[Hardware]: DMP-SNN
Nobody has claimed this yet.
Assessment
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Newbie friendliness
- 68/100
- Issue type
- Documentation
- Clarity
- Mostly clear
- Activity status
- Quiet
- Tech stack
- html
- Domain
- documentation
Research direction
Review the repository's existing hardware entries, then verify the DMP-SNN details against the linked paper and source repository. Add the supplied product information and links using the site's established format; done when the DMP-SNN entry is complete and consistent with the other hardware listings.
Written by the indexing model from the issue text.
Description
Product Name
DMP-SNN
Manufacturer / Organization
Imperial College London
Short Summary
open-hardware near-memory-compute architecture that fully leverages the advantages of the dual memory pathway architecture by retaining its compact shared state while optimizing data flow
Product/Organization Website
No response
Chip Type
Digital
Development Status
Announced
Release Year/Date
2026-06-16
Neuron Count
No response
Synapse Count
No response
Power Consumption
No response
Supported Software/SDK
No response
Detailed Description / Overview
Paper: https://www.nature.com/articles/s42256-026-01255-3
Source: https://github.com/sunpengfei1122/Dual_memory_pathways/tree/main
Related Publications
No response
- Dominant language
- HTML
- Stars
- 37
- Forks
- 30
- PR merge metrics
- No merged PRs in 30d
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
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