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Today, we're going to discuss hierarchical page tables. Can someone tell me what a page table does in general?
A page table keeps track of where various pages are located in memory.
Exactly! Hierarchical page tables break this down into multiple layers. Why do you think this is beneficial?
It reduces the size of the page table because we don't need one giant table.
That's right! This method helps manage scattered address spaces effectively. Remember the acronym 'HPT' for Hierarchical Page Tables. Let's move on.
Next, let’s talk about hashed page tables. What do we mean by hashing in this context?
Hashing is converting data into a unique fixed-size value or index.
Correct! In a hashed page table, the virtual page number is hashed to produce an entry. What’s the advantage of this method?
It speeds up the retrieval process because it reduces the number of search options.
Exactly! Remember, however, that we need to be wary of hash collisions. So, let’s remember 'HPT' when we discuss hashed page tables.
Finally, let’s cover inverted page tables. What distinguishes these from the previous methods we discussed?
Inverted page tables keep track of physical memory pages instead of virtual pages.
That's spot on! This shift allows us to maintain a single table for the entire physical memory. But does anyone see a potential downside?
Searching can be slower because we have to check each entry for a match, right?
Yes, that’s a great observation! Each method has trade-offs, as we’ve discussed today. 'I can remember HPT for Hierarchical, Hash, and Inverted!' Excellent summary.
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The section analyzes various page table structures, emphasizing how hierarchical, hashed, and inverted page tables address the challenges of memory management by balancing size and access speed. Key trade-offs include the complexity in retrieval times and memory overhead.
This section delves into the various paging techniques used in memory management systems, particularly focusing on hierarchical page tables, hashed page tables, and inverted page tables. Each of these techniques offers unique advantages and disadvantages that are crucial for understanding performance trade-offs in operating systems.
Hierarchical page tables help reduce the memory overhead of large page tables by dividing them into multiple levels, which allows for better management of scattered address spaces. However, while the hierarchical structure leads to a smaller page table size, it can also increase the time needed to access pages, as multiple levels may require several memory accesses.
Hashed page tables are particularly useful in large address spaces greater than 32 bits. By utilizing a hash function to store virtual page numbers, they improve access times at the cost of increased complexity and the potential for hash collisions, which can lead to additional lookup times.
Inverted page tables adopt a different approach by maintaining a single table indexed by physical page frames, which dramatically reduces the overall memory required for storing page tables. However, the major downside is the increased time complexity involved in searching this table when a page reference occurs.
In summary, each paging technique has its strengths and weaknesses, and the choice of which to implement depends on the specific requirements regarding memory usage and access speed.
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So, we come to hierarchical page tables. Here, we do not go into segmentation, but we have multiple page table levels; hierarchical page tables or multiple multi-level page tables. We break the logical address space into multiple page tables. The simplest scheme in this is a two-level page table.
Hierarchical page tables are an advanced way to manage memory addresses. Unlike traditional single-level page tables, hierarchical tables use multiple levels to break down the logical address space into smaller, manageable sections. This structure allows computers to use memory more efficiently by not having all the page tables in the main memory at once. In a two-level page table, the logical address is divided into parts: one part for the first-level page table, and another for the second-level page table.
Think of a library organized by a catalog system. Instead of having one huge list of all books (like a single page table), the library organizes books into categories, and each category has its own shelf with a list of specific books (like hierarchical page tables). This makes it easier for people to find what they're looking for quickly.
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So, we use paging with segmentation. Within a given segment, I go and I access a page table that may not be there in main memory at a given time. Then, I bring that page table corresponding to that segment from secondary storage to main memory and then I access the main memory page frame.
Paging with segmentation combines the benefits of two concepts: segmentation and paging. In this method, each process is divided into segments (like functions or modules) that can be individually managed. When a segment isn't currently loaded into main memory, the system fetches it from secondary storage, allowing efficient use of memory while still enabling fast access to necessary data.
Imagine a chef working with different recipes. Instead of having every ingredient in the kitchen at all times (which takes up space), the chef keeps commonly used ingredients on hand but can get other ingredients from a pantry (secondary storage) when needed. This method optimizes kitchen space and allows the chef (the system) to work efficiently.
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Now, two-level paging is not always sufficient. For 64-bit computers with a page size of 4 KB, the page table will have 252 entries. Therefore, the outer page table will have 242 entries which is very huge.
While two-level paging helps manage memory better than one-level paging, it can still be inadequate, especially in larger systems, such as 64-bit computers. When calculating the page table size for these systems, the number of entries can grow to enormous sizes, making it difficult to store and manage them efficiently. The large space needed for the outer page table can hinder performance.
Consider a massive filing cabinet. The first drawer represents the outer page table containing categories, while each subsequent drawer contains files for specific topics. If you have too many categories, the first drawer (outer table) becomes overloaded and hard to search, just like a huge outer page table that consumes too much memory.
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Another technique used to control the size of a page table is by using a hashed page table. This is more prevalent for 64-bit computers. The virtual page number is hashed into the page table.
A hashed page table simplifies the storage and retrieval of page entries by using a hashing function. This function takes the virtual page number and converts it into a specific index in the page table. If multiple page numbers hash to the same index, they are stored in a linked list format at that index. This method reduces memory usage and speeds up the lookup process, especially for larger address spaces.
Think of a phone directory. Instead of writing everyone's contact details one by one, you instead assign each person a number based on their name. When you want to find someone, you use a simple math formula (hashing) to get their position in the directory. Even if multiple people have similar names, they've got slightly different numbers (like linked lists), making searching faster.
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The main concept in inverted page tables is to only track all physical pages rather than having a page table for each process. We only keep a page table indexed by page frame number, which contains the virtual address along with the process ID.
Inverted page tables offer a different approach by maintaining a single table that contains entries for all physical memory pages, rather than separate tables for each process. This reduces the amount of memory used by the page tables since only one table is needed for the entire system. Each entry corresponds to a physical memory frame and includes the virtual address and process ID associated with it.
It's similar to a universal restaurant menu that lists every dish on one page, rather than having separate menus for each table. This way, staff can quickly pick and serve dishes based on customer's orders (virtual pages), without the clutter of multiple menus (multiple page tables).
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Key Concepts
Hierarchical Page Tables: A method to optimize memory usage by dividing page tables into multiple levels.
Hashed Page Tables: An efficient indexing method that uses a hash function for quick retrieval of page entries.
Inverted Page Tables: A memory management structure that records physical pages instead of virtual pages, reducing memory overhead.
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Hierarchical page tables allow systems with limited physical memory to manage larger virtual address spaces effectively.
A hashed page table reduces lookup times but requires consideration of hash collisions, which can increase search times.
Inverted page tables minimize memory usage by only tracking physical pages but may slow down access due to complex searches.
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If the page is high and memory's tight, use HPT, it will be alright.
Imagine a library where books are stored not in one big shelf but across several smaller shelves. That way, when you need a book, you go to the right shelf and find it easily—this is just like hierarchical page tables.
HPT - Hierarchical is for a Smaller Table; HPT is for Hashed, making all Stable.
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Review the Definitions for terms.
Term: Hierarchical Page Tables
Definition:
A structure that divides page tables into multiple levels to manage memory more efficiently.
Term: Hashed Page Tables
Definition:
A page table approach that uses a hash function to index virtual pages.
Term: Inverted Page Tables
Definition:
A page table that maintains a record of physical memory pages indexed by their frame numbers.