is not the same thing as OS Processes. Erlang Processes are very light-weight and Erlang can have many Erlang Processes within the same OS Thread. See Technically why is processes in Erlang more efficient than OS threads?
First and foremost, processes differ from threads mostly in the way their memory is handled:
Process = n*Thread + memory region (n>=1)
Processes have their own isolated memory.
Processes can have multiple threads.
Processes are isolated from each other on the operating system level.
Threads share their memory with their peers in the process.
(This is often undesirable. There are libraries and methods out there to remedy this, but that is usually an artificial layer over operating system threads.)
The memory thing is the most important discerning factor, as it has certain implications:
Exchanging data between processes is slower than between threads. Breaking the process isolation always requires some involvement of kernel calls and memory remapping.
Threads are more lightweight than processes. The operating system has to allocate resources and do memory management for each process.
Using processes gives you memory isolation and synchronization. Common problems with access to memory shared between threads do not concern you. Since you have to make a special effort to share data between processes, you will most likely sync automatically with that.
Using processes gives you good (or ultimate) encapsulation. Since inter process communication needs special effort, you will be forced to define a clean interface. It is a good idea to break certain parts of your application out of the main executable. Maybe you can split dependencies like that.
e.g. Process_RobotAi <-> Process_RobotControl
The AI will have vastly different dependencies compared to the control component. The interface might be simple: Process_RobotAI --DriveXY--> Process_RobotControl.
Maybe you change the robot platform. You only have to implement a new RobotControl executable with that simple interface. You don't have to touch or even recompile anything in your AI component.
It will also, for the same reasons, speed up compilation in most cases.
Edit: Just for completeness I will shamelessly add what the others have reminded me of :
A crashing process does not (necessarily) crash your whole application.
In General:
Want to create something highly concurrent or synchronuous, like an algorithm with n>>1 instances running in parallel and sharing data, use threads.
Have a system with multiple components that do not need to share data or algorithms, nor do they exchange data too often, use processes. If you use a RPC library for the inter process communication, you get a network-distributable solution at no extra cost.
1 and 2 are the extreme and no-brainer scenarios, everything in between must be decided individually.
For a good (or awesome) example of a system that uses IPC/RPC heavily, have a look at ros.
I've heard that under linux on multicore server it would be impossible to reach top performance when you have just 1 process but multiple threads because Linux have some limitations on the IO, so that 1 process with 8 threads on 8-core server might be slower than 8 processes.
Any comments? Are there other limitation which might slow the applications?
The applications is a network C++ application, serving 100s of clients, with some disk IO.
Update: I am concerned that there are some more IO-related issues other than the locking I implement myself... Aren't there any issues doing simultanious network/disk IO in several threads?
Drawbacks of Threads
Threads:
Serialize on memory operations. That is the kernel, and in turn the MMU must service operations such as mmap() that perform page allocations.
Share the same file descriptor table. There is locking involved making changes and performing lookups in this table, which stores stuff like file offsets, and other flags. Every system call made that uses this table such as open(), accept(), fcntl() must lock it to translate fd to internal file handle, and when make changes.
Share some scheduling attributes. Processes are constantly evaluated to determine the load they're putting on the system, and scheduled accordingly. Lots of threads implies a higher CPU load, which the scheduler typically dislikes, and it will increase the response time on events for that process (such as reading incoming data on a socket).
May share some writable memory. Any memory being written to by multiple threads (especially slow if it requires fancy locking), will generate all kinds of cache contention and convoying issues. For example heap operations such as malloc() and free() operate on a global data structure (that can to some degree be worked around). There are other global structures also.
Share credentials, this might be an issue for service-type processes.
Share signal handling, these will interrupt the entire process while they're handled.
Processes or Threads?
If you want to make debugging easier, use threads.
If you are on Windows, use threads. (Processes are extremely heavyweight in Windows).
If stability is a huge concern, try to use processes. (One SIGSEGV/PIPE is all it takes...).
If threads aren't available, use processes. (Not so common now, but it did happen).
If your threads share resources that can't be use from multiple processes, use threads. (Or provide an IPC mechanism to allow communicating with the "owner" thread of the resource).
If you use resources that are only available on a one-per-process basis (and you one per context), obviously use processes.
If your processing contexts share absolutely nothing (such as a socket server that spawns and forgets connections as it accept()s them), and CPU is a bottleneck, use processes and single-threaded runtimes (which are devoid of all kinds of intense locking such as on the heap and other places).
One of the biggest differences between threads and processes is this: Threads use software constructs to protect data structures, processes use hardware (which is significantly faster).
Links
pthreads(7)
About Processes and Threads (MSDN)
Threads vs. Processes
it really should make no difference but is probably about design.
A multi process app may have to do less locking but may use more memory. Sharing data between processes may be harder.
On the other hand multi process can be more robust. You can call exit() and quit the child safely mostly without affecting others.
It depends how dependent the clients are. I usually recommend the simplest solution.
Erlang's Characteristics
From Erlang Programming (2009):
Erlang concurrency is fast and scalable. Its processes are lightweight in that the Erlang virtual machine does not create an OS thread for every created process. They are created, scheduled, and handled in the VM, independent of underlying operating system. As a result, process creation time is of the order of microseconds and independent of the number of concurrently existing processes. Compare this with Java and C#, where for every process an underlying OS thread is created: you will get some very competitive comparisons, with Erlang greatly outperforming both languages.
From Concurrency oriented programming in Erlang (pdf) (slides) (2003):
We observe that the time taken to create an Erlang process is constant 1µs up to 2,500 processes; thereafter it increases to about 3µs for up to 30,000 processes. The performance of Java and C# is shown at the top of the figure. For a small number of processes it takes about 300µs to create a process. Creating more than two thousand processes is impossible.
We see that for up to 30,000 processes the time to send a message between two Erlang processes is about 0.8µs. For C# it takes about 50µs per message, up to the maximum number of processes (which was about 1800 processes). Java was even worse, for up to 100 process it took about 50µs per message thereafter it increased rapidly to 10ms per message when there were about 1000 Java processes.
My thoughts
I don't fully understand technically why Erlang processes are so much more efficient in spawning new processes and have much smaller memory footprints per process. Both the OS and Erlang VM have to do scheduling, context switches, and keep track of the values in the registers and so on...
Simply why aren't OS threads implemented in the same way as processes in Erlang? Do they have to support something more? And why do they need a bigger memory footprint? And why do they have slower spawning and communication?
Technically, why are processes in Erlang more efficient than OS threads when it comes to spawning and communication? And why can't threads in the OS be implemented and managed in the same efficient way? And why do OS threads have a bigger memory footprint, plus slower spawning and communication?
More reading
Inside the Erlang VM with focus on SMP (2008)
Concurrency in Java and in Erlang (pdf) (2004)
Performance Measurements of Threads in Java and Processes in Erlang (1998)
There are several contributing factors:
Erlang processes are not OS processes. They are implemented by the Erlang VM using a lightweight cooperative threading model (preemptive at the Erlang level, but under the control of a cooperatively scheduled runtime). This means that it is much cheaper to switch context, because they only switch at known, controlled points and therefore don't have to save the entire CPU state (normal, SSE and FPU registers, address space mapping, etc.).
Erlang processes use dynamically allocated stacks, which start very small and grow as necessary. This permits the spawning of many thousands — even millions — of Erlang processes without sucking up all available RAM.
Erlang used to be single-threaded, meaning that there was no requirement to ensure thread-safety between processes. It now supports SMP, but the interaction between Erlang processes on the same scheduler/core is still very lightweight (there are separate run queues per core).
After some more research I found a presentation by Joe Armstrong.
From Erlang - software for a concurrent world (presentation) (at 13 min):
[Erlang] is a concurrent language – by that I mean that threads are part of the programming language, they do not belong to the operating system. That's really what's wrong with programming languages like Java and C++. It's threads aren't in the programming language, threads are something in the operating system – and they inherit all the problems that they have in the operating system. One of the problems is granularity of the memory management system. The memory management in the operating system protects whole pages of memory, so the smallest size that a thread can be is the smallest size of a page. That's actually too big.
If you add more memory to your machine – you have the same number of bits that protects the memory so the granularity of the page tables goes up – you end up using say 64kB for a process you know running in a few hundred bytes.
I think it answers if not all, at least a few of my questions
I've implemented coroutines in assembler, and measured performance.
Switching between coroutines, a.k.a. Erlang processes, takes about 16 instructions and 20 nanoseconds on a modern processor. Also, you often know the process you are switching to (example: a process receiving a message in its queue can be implemented as straight hand-off from the calling process to the receiving process) so the scheduler doesn't come into play, making it an O(1) operation.
To switch OS threads, it takes about 500-1000 nanoseconds, because you're calling down to the kernel. The OS thread scheduler might run in O(log(n)) or O(log(log(n))) time, which will start to be noticeable if you have tens of thousands, or even millions of threads.
Therefore, Erlang processes are faster and scale better because both the fundamental operation of switching is faster, and the scheduler runs less often.
Erlang processes correspond (approximately) to green threads in other languages; there's no OS-enforced separation between the processes. (There may well be language-enforced separation, but that's a lesser protection despite Erlang doing a better job than most.) Because they're so much lighter-weight, they can be used far more extensively.
OS threads on the other hand are able to be simply scheduled on different CPU cores, and are (mostly) able to support independent CPU-bound processing. OS processes are like OS threads, but with much stronger OS-enforced separation. The price of these capabilities is that OS threads and (even more so) processes are more expensive.
Another way to understand the difference is this. Supposing you were going to write an implementation of Erlang on top of the JVM (not a particularly crazy suggestion) then you'd make each Erlang process be an object with some state. You'd then have a pool of Thread instances (typically sized according to the number of cores in your host system; that's a tunable parameter in real Erlang runtimes BTW) which run the Erlang processes. In turn, that will distribute the work that is to be done across the real system resources available. It's a pretty neat way of doing things, but relies utterly on the fact that each individual Erlang process doesn't do very much. That's OK of course; Erlang is structured to not require those individual processes to be heavyweight since it is the overall ensemble of them which execute the program.
In many ways, the real problem is one of terminology. The things that Erlang calls processes (and which correspond strongly to the same concept in CSP, CCS, and particularly the π-calculus) are simply not the same as the things that languages with a C heritage (including C++, Java, C#, and many others) call a process or a thread. There are some similarities (all involve some notion of concurrent execution) but there's definitely no equivalence. So be careful when someone says “process” to you; they might understand it to mean something utterly different…
I think Jonas wanted some numbers on comparing OS threads to Erlang processes. The author of Programming Erlang, Joe Armstrong, a while back tested the scalability of the spawning of Erlang processes to OS threads. He wrote a simple web server in Erlang and tested it against multi-threaded Apache (since Apache uses OS threads). There's an old website with the data dating back to 1998. I've managed only to find that site exactly once. So I can't supply a link. But the information is out there. The main point of the study showed that Apache maxed out just under 8K processes, while his hand written Erlang server handled 10K+ processes.
Because Erlang interpreter has only to worry about itself, the OS has many other things to worry about.
one of the reason is erlang process is created not in the OS, but in the evm(erlang virtual machine), so the cost is smaller.
how the process and threads performance will vary according to timslice.(how much time will approximately take to execute).in which situation we will use threads instead of process.
I'd like to rephrase your question as this: In what cases should a single application multiple threads, and in what cases should it use multiple processes instead?
In this question, time slices don't matter at all: operating systems today only schedule threads, and treat a "plain" process as having a single thread.
What does matter performance-wise is the creation overhead: creating a process is typically more expensive than creating a thread. Multi-processing applications avoid this cost be using pools, i.e. they create new processes only rarely, but reuse them when done with some task. As thread creation is still expensive, people often do the same with threads.
What also matters is communication overhead: in threads, you can easily share memory; in processes, you typically copy things (e.g. using a pipe). There are ways to share memory across processes as well, but those are fairly difficult to use.
So in general, threads should be faster than processes. Why people still use processes? Because they are the simpler programming model. Because of the shared memory in threads, it is very easy to make mistakes, and have libraries/APIs that are not thread-safe. Lack of thread-safety can be circumvented by using processes.