Write a program that has a function prototype before main and an implementation of the function after main. The function to be implemented is a coin toss simulation using the random number generator. The function should return 1 or true 50% of the time and 0 or false 50% of the time. Use srand and the system time to make the program run differently each time. (srand(time(NULL));). Keep track of the number of head and tails for 10, 100, 1000, 10,000, 100,000 and 1,000,000 trials. Output the number of heads and tails and number of each as a percentage of the total. Notice that the more trials the more accurate your simulation becomes.

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?