11 — Silixon-GPU

Graphics and Parallel Processing Unit

What It Is

Silixon-GPU is Hardin Labs' massively parallel computing accelerator, architecturally designed for workloads involving holographic rendering, AI inference, DNA sequence analysis, fusion plasma simulation, and general matrix computation. Unlike conventional silicon GPU chips that rely on copper interconnects and flip-chip packaging on organic substrates, the Silixon-GPU is implemented on a Silixon-HCB hybrid circuit board substrate, with the processor die bonded directly to the ceramic board using galinstan thermal interface material for zero-thermal-resistance die attachment, and inter-chip photonic links replacing conventional copper data buses for the highest-bandwidth inter-accelerator communication.

Architecture

The Silixon-GPU is organized as a mesh of 1,024 compute tiles, each containing 64 processing cores running at 3.2 GHz for a total of 65,536 physical cores. Tiles communicate through a photonic NoC (Network-on-Chip) in which laser pulses at 850 nm wavelength are routed through the HCB's embedded waveguide layer at light speed, delivering tile-to-tile latency below 100 ps at any mesh distance. The memory hierarchy consists of Silixon RAM integrated directly beneath the compute tiles in a 3D stack, providing each tile with 2 TB/s local memory bandwidth — sufficient to sustain full compute utilization on uncompressed holographic video streams at 8K per eye resolution.

Thermal Design

The thermal dissipation challenge of 65,536 active cores is met by the galinstan micro-channel network integrated into the Silixon-HCB substrate. Coolant flow is modulated by micro-electromechanical valves responsive to per-tile thermal sensors, delivering adaptive cooling that focuses maximum flow to the hottest active regions. The external faces of the GPU board are clad with Silixon-Radiant panels, providing an additional passive radiation path that reduces the required galinstan pump flow rate by 30% under average workloads.