(Nanowerk News) Researchers have developed a new light-based computing scheme that uses photonic integrated circuits to reduce the energy required for cryptocurrency and blockchain applications. Mining cryptocurrencies like Bitcoin—the process of verifying transactions and adding new cryptocurrencies to the blockchain—consumes up to 1% of the world’s energy. This energy expenditure is expected to grow as cryptocurrency and blockchain applications become more common.
Cryptocurrency is a digital currency that is created using encryption algorithms. This alternative currency requires a blockchain—a type of digital ledger that records information such as transactions in a way that is difficult or impossible to change or hack.
“Right now, cryptocurrency mining is only accessible to those who have access to highly discounted energy—under $0.05/kWh,” said first author Sunil Pai, who did research at Stanford and now works at a quantum computing company. PsiQuantum. “Our low energy chip will enable individuals worldwide to participate in mining profitably.”
In the OPTICAL (“An experimental evaluation of digitally verifiable photonic computing for blockchain and cryptocurrency”), the researchers detail their new scheme called LightHash, which uses photonic integrated circuits to create photonic blockchains. With further development, the researchers estimate that this approach, if implemented on a large scale, could result in about a tenfold increase in energy usage compared to the best modern digital electronics processors. David AB Miller leads the Stanford University research team with Shanhui Fan and Olav Solgaard.
“Our approach to photonic blockchains can also be used for applications outside of cryptocurrencies such as securely transferring data for medical records, smart contracts and voting,” said Pai. “This work paves the way for low-energy optical computing, which could ultimately reduce data center energy consumption.”
More environmentally friendly mining with silicon photonics
Growing concern about the large amounts of energy needed to mine cryptocurrencies has led some popular ones like Ethereum to turn to unproven and potentially unsafe schemes to minimize their carbon footprint.
To find a more environmentally friendly approach while maintaining a high level of security, Pai and colleagues used silicon photonics to reduce the energy requirements of cryptocurrency networks. LightHash improves upon a scheme previously developed by a team called HeavyHash which is currently used in cryptocurrency networks such as Optical Bitcoin and Kaspa.
“LightHash’s main motivation is HeavyHash’s high sensitivity to hardware faults,” said Pai. “Because analog computers, including photonic ones, struggle to achieve low error rates, we designed LightHash to retain all of HeavyHash’s security properties, while increasing its robustness to errors.”
Safely creating Bitcoins or operating their computational network requires computing hash functions such as SHA256 or Heavyhash to convert input data into a single output number in a way too complex to undo, which accounts for most of Bitcoin’s energy usage. In the new work, the researchers modified Heavyhash to work with a co-designed silicon photonic chip carrying a 6×6 network of programmable interferometers. This enables low-energy optical processing of matrix multiplication, which forms a large part of computation in Lighthash.
To evaluate the feasibility of using LightHash for matrix multiplication, the researchers built an optical rig to control and track light propagation by tuning heating elements and imaging lattice points to an infrared camera. They also implement error mitigation algorithms and define eligibility criteria for scaling the technology.
Accurate low power calculation
The experimental results achieved with silicon photonic chips match those obtained using the simulated fault predictions. “Our results show that LightHash can be feasibly computed at large scale using current silicon photonic chip technology,” said Pai. “Basically, we have found a way to use analog optical circuits to perform multiplication with near-zero power dissipation yet precise enough to be used in digital encryption schemes.”
For LightHash to demonstrate huge advantages over digital equivalents, it had to be scaled up to 64 inputs and outputs. The researchers are also working to further reduce energy consumption by designing low-power electromechanical tuning elements and energy-efficient converters to convert optical signals to electrical signals.
They say that because the new chip accelerates matrix multiplication, the most computationally intensive operation for AI applications, it could also help make the training and deployment of photonic neural networks more energy efficient compared to conventional digital implementations.
“It will be interesting to see how cryptocurrency technology develops and to what extent photonics can contribute to the increasingly mainstream role of decentralized ledgers in today’s society,” said Pai.