Serial and binary search program in c using function


Thus, for an array of n elements, the worst-case time for serial search requires n array accesses. So, the parallel implementation is equivalent to the serial implementation and produces the required output. With this method of resolving collisions, we still must decide how to choose the locations to search for an open position when a collision occurs Work-sharing constructs can be used to divide a task among the threads so that each thread executes its allocated part of the code.

The hash function must be chosen so that its return value is always a valid index for the array. This is due to the fact that no thread can directly return after finding the element. Here is the source code:. For serial searchthe worst-case running time occurs when the desired item is not in the array. When the array is full, no more records can be added to the table.

This makes OpenMP a great option whilst converting a pre-written serial program into a parallel one. However, in the implementation, we are not looking for the maximum element, instead we are looking for the index of the maximum element. When the table has many records, there are many collisions and the average time for a search is longer. While searching, the program counts the total number of accesses to array elements for all the keys that are searched, and then outputs the average number of accesses to the array.

Compare the results to the results you obtained for linear probing. To preserve the order of the matched results, another attribute index has to be added to the results. In our example the student ID is the key, but other, more complex keys are sometimes used.

Thus, for an array of n elements, the worst-case time for serial search requires n array accesses. Suppose that we only know that there will be a hundred or fewer and that they will be distributed in the range So, our custom maximum index reduction will look something like this:. Selection Sort has the time complexity of O n 2making it unsuitable for large lists.

You can find the parallel implementation here. A function called the hash functionmaps keys to array indices. All the threads exist within a single process. This would require a careful choice of new size and probably require each entry to have a new hash value computed.

But first, we present a simple search method, the serial search and its run-time analysis. This process continues moving unsorted array boundary by one element to the right. Thus, for an array of n elements, the best-case time for serial search requires just 1 array access.

So basically when we use OpenMP, we use directives to tell the compiler details of how our code shuld be run in parallel. When the table has many records, there are many collisions and the average time for a search is longer. The nodes in a particular linked list will each have a key that hashes to the same value.