TreeGRNG: Binary Tree Gaussian Random Number Generator for Efficient Probabilistic AI Hardware
Bayesian Neural Networks (BNNs) offer opportunities for greatly enhancing the trustworthiness of conventional neural networks by monitoring the uncertainties in decision-making. A significant drawback for BNN inference at the extreme edge, however, is the imperative need to incorporate Gaussian Random Number Generators (GRNG) within each neuron. State-of-the-art GRNG algorithms heavily depend on multiple arithmetic operations and the use of extensive look-up tables, posing significant implementation challenges for ultra-low power hardware implementations. To overcome this, this paper presents an innovative binary tree random number generator (TreeGRNG) allowing the use of ultra-low-cost c...
| Authors | Jonas Crols, Guilherme Paim, Shirui Zhao et al. |
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| Primary category | cs.AR |
| Published | 15 June 2026 |
| Last updated at source | 15 June 2026 |
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