How do you keep a Visual Basic program (or, better, only a single portion of it) to a single thread? For example
[Hypothetical thread limiting command here]
my code and such
[End thread limitation]
Is there any way to do this? Sorry if I am being ambiguous.
Unless you are explicitly starting other threads, or are using a 3rd party library that uses threads, Visual Basic (or any other .NET language) will not run with multiple threads. You may see some debugging messages about threads starting and shutting down, but those are from the garbage collector running in the background and not your application.
Web projects are an exception to this, as each request will be handled on a separate thread.
UPDATE
What you are seeing is most likely a combination of multiple effects.
The most important being something called Hyper-threading. Despite it's name, it has nothing to do with threads at the application level. Most likely the CPU in your computer has only 2 physical cores that support Hyper-threading (HT). HT will make each physical core show up as 2 logical cores in the operating system. The CPU will decide to process instructions on one or both of these cores on its own. This isn't true multi-threading, and you will never have to worry about any effects from HT in your code.
Another cause for what you are seeing is called Processor affinity(PA), or more properly, the lack of PA. The operating system has the choice of which logical CPUs to execute your code on. It also has the option of moving that execution around to different CPUs to try and optimize its workload. It can do this whenever it wants and as often as it wants; sometimes it can happen very rapidly. Depending on your OS you can "pin" a program to a specific core (or set of cores) to stop this from happening, but again, it won't should not affect your program's execution in any way.
As far as the rise in CPU temperature you are seeing across all core, it can be explained pretty easily. The physical cores on your CPU are very close together, under a heat-sink. As one core heats up it will warm up the other core near it.
Related
I believe I have a reasonable understanding of threading from an Object Oriented perspective using the Thread class and the Runnable interface. In one of my applications there is a "download" button that allows the user to run a task in the background that takes about half an hour whilst continuing to use the VB.NET application.
However, I do not understand how Threading maps to the physical architecture of a computer. If you have a single threaded application that runs on a PC with a quadcore processor then does a .net program use all four processors?
If you have a multi threaded application (say four threads) on a quadcore processor then does each thread execute on different cores?
Do you have any control of this as a developer?
I have referenced a book I read at university called Operating System Concepts, but I have not found a specific answer.
If you have a single threaded application that runs on a PC with a quadcore processor then does a .net program use all four processors?
No, it can’t, at least not simultaneously. However, it’s theoretically possible that the operating system’s scheduler first executes your thread on one processor and later moves it to another processor. Such a scheduler is necessary to allow simultaneously running more applications / threads than there are physical processors present: execution of a thread is sliced into small pieces, which are fed to the processor(s) one after the other. Each threads gets some time slice allocated during which it can calculate before usage of the CPU switches to another thread.
Do you have any control of this as a developer?
Not directly. What you can control is the priority of your thread to make it more important to the task scheduler.
On a more general note, you should not use threads in your use-case – at least not directly. Threads are actually pretty low-level primitives. For your specific use-case, there’s a component called BackgroundWorker which abstracts many of the low-level details of thread management for you.
If you have a multi threaded application (say four threads) on a quadcore processor then does each thread execute on different cores?
Not necessarily; again, the application has next to no control over how exactly its threads are executed; the operating system however tries really hard to schedule threads “smartly”. This means that in practice, if your application has several busy threads, they are spread out as evenly as possible across the available cores. In particular, if there are no more threads than cores then each thread gets its own core.
Generally, you do not need to worry about mapping to physical architecture, .NET and the OS will do their best to maximize efficiency of your application. Just make it multi-threaded, even at the cost of being slower on a single threaded computer. You can, however, limit your maximum number of threads (if your app theoretically scales to infinity), to a number of cores, or double that. Test performance for each case, and decide which maximum works best for you.
Sometimes setting a core # can make your app's performance even worse. For example, if core #1 is currently scanning your PC for viruses, and your antivirus is single threaded. With the above scenario, assuming a quad-core PC, you do NOT want to run your 4-threaded app on a 1-per-core basis.
Having said that, if you really want to run a thread on specific core, it is possible - see this:
How to start a Thread at Specific Core
How Can I Set Processor Affinity in .NET?
Also check this out:
How to control which core a process runs on?
Which takes longer time?
Switching between the user & kernel modes (or) switching between two processes?
Please explain the reason too.
EDIT : I do know that whenever there is a context switch, it takes some time for the dispatcher to save the status of the previous process in its PCB, and then reload the next process from its corresponding PCB. And for switching between the user and the kernel modes, I know that the mode bit has to be changed. Isn't it all, or is there more to it?
Switching between processes (given you actually switch, not run them in parallel) by an order of oh-my-god.
Trapping from userspace to kernelspace used to be done with a processor interrupt earlier. Around 2005 (don't remember the kernel version), and after a discussion on the mailing list where someone found that trapping was slower (in absolute measures!) on a high-end xeon processor than on an earlier Pentium II or III (again, my memory), they implemented it with a new cpu instruction sysenter (which had actually existed since Pentium Pro I think). This is done in the Virtual Dynamic Shared Object (vdso) page in each process (cat /proc/pid/maps to find it) IIRC.
So, nowadays, a kernel trap is basically just a couple of cpu instructions, hence rather few cycles, compared to tenths or hundreds of thousands when using an interrupt (which is really slow on modern CPU's).
A context switch between processes is heavy. It means storing all processor state (registers, etc) to RAM (at a magic memory location in the user process space actually, guess where!), in practice dirtying all cached memory in the cpu, and reading back the process state for the new process. It will (likely) have nothing still in the cpu cache from last time it ran, so each memory read will be a cache miss, and needed to be read from RAM. This is rather slow. When I was at the university, I "invented" (well, I did come up with the idea, knowing that there is plenty of dye in a CPU, but not enough cool if it's constantly powered) a cache that was infinite size although unpowered when unused (only used on context switches i.e.) in the CPU, and implemented this in Simics. Implemented support for this magic cache I called CARD (Context-switch Active, Run-time Drowsy) in Linux, and benchmarked rather heavily. I found that it could speed-up a Linux machine with lots of heavy processes sharing the same core with about 5%. This was at relatively short (low-latency) process time slices, though.
Anyway. A context switch is still pretty heavy, while a kernel trap is basically free.
Answer to at which memory location in user-space, for each process:
At address zero. Yep, the null pointer! You can't read from this entire page from user-space anyway :) This was back in 2005, but it's probably the same now unless the CPU state information has grown larger than a page size, in which case they might have changed the implementation.
I'm doing some fill in the blanks from a sample exam for my class and I was hoping you could double check my terminology.
The various scheduling queues used by the operating system would consist of lists of processes.
Interrupt handling is the technique of periodically checking to see if a condition (such as completion of some requested I/O operation) has been met.
When the CPU is in kernel mode, a running program has access to a restricted set of CPU functionality.
The job of the CPU scheduler is to select a process on the ready queue and change its state.
The CPU normally supports a vector of interrupts so the OS can respond appropriately when some event of interest occurs in the hardware.
Using traps, a device controller can use idle time on the bus to read from or write to main memory.
During a context switch, the state of one process is copied from the CPU and saved, and the state of a different process is restored.
An operating system consists of a kernel and a collection of application programs that run as user processes and either provide OS services to the user or work in the background to keep the computer running smooth.
There are so many terms from our chapters, I am not quite sure if I am using the correct ones.
My thoughts:
1. Processes and/or threads. Jobs and tasks aren't unheard of either. There can be other things. E.g. in MS Windows there are also Deferred Procedure Calls (DPCs) that can be queued.
2. This must be polling.
4. Why CPU scheduler? Why not just scheduler?
6. I'm not sure about traps in the hardware/bus context.
TL;DR: Is it possible that I am reactor throughput limited? How would I tell? How expensive and scalable (across threads) is the implementation of the io_service?
I have a farily massively parallel application, running on a hyperthreaded-dual-quad-core-Xeon machine with tons of RAM and a fast SSD RAID. This is developed using boost::asio.
This application accepts connections from about 1,000 other machines, reads data, decodes a simple protocol, and shuffles data into files mapped using mmap(). The application also pre-fetches "future" mmap pages using madvise(WILLNEED) so it's unlikely to be blocking on page faults, but just to be sure, I've tried spawning up to 300 threads.
This is running on Linux kernel 2.6.32-27-generic (Ubuntu Server x64 LTS 10.04). Gcc version is 4.4.3 and boost::asio version is 1.40 (both are stock Ubuntu LTS).
Running vmstat, iostat and top, I see that disk throughput (both in TPS and data volume) is on the single digits of %. Similarly, the disk queue length is always a lot smaller than the number of threads, so I don't think I'm I/O bound. Also, the RSS climbs but then stabilizes at a few gigs (as expected) and vmstat shows no paging, so I imagine I'm not memory bound. CPU is constant at 0-1% user, 6-7% system and the rest as idle. Clue! One full "core" (remember hyper-threading) is 6.25% of the CPU.
I know the system is falling behind, because the client machines block on TCP send when more than 64kB is outstanding, and report the fact; they all keep reporting this fact, and throughput to the system is much less than desired, intended, and theoretically possible.
My guess is I'm contending on a lock of some sort. I use an application-level lock to guard a look-up table that may be mutated, so I sharded this into 256 top-level locks/tables to break that dependency. However, that didn't seem to help at all.
All threads go through one, global io_service instance. Running strace on the application shows that it spends most of its time dealing with futex calls, which I imagine have to do with the evented-based implementation of the io_service reactor.
Is it possible that I am reactor throughput limited? How would I tell? How expensive and scalable (across threads) is the implementation of the io_service?
EDIT: I didn't initially find this other thread because it used a set of tags that didn't overlap mine :-/ It is quite possible my problem is excessive locking used in the implementation of the boost::asio reactor. See C++ Socket Server - Unable to saturate CPU
However, the question remains: How can I prove this? And how can I fix it?
The answer is indeed that even the latest boost::asio only calls into the epoll file descriptor from a single thread, not entering the kernel from more than one thread at a time. I can kind-of understand why, because thread safety and lifetime of objects is extremely precarious when you use multiple threads that each can get notifications for the same file descriptor. When I code this up myself (using pthreads), it works, and scales beyond a single core. Not using boost::asio at that point -- it's a shame that an otherwise well designed and portable library should have this limitation.
I believe that if you use multiple io_service object (say for each cpu core), each run by a single thread, you will not have this problem. See the http server example 2 on the boost ASIO page.
I have done various benchmarks against the server example 2 and server example 3 and have found that the implementation I mentioned works the best.
In my single-threaded application, I found out from profiling that a large portion of the processor instructions was spent on locking and unlocking by the io_service::poll(). I disabled the lock operations with the BOOST_ASIO_DISABLE_THREADS macro. It may make sense for you, too, depending on your threading situation.
What is the difference between a thread/process/task?
Process:
A process is an instance of a computer program that is being executed.
It contains the program code and its current activity.
Depending on the operating system (OS), a process may be made up of multiple threads of execution that execute instructions concurrently.
Process-based multitasking enables you to run the Java compiler at the same time that you are using a text editor.
In employing multiple processes with a single CPU,context switching between various memory context is used.
Each process has a complete set of its own variables.
Thread:
A thread is a basic unit of CPU utilization, consisting of a program counter, a stack, and a set of registers.
A thread of execution results from a fork of a computer program into two or more concurrently running tasks.
The implementation of threads and processes differs from one operating system to another, but in most cases, a thread is contained inside a process. Multiple threads can exist within the same process and share resources such as memory, while different processes do not share these resources.
Example of threads in same process is automatic spell check and automatic saving of a file while writing.
Threads are basically processes that run in the same memory context.
Threads may share the same data while execution.
Thread Diagram i.e. single thread vs multiple threads
Task:
A task is a set of program instructions that are loaded in memory.
Short answer:
A thread is a scheduling concept, it's what the CPU actually 'runs' (you don't run a process). A process needs at least one thread that the CPU/OS executes.
A process is data organizational concept. Resources (e.g. memory for holding state, allowed address space, etc) are allocated for a process.
To explain on simpler terms
Process: process is the set of instruction as code which operates on related data and process has its own various state, sleeping, running, stopped etc. when program gets loaded into memory it becomes process. Each process has atleast one thread when CPU is allocated called sigled threaded program.
Thread: thread is a portion of the process. more than one thread can exist as part of process. Thread has its own program area and memory area. Multiple threads inside one process can not access each other data. Process has to handle sycnhronization of threads to achieve the desirable behaviour.
Task: Task is not widely concept used worldwide. when program instruction is loaded into memory people do call as process or task. Task and Process are synonyms nowadays.
A process invokes or initiates a program. It is an instance of a program that can be multiple and running the same application. A thread is the smallest unit of execution that lies within the process. A process can have multiple threads running. An execution of thread results in a task. Hence, in a multithreading environment, multithreading takes place.
A program in execution is known as process. A program can have any number of processes. Every process has its own address space.
Threads uses address spaces of the process. The difference between a thread and a process is, when the CPU switches from one process to another the current information needs to be saved in Process Descriptor and load the information of a new process. Switching from one thread to another is simple.
A task is simply a set of instructions loaded into the memory. Threads can themselves split themselves into two or more simultaneously running tasks.
for more Understanding refer the link: http://www.careerride.com/os-thread-process-and-task.aspx
Wikipedia sums it up quite nicely:
Threads compared with processes
Threads differ from traditional multitasking operating system processes in that:
processes are typically independent, while threads exist as
subsets of a process
processes carry considerable state information, whereas multiple
threads within a process share state
as well as memory and other resources
processes have separate address spaces, whereas threads share their
address space
processes interact only through system-provided inter-process
communication mechanisms.
Context switching between threads in the same process is
typically faster than context
switching between processes.
Systems like Windows NT and OS/2 are said to have "cheap" threads and "expensive" processes; in other operating systems there is not so great a difference except the cost of address space switch which implies a TLB flush.
Task and process are used synonymously.
from wiki clear explanation
1:1 (Kernel-level threading)
Threads created by the user are in 1-1 correspondence with schedulable entities in the kernel.[3] This is the simplest possible threading implementation. Win32 used this approach from the start. On Linux, the usual C library implements this approach (via the NPTL or older LinuxThreads). The same approach is used by Solaris, NetBSD and FreeBSD.
N:1 (User-level threading)
An N:1 model implies that all application-level threads map to a single kernel-level scheduled entity;[3] the kernel has no knowledge of the application threads. With this approach, context switching can be done very quickly and, in addition, it can be implemented even on simple kernels which do not support threading. One of the major drawbacks however is that it cannot benefit from the hardware acceleration on multi-threaded processors or multi-processor computers: there is never more than one thread being scheduled at the same time.[3] For example: If one of the threads needs to execute an I/O request, the whole process is blocked and the threading advantage cannot be utilized. The GNU Portable Threads uses User-level threading, as does State Threads.
M:N (Hybrid threading)
M:N maps some M number of application threads onto some N number of kernel entities,[3] or "virtual processors." This is a compromise between kernel-level ("1:1") and user-level ("N:1") threading. In general, "M:N" threading systems are more complex to implement than either kernel or user threads, because changes to both kernel and user-space code are required. In the M:N implementation, the threading library is responsible for scheduling user threads on the available schedulable entities; this makes context switching of threads very fast, as it avoids system calls. However, this increases complexity and the likelihood of priority inversion, as well as suboptimal scheduling without extensive (and expensive) coordination between the userland scheduler and the kernel scheduler.