How does the performance of quicksort change when a cut-off value is selected? Please elaborate.
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Q: What impact does the cut-off value have on quicksort's performance? Describe, please.
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- This is some code in C for quicksort. The quicksort works correctly, but I am trying to implement multithreading. I am trying to run the recursive calls in parallel with a limit on how much threads can be running at one time (set by the global variable 'maximumThreads'). My logic is incorrect with managing how many threads can be ran at the same time. The part that I need you to look at is after the for loop in quick sort, where I have my logic for the mutex and the conditional variable. Right now when I run my code, the program runs without stopping. I would like help with correctly implementing this. #include <stdlib.h>#include <string.h>#include <pthread.h>#include <stdio.h>#define SORT_THRESHOLD 40typedef struct _sortParams {char** array;int left;int right;int* currentThreads;pthread_mutex_t* mutex;pthread_cond_t* cond_var} SortParams;static int maximumThreads; /* maximum # of threads to be used *//* This is an implementation of insert sort, which although…Write a c++ code that implement a loop that accesses a number of different locations in an array over-and-over again, and see how the average access time changes as the array size increases, from a size small enough to fit in L1 cache to a size too large to fit in L2 (or L3) cache. Try to estimate the sizes of your caches.Which of the following statement or statements are true ? Please check all that apply. Both the linkedlist and array size needs to be pre-decided Arrays have better cache locality that can make them better in terms of performance. It's easier to insert and delete elements from array than from the linkedlist Data type of the linked list doesnot need to be same, whereas in array, it must be the same memory can be allocated at runtime both for linkedlist and dynamic array Which of the following statements are true? Check all that applies 5 points Accessing any element of an array has the time complexity of O(n) Searching for an element in array and linkedlist has the same time complexity Inserting or Deleting an element from a stack or queue has the same time complexity Accessing an element from a singly…
- What happens if a process calls wait before it has called fork, i.e., it has no children? Bespecific (indicate which error is returned).Match the advantages of the Java Collection Framework to its respective description. accepts two parameters, a destination List and a swaps the Reverses the elements in a elements in a List at the specified locations. source List, and overwrites the contents of the destination List's order. with the elements of the source. O O O O O O O O O O reverse fill copy swap addAll overwrites the provided value on every entry in a List. This method can be used to re-initialize a List. O O O * 5 points add all the specified elements to a Collection. O O OIn the third step, you will review the Quicksort and the Insertion Sort code. You will recall from the class presentation that it was suggested that Quicksort is not very efficient when the partition sizes become very small. It was also suggested in class that most implementations of Quicksort switch to another method when the partition size gets small. Create a new version of the Quicksort code to switch to Insertion sort on partitions less than 32 data items in size. 1. Confirm, using a small data set, that your version works. 2. Run a comparison between the original Quicksort and your new version in a way like the way you did comparisons in Step 2. Use the RANDOM.TXT file for the data to test both versions - with at least 50000 items of data in your input file.
- Implement a merge() variant that replicates the second half of a[] to aux[] in decreasing order before merging back to a[]. This update allows you to delete the code from the inner loop that tests that each of the halves has been exhausted. Please keep in mind that the resulting sort is not stable.What impact does the cut-off value have on quicksort's performance? Describe, please.Explore the performance considerations when using the Comparable interface for sorting large collections of objects. Are there any optimizations or best practices to follow in such cases?
- This is some code in C for quicksort. The quicksort works correctly, but I am trying to implement multithreading. I am trying to run the recursive calls in parallel with a limit on how much threads can be running at one time (set by the global variable 'maximumThreads'). My logic is incorrect with managing how many threads can be ran at the same time. The part that I need you to look at is after the for loop in quick sort, where I have my logic for the mutex and the conditional variable. Right now when I run my code, the program runs indefinitely. I would like help with correctly implementing this part. #include <stdlib.h>#include <string.h>#include <pthread.h>#include <stdio.h>#define SORT_THRESHOLD 40typedef struct _sortParams {char** array;int left;int right;int* currentThreads;pthread_mutex_t* mutex;pthread_cond_t* cond_var} SortParams;static int maximumThreads; /* maximum # of threads to be used *//* This is an implementation of insert sort, which…This question was rejected because lack of a text file, which I do not see a way to upload. I saved the first part of the file as an image because that is all I can upload. If that doesn't suffice, please advise how to include a text file. In C++, I would like some help improving or making a better password lookup function for a Hash Table class/program I made, The function: it is supposed to lookup a user password using their ID and name which I read in from a text file. The one I have only works for the first 10 records, which I highlighted below in the program. string lookupPassword (string inUserID, string inUserName){ string thePassword; ... return thePassword; } Here is part of the program thus far: // Hash.cpp #include <iostream>#include<string>#include<iomanip>#include<fstream>using namespace std;//node classclass nodeBST {private: //user data string userID; string userName; string userPW; //BST left and right children nodeBST*…Implement a blog server in C 1. Implement get of all posts (GET /posts), and individual post (GET /post/1) 2. Implement creation of post (POST /posts). Allow the user to enter their name, but check that they are a valid user in db. Do error checking! The user should not specify the post id; that should come from the database. 3. Write three html files to test this; serve them with the blog server: index.html shows the list of posts with a link to each. post.html shows a post. publish.html allows the creation of a new post. Link these together as a user would expect!
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