Already have an account? Get multiple benefits of using own account!
Login in your account..!
Remember me
Don't have an account? Create your account in less than a minutes,
Forgot password? how can I recover my password now!
Enter right registered email to receive password!
Present your own fully documented and tested programming example illustrating the problem of unbalanced loads. Describe the use of OpenMP's scheduler as a means of mitigating this problem.
The below example shows a number of tasks that all update a global counter. Since threads share the same memory space, they indeed see and update the same memory location. The code returns a false result because updating the variable is much quicker than creating the thread as on a multicore processor the chance of errors will greatly increase. If we artificially increase the time for the update, we will no longer get the right result. All threads read out the value of sum, wait a while (presumably calculating something) and then update.
#include
#include "pthread.h"
int sum=0;
void adder() {
int sum = 0;
int t = sum; sleep(1); sum = t+1;
return;
}
#define NTHREADS 50
int main() {
int i;
pthread_t threads[NTHREADS];
printf("forking\n");
for (i=0; i if (pthread_create(threads+i,NULL,&adder,NULL)!=0) return i+1; printf("joining\n"); for (i=0; i { if (pthread_join(threads[i],NULL)!=0) return NTHREADS+i+1; printf("Sum computed: %d\n",sum); } return 0; } The use of OpenMP is the parallel loop. Here, all iterations can be executed independently and in any order. The pragma CPP directive then conveys this fact to the compiler. A sequential code can be easily parallelized this way. #include #include #include "pthread.h" int sum=0; void adder() { int sum = 0; int t = sum; sleep(1); sum = t+1; return; } #define NTHREADS 50 int main() { int i; pthread_t threads[NTHREADS]; printf("forking\n"); #pragma omp for for (i=0; i if (pthread_create(threads+i,NULL,&adder,NULL)!=0) return i+1; } printf("joining\n"); for (i=0; i { if (pthread_join(threads[i],NULL)!=0) return NTHREADS+i+1; printf("Sum computed: %d\n",sum); } return 0; }
if (pthread_create(threads+i,NULL,&adder,NULL)!=0) return i+1;
printf("joining\n");
for (i=0; i { if (pthread_join(threads[i],NULL)!=0) return NTHREADS+i+1; printf("Sum computed: %d\n",sum); } return 0; } The use of OpenMP is the parallel loop. Here, all iterations can be executed independently and in any order. The pragma CPP directive then conveys this fact to the compiler. A sequential code can be easily parallelized this way. #include #include #include "pthread.h" int sum=0; void adder() { int sum = 0; int t = sum; sleep(1); sum = t+1; return; } #define NTHREADS 50 int main() { int i; pthread_t threads[NTHREADS]; printf("forking\n"); #pragma omp for for (i=0; i if (pthread_create(threads+i,NULL,&adder,NULL)!=0) return i+1; } printf("joining\n"); for (i=0; i { if (pthread_join(threads[i],NULL)!=0) return NTHREADS+i+1; printf("Sum computed: %d\n",sum); } return 0; }
{
if (pthread_join(threads[i],NULL)!=0) return NTHREADS+i+1;
printf("Sum computed: %d\n",sum);
return 0;
The use of OpenMP is the parallel loop. Here, all iterations can be executed independently and in any order. The pragma CPP directive then conveys this fact to the compiler. A sequential code can be easily parallelized this way.
#pragma omp for
for (i=0; i if (pthread_create(threads+i,NULL,&adder,NULL)!=0) return i+1; } printf("joining\n"); for (i=0; i { if (pthread_join(threads[i],NULL)!=0) return NTHREADS+i+1; printf("Sum computed: %d\n",sum); } return 0; }
for (i=0; i { if (pthread_join(threads[i],NULL)!=0) return NTHREADS+i+1; printf("Sum computed: %d\n",sum); } return 0; }
Question: a) Each process is represented in the operating system by a process control block (PCB). The PCB contains many pieces of information associated with a specific proce
Unix process API The two most important function calls to use when programming with several processes are fork and exec: fork() creates a copy of current process. It gives
what is cpu
Use and overview? Pure and impure interpreter?
Need capstone project
Explain the Architecting For Threads When available, threads are an integral part of any multitasking server application program. It is important that the operating system prov
Compare between the one and two-dimensional memory organizations in terms of the memory structure, advantages, and disadvantages. Which approach would better support the needs o
4. Describe priority scheduling algorithm. Consider the following set of processes. Show the order in which the algorithm will schedule these processes. Assume preemptive and non-p
Q. Regard as a logical address space of eight pages of 1024 words every mapped onto a physical memory of 32 frames. a. How several bits are there in the logical address? b. H
DIFFERENT MULTITHREADING MODELS Multithreading Models the majority multithreading models fall into one of the following categories of threading implementation: 1. M
Get guaranteed satisfaction & time on delivery in every assignment order you paid with us! We ensure premium quality solution document along with free turntin report!
whatsapp: +91-977-207-8620
Phone: +91-977-207-8620
Email: [email protected]
All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd