Projects:2018s1-121 In-Memory Semantic Processing Using Hyperdimensional Computing

Project Team

Hanchao Guo

Tait Moseley

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Supervisor and Co-advisor

Branden Phillips and Peng Wang

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Introduction

In hyperdimensional computing, long binary vectors are used to encode knowledge. The relationship between facts can be captured using correlations between their binary encodings. Specially designed memory hardware can then perform operations, such as searches for relevant information, in parallel, in the memory. This is one way to overcome the well known von Neumann bottleneck of conventional computers, in which memory can only be searched sequentially. Hyperdimenional computing is a relatively new idea. A first aim of this project is to develop a case study example, simulated in software, that demonstrates its use in a practical application. The second aim of the project is to investigate hardware designs for memory circuits to perform hypervector operations in memory. These circuits may use emerging technologies such as resistive RAMs (RRAMs). Hardware to automate the spreading activation function is of particular interest.