Optimizing Array Summing with Multithreading

Table of Contents:

1. Introduction
2. Passing Arguments to Threads
   1. Number of Threads
   2. Initializing Mutex and Variables
3. Splitting the Array
   1. First Half
   2. Second Half
4. Summing the Half Sums
   1. Creating the Sum Variable
   2. For Loop
   3. Adding the Index
5. Returning the Sum
   1. Handling Dynamically Allocated Memory
   2. Returning the Sum
   3. De-allocating Memory
6. Computing the Final Result
   1. Initializing Global Sum
   2. Adding the Half Sums
   3. Freeing Memory
7. Conclusion

Passing Arguments to Threads and Summing Array Elements 💻

Passing arguments to threads is a crucial aspect of multithreaded programming. In this article, we will discuss a simple and practical example that demonstrates how to pass arguments to threads and sum up the elements of an array. Instead of working with ten threads, we will limit ourselves to just two threads for the sake of simplicity.

1. Introduction

Our goal is to create a program that sums up all the numbers in a given array, specifically the primes array. We will divide the array into halves, with each half being processed by a separate thread. The partial sums obtained from each thread will be combined in the main thread to obtain the final result.

2. Passing Arguments to Threads

2.1 Number of Threads

To begin with, we need to adjust the number of threads in our program. Since we are working with only two threads in this case, we modify the code accordingly.

2.2 Initializing Mutex and Variables

We also need to initialize the mutex and other variables that will be used in the program. By doing so, we ensure thread safety and avoid conflicts during execution.

3. Splitting the Array

Now that we have the necessary preparations in place, we can move on to splitting the array into halves.

3.1 First Half

The first half of the array will be processed by the first thread. We pass the index of the first element to this thread for computation.

3.2 Second Half

The second half of the array will be processed by the second thread. We pass the index of the sixth element to this thread to sum the subsequent numbers.

4. Summing the Half Sums

In this section, we focus on summing the half sums obtained from each thread.

4.1 Creating the Sum Variable

First, we initialize a variable called sum with a value of zero.

4.2 For Loop

Next, we iterate through the array elements and add them to the sum variable. We use a for loop to iterate from the start index to a predetermined number of elements.

4.3 Adding the Index

To ensure that the correct elements are added to the sum, we add the index to the mix. This allows us to sum the appropriate numbers in each iteration.

5. Returning the Sum

After obtaining the sum from each thread, we need to return it to the main thread for further processing.

5.1 Handling Dynamically Allocated Memory

Since our program involves dynamically allocated memory, we have two options for returning the sum. We can either allocate additional memory and return it, or we can return the memory already allocated.

5.2 Returning the Sum

In this case, we choose the latter approach. We return the dynamically allocated memory, which contains the sum, back to the main thread.

5.3 De-allocating Memory

To ensure proper memory management, we need to free the memory that was allocated during the execution of the thread. Failure to do so can lead to memory leaks, causing performance issues.

6. Computing the Final Result

With the sums obtained from each thread, we can now compute the final result.

6.1 Initializing Global Sum

We initialize a variable called "global sum" with a value of zero. This variable will store the cumulative sum of the half sums obtained from each thread.

6.2 Adding the Half Sums

We add the references of the half sums to the "global sum" variable. This accumulates the partial sums and gives us the final result.

6.3 Freeing Memory

Lastly, we free the memory that was allocated during the execution of the threads. This ensures proper memory management and avoids memory leaks.

7. Conclusion

In conclusion, we have successfully demonstrated how to pass arguments to threads and efficiently sum the elements of an array using a multi-threaded approach. By dividing the array into halves and processing them concurrently, we can optimize the computation and obtain the desired result. Remember to handle dynamically allocated memory properly and ensure thread safety for robust and efficient programming.

Highlights:

• Practical example of passing arguments to threads
• Summing up elements of a given array
• Optimizing computation using multi-threading
• Dividing array into halves for concurrent processing
• Proper memory management and thread safety for efficient programming

FAQ:

Q1. Can I adjust the number of threads in this program? Yes, you can modify the number of threads according to your requirements. However, keep in mind that an excessive number of threads may lead to performance issues.

Q2. Is it necessary to free the memory allocated during thread execution? Yes, it is crucial to free the dynamically allocated memory to prevent memory leaks. Improper memory management can result in performance degradation.

Q3. What is the advantage of using multi-threading in this example? By using multi-threading, we can divide the task of summing up the array elements into parallel processes. This significantly improves the performance and execution time of the program.

Q4. Can I modify the code to sum up elements in a different array? Certainly! You can modify the code to work with any array of your choice. Simply replace the name of the array variable with your desired array.

Q5. Where can I find the code for this example? The code for this example can be found on our website. Please refer to the link provided in the description or visit our website directly.

Resources:

• Link to Example Code
• Link to Website