How to implement pseudo LRU?

We discussed true LRU implementations, but they are usually costly. In this post, we will explain how to implement pseudo LRU.

An example is shown below. The data structure is similar to a binary tree. For N ways in a cache set, we need to keep (N – 1) bits. If there are 8 sets in a way, then we will need 7 bits.

Upon a cache access, all tree nodes point to that cache way will be flipped. For example, if set 3 is accessed, then h0, h1 and h4 will be flipped in next cycle.

To find LRU, we can perform a depth-first-search starting from h0, and traverse nodes in lower levels. If the node is 0, then we traverse the left sub-tree; otherwise, we traverse the right sub-tree. In the diagram above, the LRU is set 3.

Once we understand the basic idea of pseudo LRU, it is easy to write code for pseudo LRU.

How to implement true LRU? (II)

We covered 2 true LRU implementations: square matrix implementation and counter based implementation in previous post. We will discuss 2 more true LRU implementations in this post.

In the following discussion, we assume the number of ways in a cache set is N.

Linked List Implementation

Linked list is probably the most straightforward LRU implementation. Nodes are linked from head to tail. Head points to the most recently used item, while tail points to the least recently used item.

Upon a cache access, the corresponding node “jumps” to the head, and the previous head becomes the next node of new head.

Continue reading → How to implement true LRU? (II)

How to implement true LRU? (I)

Least Recently Used, or LRU, is the optimal cache replacement policy, and it is used in various applications where arbitration is required. In this post, we will discuss different true LRU implementations, based on the paper “Highly Efficient LRU Implementations for High Associativity Cache Memory”.

In the following discussion, we assume the number of ways in a cache set is N.

Continue reading → How to implement true LRU? (I)