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Resilient Brain-Inspired Hyperdimensional Computing Architectures

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Short Description

The mathematical properties of high-dimensional (HD) spaces show remarkable agreement with behaviors controlled by the brain. Computing with HD vectors, referred to as “hypervectors,” is a brain-inspired alternative to computing with numbers. The most important aspect of HD computing is its robustness against noise and variations in the computing platforms, allowing to implement resilient controllers. Its tolerance in low signal-to-noise ratio (SNR) conditions and for faulty components is achieved by brain-inspired properties of hypervectors: (pseudo)randomness, high-dimensionality, and fully distributed holographic representations.

In this project, your goal would be to design and develop an end-to-end robust HD processor with extremely resilient controller based on principles of HD computing, and measure its resiliency against faulty components.

Status: Available

Looking for 1-2 Semester/Master students
Contact: Abbas Rahimi


HDL coding
Fault Injection and Testing


20% Theory
40% Architecture Design
40% Test


Luca Benini

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Detailed Task Description


Practical Details



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