Interactive 3D Crossbar Array Visualization | WebGL + Three.js | Memristor Device Simulation | Author: QAISER ABBAS
Research-grade framework for memristive crossbar security analysis, fault injection, side-channel attacks, and PUF-based hardware defenses using MemTorch + PyTorch.
MemristorLab — Interactive Memristive Neuromorphic Computing & In-Memory AI Laboratory. 6 modules: memristor physics, crossbar VMM, sneak path analysis, weight mapping, neuromorphic inference, energy arena. Zero dependencies.
VOLT — Virtual Ohmic Logic Testbench: Rust AIMC crossbar physics simulator (Ohm/KCL, DAC/ADC, noise). Optional PyO3 bindings.
Differential memristive crossbar with a hardware-friendly in-situ (Manhattan/sign-rule) learning rule, tested on parity-3 — the calibrated in-memory-compute baseline of the physical-learning-substrates portfolio. Verdict #1: PASS, learns parity-3 at SNR ~24.5 (half co-located: physics activations, off-array error sign, physical-pulse increment).
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