Professor F. Lake tells his class that it is asymptotically faster to square an -bit integer than to multiply two n-bit integers. Should they believe him?

Short Answer

Expert verified

No, the statement of Professor F. Lake is wrong.

Step by step solution

01

Introduction

Evaluate the following details:

• The algorithm's execution time is determined using asymptotic notations.

• According to the Professor, the n-bit integer algorithm squaring is faster than multiplying two n-bit integers.

• The algorithm's asymptotic value is determined by the number of items and actions in the algorithm.

02

Correct Fact

“No”, students should not believe the professor.

Description:

• When an n-bit integer is squared, numerous cross-terms become equal.

• As a result, there's no need to do it again.

• Take the 3-bit integer "1012" as an example.

• This number is written as a2, a1 , and a0 from left to right.

• If you square this number, you'll obtain 9 terms.

• In the matrix below, the terms are listed.

a2a2a2a1a2a0a1a2a1a1a1a0a0a2a0a1a0a0

• This is a symmetric matrix. Because the primary diagonal's components are all the same.

• In other words, certain elements do not require calculation.

• As a result, this approach for squaring n-bit values is not asymptotically superior.

• This algorithm will benefit from a steady pace.,

As a result, Professor is incorrect in his assertion that the fast-squaring method may be improved at a constant pace.

Unlock Step-by-Step Solutions & Ace Your Exams!

  • Full Textbook Solutions

    Get detailed explanations and key concepts

  • Unlimited Al creation

    Al flashcards, explanations, exams and more...

  • Ads-free access

    To over 500 millions flashcards

  • Money-back guarantee

    We refund you if you fail your exam.

Over 30 million students worldwide already upgrade their learning with Vaia!

One App. One Place for Learning.

All the tools & learning materials you need for study success - in one app.

Get started for free

Most popular questions from this chapter

Practice with the fast Fourier transform.

(a) What is the FFT of (1,0,0,0)? What is the appropriate value of ωin this case? And of which sequence is (1,0,0,0)the FFT?

(b)Repeat for (1,0,1,-1).

In this problem we will develop a divide-and-conquer algorithm for the following geometric task.

CLOSEST PAIRInput: A set of points in the plane, {p1=(x1;y1),p2=(x2,y2),...,pn=(xn,yn)}

Output: The closest pair of points: that is, the pair PiPjfor which the distance between piand pj, that is,

(xi-xi)2+z(yi-yi)2,

is minimized.

For simplicity, assume that n is a power of two, and that all the x-coordinates role="math" localid="1659237354869" xi are distinct, as are the y-coordinates.

Here’s a high-level overview of the algorithm:

.Find a value for which exactly half the points have xi<x, and half have xi>x. On this basis, split the points into two groups, L and R.

• Recursively find the closest pair in L and in R. Say these pairs are pL·qLLand pR·qRRwith distances dLand dR respectively. Let d be the smaller of these two distances.

• It remains to be seen whether there is a point in Land a point in R that are less than distance dapart from each other. To this end, discard all points with xi<x-dor xi>x+d and sort the remaining points by y-coordinate.

• Now, go through this sorted list, and for each point, compute its distance to the seven subsequent points in the list. Let pM·qMbe the closest pair found in this way.

• The answer is one of the three pairs role="math" localid="1659237951608" {pL,qL},{pR,qR}{pM,qM}, whichever is closest.

(a) In order to prove the correctness of this algorithm, start by showing the following property: any square of size d×d in the plane contains at most four points of L.

(b) Now show that the algorithm is correct. The only case which needs careful consideration is when the closest pair is split between L and R.

(c) Write down the pseudocode for the algorithm, and show that its running time is given by the recurrence:

T(n)=2T(nl2)+0(nlogn)

Show that the solution to this recurrence is o(nlogzn).

(d) Can you bring the running time down to O(nlogn)?

Suppose you are choosing between the following three algorithms: • Algorithm A solves problems by dividing them into five sub-problems of half the size, recursively solving each sub-problem, and then combining the solutions in linear time. •

Algorithm B solves problems of size n by recursively solving two sub-problems of size n-1and then combining the solutions in constant time. • Algorithm C solves problems of size n by dividing them into nine sub-problems of size n/3, recursively solving each sub-problem, and then combining the solutions in O(n2)time.

What are the running times of each of these algorithms (in big- O notation), and which would you choose?

In justifying our matrix multiplication algorithm (Section 2.5), we claimed the following block wise property: if X and Y are n×nn matrices, and

X=[ABCD],Y=[EFGH],

where A,B,C,D,E,F,G, and H are n/2×n/2 sub-matrices, then the product XY can be expressed in terms of these blocks:

XY=[ABCD][EFGH]=[AE+BGAF+BHCE+DGCF+DH]

Prove this property.

Practice with polynomial multiplication by FFT.

(a) Suppose that you want to multiply the two polynomials x + 1 and x2+1using the FFT. Choose an appropriate power of two, find the FFT of the two sequences, multiply the results component wise, and compute the inverse FFT to get the final result.

(b) Repeat for the pair of polynomials 1+x+2x2and 2 + 3x.

See all solutions

Recommended explanations on Computer Science Textbooks

View all explanations

What do you think about this solution?

We value your feedback to improve our textbook solutions.

Study anywhere. Anytime. Across all devices.

Sign-up for free