Each core: 1,024 spiking neurons, 131K synapses, a programmable learning engine. Cores communicate through a barrier-synchronized mesh or asynchronous event-driven network-on-chip.
Three-factor plasticity with eligibility traces and reward modulation. A programmable microcode engine lets you write custom learning rules — STDP, reinforcement learning, homeostatic normalization — in 14 opcodes.
Define networks, compile to hardware, simulate or deploy. Cycle-accurate simulator for development. FPGA backend for the real thing.
| Catalyst N1 | Loihi 1 | TrueNorth | SpiNNaker | BrainScaleS | |
|---|---|---|---|---|---|
| Total neurons | 131K | 131K | 1M | 18K* | 512 |
| Synapses/core | 131K | 128K | 256 | SW | 224 |
| On-chip learning | Yes | Yes | — | Yes | Yes |
| Graded spikes | Yes | — | — | — | — |
| Dendrite trees | Yes | Yes | — | — | — |
| Embedded CPU | Yes | Yes | — | Yes | — |
| Open design | Yes | — | — | Yes | — |
*Per ARM968 core. SpiNNaker scales to ~1M neurons across 1000+ chips.
Independent hardware engineer, UK. Every line of RTL, every test, every tool in the SDK. One person. 25 development phases. 98 test scenarios. Zero failures.
Full RTL, testbenches, SDK, and paper. CERN-OHL-W licensed. No NDAs. No black boxes.
View repositoryNext generation. Higher neuron density, enhanced compute primitives. Targeting feature parity with the industry's latest.