Considering there are 2 dictionaries, one with the name of the person and the stock name and number of stocks they have and the other dictionary has the stock name and it’s today’s market value - Ex: a = { “Joe” :{“AAPL”:5, “AMZN”:2}, ”Bill” :{“AAPL”:2, “AMZN” :5 }}

B = {“AAPL” : 227, “AMZN” :1721 , “NFLX” : 267 , “TSLA” : 244, “FB” : 179 }

Write a Python program to find the amount of money each person makes by selling all of their stock today, and who will get the most value

Consider the simple 3-station assembly line illustrated below, where the 2 machines at station 1 are parallel, i. e., the product only needs to go through one of the 2 machines before proceeding to station 2.what is the throughput time of this process?

Stops: using the information learned in this course, explain three things you will not do when driving. a. b. c. explain why you will not do these things when driving. starts: using the information learned in this course, explain three things you will do when driving. a. b. c. explain why you will do these particular things when driving. explain one thing you will stop doing as a passenger. explain one thing you will start doing as a passenger.

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?