Improvement of the in-Memory Automata Processor Accelerators using Emerging Memories, M.Sc. Thesis Sharif University of Technology ; Hessabi, Shahin (Supervisor)
Abstract
Non-deterministic finite automata (NFA) are an elementary type of Turing machines with very high processing power. NFA processors provide parallelism at the data and task level because they can be in several different output states in one clock cycle. Implementing such machines with memory is a good strategy because if we consider each of the memory columns as a state, by selecting a row of the memory, we can activate several states at the same time, which is an implementation of NFA. NFA-based automata processors were first introduced by Micron and were very powerful for issues such as pattern matching, DNA sequencing, or regular expressions and, in general, for machine learning topics....
Cataloging briefImprovement of the in-Memory Automata Processor Accelerators using Emerging Memories, M.Sc. Thesis Sharif University of Technology ; Hessabi, Shahin (Supervisor)
Abstract
Non-deterministic finite automata (NFA) are an elementary type of Turing machines with very high processing power. NFA processors provide parallelism at the data and task level because they can be in several different output states in one clock cycle. Implementing such machines with memory is a good strategy because if we consider each of the memory columns as a state, by selecting a row of the memory, we can activate several states at the same time, which is an implementation of NFA. NFA-based automata processors were first introduced by Micron and were very powerful for issues such as pattern matching, DNA sequencing, or regular expressions and, in general, for machine learning topics....
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