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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2402.12130 |
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| _version_ | 1866911779997614080 |
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| author | Dudek, Piotr |
| author_facet | Dudek, Piotr |
| contents | This paper proposes the design and implementation strategy of a novel computing architecture, the Factor Machine. The work is a step towards a general-purpose parallel system operating in a non-sequential manner, exploiting processing/memory co-integration and replacing the traditional Turing/von Neumann model of a computer system with a framework based on "factorised computation". This architecture is inspired by neural information processing principles and aims to progress the development of brain-like machine intelligence systems, through providing a computing substrate designed from the ground up to enable efficient implementations of algorithms based on relational networks. The paper provides a rationale for such machine, in the context of the history of computing, and more recent developments in neuromorphic hardware, reviews its general features, and proposes a mixed-signal hardware implementation, based on using analogue circuits to carry out computation and localised and sparse communication between the compute units. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_12130 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Factor Machine: Mixed-signal Architecture for Fine-Grained Graph-Based Computing Dudek, Piotr Hardware Architecture C.1.4 This paper proposes the design and implementation strategy of a novel computing architecture, the Factor Machine. The work is a step towards a general-purpose parallel system operating in a non-sequential manner, exploiting processing/memory co-integration and replacing the traditional Turing/von Neumann model of a computer system with a framework based on "factorised computation". This architecture is inspired by neural information processing principles and aims to progress the development of brain-like machine intelligence systems, through providing a computing substrate designed from the ground up to enable efficient implementations of algorithms based on relational networks. The paper provides a rationale for such machine, in the context of the history of computing, and more recent developments in neuromorphic hardware, reviews its general features, and proposes a mixed-signal hardware implementation, based on using analogue circuits to carry out computation and localised and sparse communication between the compute units. |
| title | Factor Machine: Mixed-signal Architecture for Fine-Grained Graph-Based Computing |
| topic | Hardware Architecture C.1.4 |
| url | https://arxiv.org/abs/2402.12130 |