Open In App

Associative Memory

Associative memory is also known as content addressable memory (CAM) or associative storage or associative array. It is a special type of memory that is optimized for performing searches through data, as opposed to providing a simple direct access to the data based on the address.

it can store the set of patterns as memories when the associative memory is being presented with a key pattern, it responds by producing one of the stored pattern which closely resembles or relates to the key pattern.

it can be viewed as data correlation here. input data is correlated with that of stored data in the CAM.

it forms of two type:

  1. auto associative memory network : An auto-associative memory network, also known as a recurrent neural network, is a type of associative memory that is used to recall a pattern from partial or degraded inputs. In an auto-associative network, the output of the network is fed back into the input, allowing the network to learn and remember the patterns it has been trained on. This type of memory network is commonly used in applications such as speech and image recognition, where the input data may be incomplete or noisy.
  2. hetero associative memory network : A hetero-associative memory network is a type of associative memory that is used to associate one set of patterns with another. In a hetero-associative network, the input pattern is associated with a different output pattern, allowing the network to learn and remember the associations between the two sets of patterns. This type of memory network is commonly used in applications such as data compression and data retrieval.

Associative memory of conventional semiconductor memory (usually RAM) with added comparison circuity that enables a search operation to complete in a single clock cycle. It is a hardware search engine, a special type of computer memory used in certain very high searching applications. 

How Does Associative Memory Work?

In conventional memory, data is stored in specific locations, called addresses, and retrieved by referencing those addresses. In associative memory, data is stored together with additional tags or metadata that describe its content. When a search is performed, the associative memory compares the search query with the tags of all stored data, and retrieves the data that matches the query.

Associative memory is designed to quickly find matching data, even when the search query is incomplete or imprecise. This is achieved by using parallel processing techniques, where multiple search queries can be performed simultaneously. The search is also performed in a single step, as opposed to conventional memory where multiple steps are required to locate the data.

Applications of Associative memory :-

  1. It can be only used in memory allocation format.
  2. It is widely used in the database management systems, etc.
  3. Networking: Associative memory is used in network routing tables to quickly find the path to a destination network based on its address.
  4. Image processing: Associative memory is used in image processing applications to search for specific features or patterns within an image.
  5. Artificial intelligence: Associative memory is used in artificial intelligence applications such as expert systems and pattern recognition.
  6. Database management: Associative memory can be used in database management systems to quickly retrieve data based on its content.

Advantages of Associative memory :-

  1. It is used where search time needs to be less or short.
  2. It is suitable for parallel searches.
  3. It is often used to speedup databases.
  4. It is used in page tables used by the virtual memory and used in neural networks.

Disadvantages of Associative memory :-

  1. It is more expensive than RAM.
  2. Each cell must have storage capability and logical circuits for matching its content with external argument.
Article Tags :