Loading the lesson
Loading the lesson
Search AllRounder.ai
Search the courses, subjects, tracks, games and features, or jump straight to a page.
Search the courses, subjects, tracks, games and features, or jump straight to a page.
Learn it your way
A short class with Sarah and her students. The other ways are under More.
Sign up free to listen. Transcripts are free to read.
Today, we’ll dive into page tables and their sizes—vital for managing virtual memory. Can anyone tell me why we need page tables?
To map virtual addresses to physical addresses!
Exactly! Page tables help track where virtual pages reside in physical memory. Now, what happens if our page tables become too large?
They consume a lot of memory, which can slow down system performance.
Correct! This is why we need to consider methods for reducing their sizes, like hierarchical page tables.
Hierarchical page tables break down page tables into levels. Who can explain how?
The outer table points to inner tables, and they allow us to manage larger address spaces without needing huge single tables.
Great point! This way, when we only need portions of the virtual address space, we can keep other parts off memory. What’s an example of a system that might benefit?
64-bit systems where the address space is enormous!
Exactly! Next, let’s discuss hashing techniques to optimize memory further.
Hashed page tables only store entries for valid virtual addresses. Can someone explain how this helps?
It reduces memory usage by not storing all possible entries.
Exactly! And if we hash to find an entry instead of searching through the whole table, what does this do?
It speeds up the lookup process!
Yes, very good! However, an inverted page table does something even different...
Now, what about inverted page tables? What’s their key feature?
They only use one page table for all physical memory, indexed by the physical frame number.
Spot on! This can save a lot of memory. Who remembers the trade-off with them?
It can take longer to search because we have to check a larger table.
Exactly! You all have a great grasp of these concepts. Let’s wrap up with a quick exercise.
Multi-level structure that helps manage larger address spaces effectively.
Tables that store entries for valid addresses only, using hashing for fast lookups.
A single table for all physical memory, indexed by physical frames to save space.
In layers we split, tables don't grow too lit!
Imagine a librarian organizing books by sections and sub-sections. Instead of one oversized catalog, smaller catalogs help find books faster.
HITS: Hashed, Inverted, Two-level, Segmented (Four methods to handle page tables).
HPT = Hierarchical Page Tables (efficiently group details) and HPT = Hashed Page Tables (fast lookups only for current needs).
Term
What is a hierarchical page table?
Click to flip
Term
What does a hashed page table do?
Click to flip
A data structure used in virtual memory systems to map virtual addresses to physical addresses.
A multi-level page table structure that divides the address space into lower levels to reduce the size of the individual tables.
A page table that uses a hash function to find an entry, storing only valid virtual addresses.
A page table where entries correspond to physical frames, reducing memory needed for storing multiple tables for each process.
The range of addresses that a process can use, typically larger than physical memory.
This section outlines methods for reducing page table sizes, including hierarchical and hashed page tables.
It discusses hierarchical page tables, hashing techniques, and inverted page tables as strategies to manage memory more effectively in systems with large address spaces. Each method has its benefits and trade-offs in terms of speed and efficiency.
In this section, we explore several methods for optimizing page table sizes to manage memory efficiently. The hierarchical page table technique introduces multi-level page tables which allow the virtual address space to be broken down into smaller segments, reducing the size of individual page tables. By separating logical addresses into multiple components—outer and inner page tables—system memory can better handle scattered memory allocation.
A special focus is placed on two-level and three-level page tables, particularly their suitability for 64-bit architectures. As more address space is needed, they can lead to larger page tables. Additionally, hashed page tables utilize hashing techniques to maintain a smaller footprint in memory by only storing entries for valid logical addresses that correspond to the physical memory.
Finally, inverted page tables present an alternative where a single table is indexed by physical memory pages rather than by logical addresses, reducing memory consumption while increasing lookup time. This concludes with a practical exercise calculating page sizes for a system with specific attributes.