Researchers were able to enhance light-based chipsets for computers! Right now, people are demanding more powerful computing abilities for applications in artificial intelligence.
These include speech and pattern recognition, or self-driving vehicles. The demands often exceed the capacities of conventional computer processors.
And now, the researchers at the University of Munster are creating new methods and process architectures. They can cope with these tasks more efficiently. These experts revealed what they call photonic processors.
These chips process by means of light, and can process information much more rapidly and in parallel. Electronic chips nowadays are not capable of doing this kind of task.
Combining photonic structures with PCMs
According to Science Codex's latest report, the scientists and researchers combined the phase-change materials or PCMs with the photonic structures. They used PCMs as energy-efficient storage elements.
These materials are commonly integrated into BluRay discs or DVDs in optical data storage. However, the new chips are now unable to store and preserve matrix elements without the need for an energy supply.
To solve this issue, the scientists used a chip-based frequency comb as a light source to carry out matrix multiplications on multiple data sets in parallel.
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Munter physicists explained that a frequency comb provides different optical wavelengths. These are processed independently of one another in the same photonic chip.
The innovation allowed the new chipsets to enable highly parallel data processing. They can now do this by calculating on all wavelengths continuously.
Top chip manufacturers today
As of the moment, almost all giant chipset manufacturers are still developing and focusing on electronic chips. Although this technology has certain limitations, they are still able to integrate great features that can really improve the experience of many users. ElectronicsAndYou's are listed as the top manufacturers right now.
- Samsung Electronics
- SK Hynix
- Intel Corporation
- Micron Technology
- TSMC
- Avago Technologies
- Nvidia
- Toshiba
- Qualcomm
- Texas Instruments
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Written by: Giuliano de Leon.