You are a visitor at a political convention with n delegates; each delegate is a member of exactly one political party. It is impossible to tell which political party any delegate belongs to; in particular, you will be summarily ejected from the convention if you ask anyone. However, you can determine whether any pair of delegates belong to the same party by introducing them to each other. Members of the same political party always greet each other with smiles and friendly handshakes, member of different parties always greet each other with angry stares and insults. Suppose more than half of the delegates belong to the same political party. Design a divide and conquer algorithm that identifies all member of this majority party and analyze the running time of your algorithm.
(Clarification: If we represent those delegates with array A[1..n), we cannot get result of A[i]< A[j]? or A[i] > A[j]? But we can get the result of A[i] == A[j]? in constant time.)

Mariah was working on a multimedia presentation that included both video and audio files. the file was huge, and she wanted to send it to her coworker in another office. she needed to reduce the size of the file so that it could be transmitted faster. the utility she used to do this was

Write pseudocode to represent the logic of a program that allows the user to enter a value. the program multiplies the value by 10 and outputs the result.

When making changes to optimize part of a processor, it is often the case that speeding up one type of instruction comes at the cost of slowing down something else. for example, if we put in a complicated fast floating-point unit, that takes space, and something might have to be moved farther away from the middle to accommodate it, adding an extra cycle in delay to reach that unit. the basic amdahl's law equation does not take into account this trade-off. a. if the new fast floating-point unit speeds up floating-point operations by, on average, 2ă—, and floating-point operations take 20% of the original program's execution time, what is the overall speedup (ignoring the penalty to any other instructions)? b. now assume that speeding up the floating-point unit slowed down data cache accesses, resulting in a 1.5ă— slowdown (or 2/3 speedup). data cache accesses consume 10% of the execution time. what is the overall speedup now? c. after implementing the new floating-point operations, what percentage of execution time is spent on floating-point operations? what percentage is spent on data cache accesses?