Multithreading in c linux

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Using multiple thread to complete a certain task to improve code efficiency.

samuelpio01/multithreading-in-c

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README.md

(can be used in C++ too but instead of using ‘gcc’ for compiling, use ‘g++’)

Using multiple thread to complete a certain task to improve code efficiency.

This program is compiled and executed on CentOS system

Write a program to find points (x,y) in an array such that between no two points there exists another value ‘z’ in the array which falls between ‘x’ and ‘y’.

ie: the point z should not be between x and y.

Print the value of the points (x,y) which have no values between them and the distance between them.

 (0,1) or (1,0) = 1 (3,5) or (5,3) = 2 (3,2) or (2,3) = 1 (5,7) or (7,5) = 2 (7,10) or (10,7) = 3 (1,2) or (2,1) = 1 

To compile the singlethread_execution.c file

Compile: GCC compiler: gcc singlethread_execution.c -o singlethread_execution

—> An executable file pthread_multithreading will be created.

To execute the singlethread_execution file

2. Using POSIX Thread Library (pthread)

To compile the pthread_multithreading.c file

Compile: GCC compiler: gcc pthread_multithreading.c -o pthread_multithreading -lpthread

Note: It is mandatory to compile the file using -lpthread as we are using the POSIX thread library, otherwise the compilation will give an error.

—> An executable file pthread_multithreading will be created.

To execute the pthread_multithreading file

For the syntax of pthread_create() or pthread_join() refer Linux Programmers Manual 

The Order of the Output may not be in the same sequence but it will definitely give all the possibilities because the order would depend on the scheduling of the thread.

OpenMP (Open Multi-Processing) is an application programming interface (API) that supports multi-platform shared memory multiprocessing programming in C, C++, and Fortran, on most platforms, instruction set architectures (ISA) and operating systems, including Solaris, AIX, HP-UX, Linux, macOS, and Windows. It consists of a set of compiler directives, library routines, and environment variables that influence run-time behavior.

You might have noticed the changes that are required in the code to spawn threads using POSIX Thread Library. To overcome that a better option would be to use the OpenMP API.

In your code, do not forget to #include library

To Compile and Execute use the same commands as of Single Threads.

There is a big difference when it comes to Performance which is counted in terms of Latency and Throughput.

Latency (Execution time): Time taken to finish execution of a certain task or CPU intensive calculations the time taken to complete the task will be higher.

Throughput : Number of tasks executed in a fixed time.

To check execution time of the process use ‘time’ before the Execution command

eg: time ./pthread_multithreading

In the programs above it may not take much time with the given size of array. But try to increase the size of the array to 3000 or 5000 and then you will notice a significant difference in execution time.

This can also be tried on Multiplication of nxn matrices or any code that take lots of CPU time for calculations. It will definitely improve the performance.

To check number of CPU’s and CPU threads and other CPU info

Number of Cores in your system (Shown by CPUS) = No of Sockets x No Cores per socket x No of Threads per Core

To check utilization of CPU threads

Use the command htop in terminal.

If htop is not installed on your Linux system then follow the instructions below

Installation of ‘htop’

For RHEL, CentOS & Fedora Systems:

Once htop is installed on your system you can simply run it with the command:

You will see something like this

Since on my machine(CPU) has 8 cores we can see numbers between 1 to 8 which represent the CPU core and along with it is the Utilization of CPU (in %).

This is how I have handled multithreading. I’m open to suggestions. Shoot in your questions or suggestions at samuelpio01@gmail.com

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Using multiple thread to complete a certain task to improve code efficiency.

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Программирование C в Linux — потоки pthreads

Многопоточность в программировании является важным механизмом в наше время. Поэтому я решил посвятить несколько статей этой теме.

В семействах ОС Windows — каждая программа запускает один процесс выполнения, в котором находится как минимум один поток (нить). В процессе может находиться множество потоков, между которыми делится процессорное время. Один процесс не может напрямую обратиться к памяти другого процесса, а потоки же разделяют одно адресное пространство одного процесса. То есть в Windows — процесс это совокупность потоков.

В Linux же немного по-другому. Сущность процесса такая же, как и в Windows — это исполняемая программа со своими данными. Но вот поток в Linux является отдельным процессом (можно встретить название как «легковесный процесс», LWP). Различие такое же — процесс отдельная программа со своей памятью, не может напрямую обратиться к памяти другого процесса, а вот поток, хоть и отдельный процесс, имеет доступ к памяти процесса-родителя [2]. LWP процессы создаются с помощью системного вызова clone() с указанием определенных флагов.

Но также имеется такая вещь, которая называется «POSIX Threads» — библиотечка стандарта POSIX, которая организует потоки (они же нити) внутри процесса. Т.е тут уже распараллеливание происходит в рамках одного процесса.

И тут встает вопрос различия терминов «поток», «процесс», «нить» и т.д. Проблема в том, что в англоязычной литературе данные термины определяются однозначно, у нас же с нашим великим и могучим имеются противоречия, что может привести к дикому диссонансу.

Но это все в общих чертах, для более точной информации следует обратиться к соответствующей литературе, либо к официальной документации, можно почитать man’ы. В конце статьи я приведу несколько полезных ссылок на ресурсы, где более подробно расписано как все работает, а пока займемся практикой.

Я рассмотрю два варианта «распараллеливания» программы — создания потока/нити с помощью функций из pthread.h (POSIX Threads), либо создание отдельного процесса с помощью функции fork().

Сегодня рассмотрим потоки из библиотеки pthread.

Шаблон кода для работы с потоками выглядит следующим образом:

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C threading in linux?

Does someone have a simple example of threading in c? I want to build a small console app that will read a txt file file line by line and then use threads to process the entire txt. How should I do this? splitting the txt into X where X=N of threads, is the first thing that comes to my mind, is there a better way?

How to split and is it needed or not is very very your design specific. What do you mean by processing, what kind of data in file.. there is no one solution for all cases.

6 Answers 6

Search for pthreads. I’m also a thread newbie. Here is a code snippet to sum from 1 to 1000000000 (also my first working pthread program).

#include #include struct arg < int a, b; int *rst; >; typedef struct arg arg; void* sum(void *); int main() < pthread_t sum1, sum2; int s1, s2; pthread_create(&sum1, NULL, sum, &(arg)); pthread_create(&sum2, NULL, sum, &(arg)); pthread_join(sum1, NULL); pthread_join(sum2, NULL); printf("%d\n", s1 + s2); > void* sum(void *ptr) < int i, temp = 0; arg *x = ptr; for(i = x->a; i b; ++i) temp += i; *(x->rst) = temp; > 

rst should be declared volatile . Also, this code is only valid under the C99 standard, this is not valid C89.

rst does not need to be a volatile qualfied pointer, the code is fine. The store to *(x->rst) cannot be elided by the compiler, because it cannot determine if its externally visible; and the pthread_join implies a barrier.

The best option IMHO is to use POSIX threads. You can see more details HERE.

Also please check the link in James’ answer.

Search for POSIX threads, also known as pthreads. Tutorial Here

If you want an easy way to do it, OpenMP is a powerful multithreading library which is supported by gcc.

This will perform simple addition of two arrays and store the result in «a», but on a quad core machine, will spawn 4 threads to handle it, ( 8 if hyperthreading is supported).

Easy multicore programming on Linux. 🙂

First thing is asking yourself whether you really need to do multi-threading here. Do you need shared state between the threads, e.g. does the parses information from all the URLS end up in the same data structure? If not, processes (fork) might be sufficient. Or you might not even go that far and just use event-based programming (glib, libev).

Glib might be worth your while even if you decide to use threads after all, as it has a decent thread abstraction, including thread pools. This would make partitioning your file very easy, as you just create X thread pools, then add the dl/parse pools to one of them (line-no. % pool size).

If it’s just about speeding up downloads, maybe your http library already has related functionality. For curl, there’s a bunch of curl_multicalls, with an interesting example here.

By the way, amongst the curl examples, there’s also a multi-thread one that might just be what you need.

splitting the txt into X where X=N of threads, is the first thing that comes to my mind, is there a better way?

It depends on your application.

• Threads may help if interpreting the data is the bottleneck, the performance gain will be limited by the file I/O speed
• Threads wont help if reading the file is the bottleneck, the disk I/O is limited by the hardware and will only degrade if more threads request data

If interpreting the information takes long you can use something like the producer consumer pattern and test yourself how much threads you need. (try with a low number and see how many give you the best performance). Some examples can be found here and here

As the other answers point out you can use pthreads to implement threading.

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