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The team estimates that their hardware can outperform the best electronic processors by a factor of 100 in terms of energy efficiency and compute density.Get a daily digest of the latest news in tech, science, and technology, delivered right to your mailbox. Subscribe now.
A team of scientists from Oxford University and their partners from Germany and the UK have developed a new kind of AI hardware that uses light to process three-dimensional data. Based on integrated photonic-electronic chips, the hardware can perform complex calculations in parallel using different wavelengths and radio frequencies of light. The team claims their hardware can boost the data processing speed and efficiency for AI tasks by several orders of magnitude.
The team estimates that their hardware can outperform the best electronic processors by a factor of 100 in terms of energy efficiency and compute density, even with a modest scaling of 6 inputs × 6 outputs. They also expect to achieve further improvement in computing parallelism by exploiting more light features, such as polarization and mode multiplexing.
Dr. Bowei Dong, the first author of the paper and a researcher at the Department of Materials, Oxford University, said: “We used to think that using light instead of electronics could only increase parallelism by using different colors – but then we discovered that using radio frequencies to represent data opens up a whole new dimension, enabling superfast parallel processing for emerging AI hardware.
Professor Harish Bhaskaran, the leader of the research and the co-founder of Salience Labs, said: “This is an exciting time to be doing research in AI hardware at the fundamental scale, and this work is one example of how we can push the boundaries of what we thought was possible.”New developments in hardware-based “accelerators” range from electronic tensor cores and memristor-based arrays to photonic implementations.
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