Server farms such as Google and Yahoo! provide enough compute capacity for the highest request rate of the day. Imagine that mos
t of the time these servers operate at only 60% capacity. Assume further that the power does not scale linearly with the load; that is, when the servers are operating at 60% capacity, they consume 90% of maximum power. The servers could be turned off, but they would take too long to restart in response to more load. A new system has been proposed that allows for a quick restart but requires 20% of the maximum power while in this "barely alive" state. a. How much power savings would be achieved by turning off 60% of the servers? b. How much power savings would be achieved by placing 60% of the servers in the "barely alive" state? c. How much power savings would be achieved by reducing the voltage by 20% and frequency by 40%? d. How much power savings would be achieved by placing 30% of the servers in the "barely alive" state and 30% off?
1 answer:
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Answer:
#section 1
def maxTemp(filename):
import pathlib
f = pathlib.Path(filename)
f.exists()
if f.exists():
f = open(filename, "r")
#section 2
next(f)
res = [int(sub.split(',')[1]) for sub in f]
maxdata = (res[0])
for i in range(len(res)-1):
if maxdata < res[i]:
maxdata = res[i]
index = res.index(maxdata)
f.close()
#section 3
li = []
a = open(filename, "r")
for line in a:
line = line.strip()
li.append(line)
a.close()
return (li[index+1])
else:
return -1
print(maxTemp("new.csv"))
Explanation:
#section 1:
The function maxTemp is defined. We import pathlib in other to check if the file exists, if it does we carry on with opening the file and if it doesn't the program returns -1.
#section 2:
We start splitting the sub-lists from the second line i.e <em>next(f)</em>. For each line we take the second index element and convert it to an integer.
<em>res = [int(sub.split(',')[1]) for sub in f] </em>
The maximum number is gotten by using the if statement to compare all elements in the list. The index of the maximum item in the list is collected.
the file is then closed.
#section 3 :
The file is re-opened and all the lines are striped and passed into a new list and the index recovered from section 2, is used to get the day with the highest temperature and the line is returned.
