Scientists used IBM's R2 Heron quantum processor to predict the secondary protein structure of a 60-nucleotide-long mRNA ...

Quantum programs typically execute via a predictable pattern of qubits. HyperQ determines the optimum time slots for each ...

Chipsets known as graphics processing units (GPUs) are capable of running sophisticated algorithms in parallel, helping businesses achieve breakthroughs across myriad generative AI applications ...

Their new design method uses voxel-like building blocks and an algorithm called MOSES to fabricate nanoscale devices in parallel, with applications ranging from optical computing to bio-scaffolds.

A team from the Chinese Academy of Sciences developed a parallel optical computing architecture with 100 wavelengths, pushing the boundary of computility.

Parallel computing underpins much of today’s software, especially large language models (GPUs are parallel by design). Even so, the basic technique could be applied to a wider range of problems.

2. Implement hybrid cryptography. • Adopt a crypto-agile approach, allowing systems to support a hybrid approach with classical and quantum-resistant algorithms in parallel.

As quantum computing technology continues to advance, MicroAlgo's multi-simulator collaborative subgraph isomorphism algorithm is expected to play a key role in more application areas.

Chinese researchers have achieved a groundbreaking performance boost in supercomputing, using domestically developed GPUs. Their new computing model delivered a nearly tenfold speed improvement ...