Braindrop : a mixed-signal neuromorphic architecture with a dynamical systems-based programming model
Abstract/Contents
- Abstract
- This thesis describes the architecture of Braindrop, a .85 square-millimeter, 4096-neuron, low-power, mixed-signal neuromorphic system. Braindrop is the first such system designed with a comprehensive set of high-level programming abstractions and a synthesis procedure for mapping them to mismatched (and temperature-sensitive) subthreshold analog hardware. This high level of abstraction stands in stark contrast to previous neuromorphic systems, which required expert knowledge (and extensive characterization) of the hardware to use. Braindrop's computations are specified as coupled nonlinear dynamical systems. This program specification is synthesized to the hardware using the Neural Engineering Framework, not just compensating for, but leveraging the fabric of mismatched analog circuit elements as dynamic computational primitives. For typical network configurations, Braindrop achieves an energy per equivalent synaptic operation of 388 fJ.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2018; ©2018 |
| Publication date | 2018; 2018 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Neckar, Alexander |
|---|---|
| Degree supervisor | Boahen, Kwabena (Kwabena Adu) |
| Thesis advisor | Boahen, Kwabena (Kwabena Adu) |
| Thesis advisor | Manohar, Rajit |
| Thesis advisor | Olukotun, Oyekunle Ayinde |
| Degree committee member | Manohar, Rajit |
| Degree committee member | Olukotun, Oyekunle Ayinde |
| Associated with | Stanford University, Department of Electrical Engineering. |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Alexander Neckar. |
|---|---|
| Note | Submitted to the Department of Electrical Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2018. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2018 by Alexander Smith Neckar
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