# merge-sort multithread

suggest change*A* is an array and *p* and *q* indexes of the array such as you gonna sort the sub-array *A[p..r]*. *B* is a sub-array which will be populated by the sort.

A call to *p-merge-sort(A,p,r,B,s)* sorts elements from *A[p..r]* and put them in *B[s..s+r-p]*.

p-merge-sort(A,p,r,B,s) n = r-p+1 if n==1 B[s] = A[p] else T = new Array(n) //create a new array T of size n q = floor((p+r)/2)) q_prime = q-p+1 spawn p-merge-sort(A,p,q,T,1) p-merge-sort(A,q+1,r,T,q_prime+1) sync p-merge(T,1,q_prime,q_prime+1,n,B,s)

Here is the auxiliary function that performs the merge in parallel. *p-merge* assumes that the two sub-arrays to merge are in the same array but doesn’t assume they are adjacent in the array. That’s why we need *p1,r1,p2,r2*.

p-merge(T,p1,r1,p2,r2,A,p3) n1 = r1-p1+1 n2 = r2-p2+1 if n1<n2 //check if n1>=n2 permute p1 and p2 permute r1 and r2 permute n1 and n2 if n1==0 //both empty? return else q1 = floor((p1+r1)/2) q2 = dichotomic-search(T[q1],T,p2,r2) q3 = p3 + (q1-p1) + (q2-p2) A[q3] = T[q1] spawn p-merge(T,p1,q1-1,p2,q2-1,A,p3) p-merge(T,q1+1,r1,q2,r2,A,q3+1) sync

And here is the auxiliary function dichotomic-search.

*x* is the key to look for in the sub-array T[p..r].

dichotomic-search(x,T,p,r) inf = p sup = max(p,r+1) while inf<sup half = floor((inf+sup)/2) if x<=T[half] sup = half else inf = half+1 return sup

Found a mistake? Have a question or improvement idea?
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