Artificially creating memory usage in Python

You have a couple of misconceptions that I'll try to address.

• You have to use CPU to use memory. There's no other way.
• Your copy of a list is only assigning a pointer. You're not moving memory.

If you want to increase memory utilization, you need to keep adding data to your list:

l = []
for i in range(0, 1024*1024):
    l.append("*" * 1024)

Or using something similar to your method,

l = [17] * 1024

for i in range(0, 16):
   l = l + l  # doubles the list each time.

That will allocate the memory. If you want to measure access to it in isolation, you'll want to loop over l modifying the values or summing them.

sum(l)

or

for i in range(0, len(l)):
    l[i] += 1

In the end, your benchmark is going to be very simplistic (like doesn't address multiple cores accessing memory simultaneously, doesn't take into account processor caches, lookahead, random vs serial access, etc.) Using Python is also not optimal because you are not in full control of the memory allocation and garbage collection.

Proper memory benchmarking is a deep subject...

Edit:

This is what you are asking for, more or less:

from datetime import datetime
from datetime import timedelta

memory1 = "*" * 1024**3

start = datetime.now()

j = 0

while (datetime.now() - start) < timedelta(minutes=1):
    j += 1

memory2 = "*" * 1024**3

while (datetime.now() - start) < timedelta(minutes=2):
    j += 1

You can adjust memory1 and memory2 to get your 40% and 90% depending on your actual system size. The program will need to use the CPU while it allocates the string. It first has to request the memory from the kernel, but then has to fill it in with '*', otherwise the memory will only be virtual. If you were writing this in C, you could just touch one byte in each 4k page.