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RAM model

As explained in Grokking Data Structures

A random-access machine is an abstract computation model with a single processor, uniform random-access memory, and basic instructions that take constant time.

The RAM model is a simplified computer with one processor and uniform random-access memory. It lets you compare algorithms without depending on CPU speed, multitasking, parallelism, or hardware memory layers. section 4.6

The model assumes:

  • Any memory location can be accessed in one operation, regardless of its position. section 4.6
  • The processor provides a small set of arithmetic, data-movement, and flow-control instructions. section 4.6
  • Each basic instruction takes constant time, written as O(1). section 4.8

Why it matters

Under the RAM model, binary search is associated with logarithmic growth, linear search with linear growth, and handling every subset of an array with exponential growth. These classifications describe how running time or memory changes as input size increases. section 4.16

How Grokking Data Structures covers it

How deep it goes
Defines processor, memory, and constant-time instructions, while acknowledging that real memory is finite and hierarchical.
Examples
Uses binary search, linear search, priority queues, array pairs, and array subsets to illustrate growth classes.
What you can do after
Evaluate algorithm growth by counting constant-time instructions under a consistent computational model.
How it connects
Connects random-access computation with asymptotic analysis, Big-O notation, and constant-time operations.

Related concepts

This explainer was generated by Manning's knowledge graph from the text of Grokking Data Structures. The section links point to the parts of the book it draws on.