Communicating and computing with spikes in neuromorphic systems
Abstract/Contents
- Abstract
- We provide an overview of neuromorphic engineering and describe two contributions to Braindrop, a state-of-the-art neuromorphic system. First, we describe a method for performing summing and weighting of spike trains by accumulative thinning, a deterministic procedure for merging and dropping spikes. Previous methods relied on probabilistic thinning, which results in Poissonian statistics. As a result, when the thinned spike-train is filtered with a first-order low-pass synapse, the signal-to-noise ratio (SNR) scales as the square-root of its rate. For our accumulative thinning method, the SNR depends on the weight w; it scales linearly in the best-case scenario (w-> 0) and as the square-root in the worst-case (w-> 1). We find that a three-quarter power scaling minimizes energy consumption. Second, we present a serial H-tree router for two-dimensional (2D) arrays. Existing routing mechanisms for 2D arrays either use low-overhead grids with one or two shared wires per row or column (e.g., RAM) or high-overhead meshes with many wires connecting neighboring clients (e.g., supercomputers). Neither is suitable for intermediate-complexity clients (e.g., small clusters of silicon neurons). We present a router tailored to 2D arrays of such clients. It uses a tree laid out in a fractal pattern (H-tree), which requires less wiring per signal than a grid, and adopts serial-signaling, which keeps link-width constant, regardless of payload size. To route from the tree's leaves to its root (or vise versa), each node prepends (consumes) a delay-insensitive 1-of-4 code that signals the route's previous (next) branch; additional codes carry payload. We employ this serial H-tree router to service a 16x16 array of silicon-neuron clusters, each with 16 spike-generating analog somas, 4 spike-consuming analog synapses, and one 128-bit SRAM. Fabricated in a 28-nm CMOS process, the router communicates 26.8M soma-generated and 18.3M synapse-targeted spikes per second while occupying 43% of the client's 35.1x36.1 sq.um.
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 | Fok, Sam |
|---|---|
| Degree supervisor | Boahen, Kwabena (Kwabena Adu) |
| Thesis advisor | Boahen, Kwabena (Kwabena Adu) |
| Thesis advisor | Khatib, Oussama |
| Thesis advisor | Shenoy, Krishna V. (Krishna Vaughn) |
| Degree committee member | Khatib, Oussama |
| Degree committee member | Shenoy, Krishna V. (Krishna Vaughn) |
| Associated with | Stanford University, Department of Electrical Engineering. |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Sam Fok. |
|---|---|
| Note | Submitted to the Department of Electrical Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2018. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2018 by Sam Fok
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