In this simulation task, you will use a simple program, which is known as
paging-linear-translate.py, to see if you understand how simple
virtual-to-physical address translation works with linear page tables. See the
README for details.
-v flag, you can see how many page-table entries are
filled.First, to understand how linear page table size changes as the address space grows:
paging-linear-translate.py -P 1k -a 1m -p 512m -v -n 0
paging-linear-translate.py -P 1k -a 2m -p 512m -v -n 0
paging-linear-translate.py -P 1k -a 4m -p 512m -v -n 0
Then, to understand how linear page table size changes as page size grows:
paging-linear-translate.py -P 1k -a 1m -p 512m -v -n 0
paging-linear-translate.py -P 2k -a 1m -p 512m -v -n 0
paging-linear-translate.py -P 4k -a 1m -p 512m -v -n 0
Before running any of these, try to think about the expected trends.
1.1. How can the page table size governed in equations? Give the equations to show, which parameters govern the page table size.
1.2. How should page-table size change as the address space grows? As the page size grows?
1.3. Why shouldn’t we just use really big pages in general?
-u
flag. For example: paging-linear-translate.py -P 1k -a 16k -p 32k -v -u 0
paging-linear-translate.py -P 1k -a 16k -p 32k -v -u 25
paging-linear-translate.py -P 1k -a 16k -p 32k -v -u 50
paging-linear-translate.py -P 1k -a 16k -p 32k -v -u 75
paging-linear-translate.py -P 1k -a 16k -p 32k -v -u 100
What happens as you increase the percentage of pages that are allocated in each address space?
paging-linear-translate.py -P 8 -a 32 -p 1024 -v -s 1
paging-linear-translate.py -P 8k -a 32k -p 1m -v -s 2
paging-linear-translate.py -P 1m -a 256m -p 512m -v -s 3
Which of these parameter combinations are unrealistic? Why?