How do programming and electricity work together?

Least square fit to polynomial write a function leastsquarefit3pol that solves a linear system of equations to find a least squares fit of a third order polynomial to an experimental data set given as two row arrays. the function leastsquarefit3pol must explicitly solve a set of linear equations and cannot use polyfit. there should be no restriction on the size of the problem that can be solved.

Problem 1 - hashing we would like to use initials to locate an individual. for instance, mel should locate the person mark e. lehr. note: this is all upper case. generate a hash function for the above using the numbers on your telephone. you know, each letter has a number associated with it, so examine your telephone keypad. generate 512 random 3 letter initials and take statistics on a linked list array size 512 to hold this information report how many have no elements, 1 element, 2 elements, does this agree with the hashing statistics distribution?

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?