12/11/20

## Page Tables Optimisations

##### Memory Organisation

* The **root page table** is always maintained in memory.
* Page tables themselves are maintained in **virtual memory** due to their size.
* Assume a **fetch** from main memory takes $T$ time - single page table access is now $2\cdot T$  and **two** page table levels access is $3 \cdot T$.
  * Some optimisation needs to be done, otherwise memory access will create a bottleneck to the speed of the computer.

### Translation Look Aside Buffers

* Translation look aside buffers or TLBs are (usually) located inside the memory management unit
  * They **cache** the most frequently used page table entries.
    * As they're stored in cache its super quick.
  * They can be searched in **parallel**.
* The principle behind TLBs is similar to other types of **caching in operating systems**. They normally store anywhere from 16 to 512 pages.
* Remember: **locality** states that processes make a large number of references to a small number of pages.

![TLB diagram](/lectures/osc/assets/W.png)

The split arrows going into the TLB represent searching in parallel. 

* If the TLB gets a hit, it just returns the frame number
* However if the TLB misses:
  * We have to account for the time it took to search the TLB
  * We then have to look in the page table to find the frame number
* Worst case scenario is a page fault (takes the longest). This is where we have to retrieve a page table from secondary memory, so that it can then be searched.

> Quick maths:
>
> * Assume a single-level page table
>
> * Assume 20ns associative **TLB lookup time**
>
> * Assume a 100ns **memory access time**
>
>   * **TLB hit** => 20 + 100 = 120ns
>   * **TLB miss** => 20 + 100 + 100 = 220ns
>
> * Performance evaluation of TLBs
>
>   * For an 80% hit rate, the estimated access time is: 
>     $$
>     120\cdot 0.8 + 220\cdot (1-0.8)=140ns
>     $$
>     (**40% slowdown** relative to absolute addressing)
>     
>   * For a 98% hit rate, the estimated access time is: 
>     $$
>     120\cdot 0.98 + 220\cdot (1-0.98)=122ns
>     $$
>    (**22% slowdown**) 
>
> NOTE: **page tables** can be **held in virtual memory** => **further slow down** due to **page faults**.

### Inverted Page Tables

A **normal page table size** is proportional to the number of pages in the virtual address space => this can be prohibitive for modern machines

>An **inverted page table's size** is **proportional** to the size of **main memory**
>
>* The inverted table contains one **entry for every frame** (not for every page) and it **indexes entries by frame number** not by page number.
>* When a process references a page, the OS must search the entire inverted page table for the corresponding entry (which could be too slow)
>  * It does save memory as there are fewer frames than pages.
>* To find if your pages is in main memory, you need to iterate through the entire list.
>* *Solution*: Use a **hash function** that transforms page numbers (*n* bits) into frame numbers (*m* bits) - Remember *n* > *m*
>  * The has functions turns a page number into a potential frame number.

![inverted page table](/lectures/osc/assets/x.webp)

So when looking for the page's frame location. We have to sequentially search through the table until we hit a match, we then get the frame number from the index - in this case 4.

#### Inverted Page Table Entry

> * The **frame number** will be the index of the inverted page table.
> * Process Identifier (**PID**) - The process that owns this page.
> * Virtual Page Number (**VPN**)
> * **Protection** bits (Read/Write/Execute)
> * **Chaining Pointer** - This field points towards the next frame that has exactly the same VPN. We need this to solve collisions

![Inverted Page table entry](/lectures/osc/assets/Y.png)

![inverted page table address translation](/lectures/osc/assets/Z.png)

Due to the hash function, we now only have to look through all entries with **VPN**: 1 instead of all the entries.

#### Advantages

* The OS maintains a **single inverted page table** for all processes
* It **saves lots of space** (especially when the virtual address space is much larger than the physical memory)

#### Disadvantages

* Virtual to physical **translation becomes much slower**
* Hash tables eliminates the need of searching the whole inverted table, but we have to handle collisions (which also **slows down translation**)
* TLBs are necessary to improve their performance.

### Page Loading

* Two key decisions have to be made when using virtual memory
  * What pages are **loaded** and when
    * Predictions can be made for optimisation to reduce page faults
  * What pages are **removed** from memory and when
    * **page replacement algorithms**

#### Demand Paging

> Demand paging starts the process with **no pages in memory**
>
> * The first instruction will immediately cause a **page fault**.
> * **More page faults** will follow but they will **stabilise over time** until moving to the next **locality**
> * The set of pages that is currently being used is called it's **working set** (same as the resident set)
> * Pages are only **loaded when needed** (i.e after **page faults**)

#### Pre-Paging

> When the process is started, all pages expected to be used (the working set) are **brought into memory at once**
>
> * This **reduces the page fault rate**
> * Retrieving multiple (**contiguously stored**) pages **reduces transfer times** (seek time, rotational latency, etc)
>
> **Pre-paging** loads as many pages as possible **before page faults are generated** (a similar method is used when processes are **swapped in and out**) 

*ma*: memory access time				*p*: page fault rate				*pft*: page fault time

**Effective access time** is given by: $T_{a} = (1-p)\cdot ma+pft\cdot p$

NOTE: This doesn't take into account TLBs.

The expected access time is **proportional to page fault rate** when keeping page faults into account.
$$
T_{a} \space\space\alpha \space\space p
$$

* Ideally, all pages would have to be loaded without demanding paging.

### Page Replacement

> * The OS must choose a **page to remove** when a new one is loaded
> * This choice is made by **page replacement algorithms** and **takes into account**:
>   * When the page was **last used** or **expected to be used again**
>   * Whether the page has been **modified** (this would cause a write).
> * Replacement choices have to be made **intelligently** to **save time**.

#### Optimal Page Replacement

> * In an **ideal** world
>   * Each page is labelled with the **number of instructions** that will be executed/length of time before it is used again.
>   * The page which is **going to be not referenced** for the **longest time** is the optimal one to remove.
> * The **optimal approach** is **not possible to implement** 
>   * It can be used for post execution analysis
>   * It provides a **lower bound** on the number of page faults (used for comparison with other algorithms) 

#### FIFO

> * FIFO maintains a **linked list** of new pages, and **new pages** are added at the end of the list
> * The **oldest page at the head** of the list is **evicted when a page fault occurs**
>
> This is a pretty bad algorithm <s>unsurprisingly</s>

![FIFO page replacement](/lectures/osc/assets/a1.png)

Explanation at 53:40

Shaded squares on the top row are page faults. Shaded squares in the grid are when a new page is brought into memory.

