Computation Model: Cellular Automaton

All systems with computation model: Cellular automaton

Systems (12)

Belousov-Zhabotinsky (BZ) reaction computer

f(x) = boolean logic / reaction-diffusion computation (via chemical wave collisions)

The BZ reaction is an oscillating chemical system that produces propagating excitation waves in a thin layer of reagent (typically ferroin or ruthenium catalyst in acidified bromate/malonate). Signals...

stochastic irreversible approximate

BrainScaleS wafer-scale neuromorphic system

f(x) = accelerated analog spiking neural network emulation

BrainScaleS wafer-scale neuromorphic system blends analog wafer-scale integrators with digital control, forming the EBRAINS neuromorphic computing service for fast emulation of spiking neural networks...

stochastic irreversible approximate

DNA strand-displacement computer

f(x) = boolean logic / neural network inference (via hybridization cascades)

Single-stranded DNA molecules in solution compute via toehold-mediated strand displacement: a short single-stranded 'toehold' on a partially double-stranded gate complex allows an input strand to inva...

stochastic irreversible approximate

IBM TrueNorth

f(x) = event-driven spiking neural network inference with massively parallel neurosynaptic cores

IBM TrueNorth is a 45 nm CMOS neurosynaptic chip with one million programmable spiking neurons and 256 million configurable synapses. It realizes massively parallel, event-driven computation with asyn...

deterministic irreversible approximate

Intel Loihi 1

f(x) = Neuromorphic computing research

Intel Loihi 1 is an asynchronous digital neuromorphic research chip with 128 programmable cores connected by a packet-switched mesh, simulating roughly 130k neurons and 130M synapses per chip for robo...

deterministic irreversible exact

Intel Loihi 2

f(x) = asynchronous event-driven spiking neural networks with integrated learning

Intel's second-generation neuromorphic research chip implements asynchronous event-driven spiking neural networks with tightly coupled memory and compute plus sparse programmable synapses for adaptive...

deterministic irreversible approximate

Memristive Hopfield network optimizer

f(x) = optimization via chaotic annealing / transient dynamics

Memristive circuits implementing Hopfield network topology where the intrinsic nonlinearity of memristors creates transient chaotic annealing processes. The chaotic dynamics enable escape from local m...

stochastic irreversible heuristic

Neuromorphic chip (Intel Loihi / IBM TrueNorth)

f(x) = spiking neural network computation

Silicon chips that mimic neural computation using spiking neurons and synaptic connections. Intel Loihi and IBM TrueNorth implement event-driven, asynchronous processing with on-chip learning capabili...

stochastic irreversible approximate

Physarum polycephalum (slime mold)

f(x) = Steiner tree / shortest transport network (approximate)

The plasmodial slime mold extends filaments toward nutrient sources and progressively reinforces paths that carry more flow, pruning inefficient routes. Toshiyuki Nakagaki showed it reproduces the Tok...

stochastic irreversible heuristic

Repressilator (synthetic gene oscillator)

f(x) = limit-cycle oscillation / biological clock (via negative-feedback transcription loop)

Elowitz & Leibler (2000, Nature) constructed a synthetic oscillator in E. coli from three mutual repressor genes wired in a ring: LacI represses tetR; TetR represses cI; CI represses lacI. No gene pro...

stochastic irreversible approximate

SpiNNaker

f(x) = Massively parallel ARM968 neuromorphic fabric for real-time spiking networks

SpiNNaker machines at the University of Manchester network over a million ARM968 cores via packet-switched triple-torus routers to run spiking neural networks with local plasticity and sensor-motor I/...

deterministic irreversible exact

Thermodynamic computer (Normal Computing SPU)

f(x) = probabilistic sampling / linear algebra via thermal equilibration

Analog physics-based computers using thermodynamic principles for computation. Normal Computing's Stochastic Processing Unit (SPU) uses RLC circuits as unit cells with all-to-all coupling via switched...

stochastic irreversible approximate