Google is using Nvidia's supercomputer to improve the performance of its quantum computer.
On the evening of November 18th, Nvidia announced its latest collaboration with Google in the field of quantum computing at SC24. It is reported that Nvidia has provided Google with a Nvidia Eos supercomputer equipped with 1024 H100 GPUs, which, in conjunction with the CUDA-Q platform, can be used to simulate the process of system environment interaction in quantum computing and attempt to solve the "noise" problem in quantum computing.
To make a breakthrough in the commercialization of quantum computers, it is necessary to increase the scale of quantum computing while controlling the generated 'noise', "said a scientist from Google Quantum AI." With the assistance of NVIDIA, we can try to solve the negative impact of 'noise' when designing more complex quantum chips. "Previously, the related simulation calculations took a huge amount of time, about a week. However, Nvidia claims that the current computation time can be reduced to a few minutes.
Quantum computing is the next generation of computing models that follow the laws of quantum mechanics physics, and its computing speed far exceeds current computer processing. However, the development and commercialization of quantum computing is still in its early stages, and it is expected to take decades to achieve large-scale commercialization. Noise is considered the "danger of quantum processors". Quantum processors are highly sensitive to noise, and even very slight noise can interfere with quantum computing, thereby affecting the accuracy of quantum computing.
At present, many large international technology companies are focusing on the field of quantum computing. Google has released its roadmap of six major milestones in the field of quantum computing, and has achieved two milestones in 2019 and 2023 respectively. In 2019, it announced that its quantum computing could complete computing tasks that would take the most advanced computers 10000 years to complete in 200 seconds. In 2023, it once again announced a major breakthrough in the field of quantum error correction, which can significantly improve the accuracy of quantum computing. The third milestone that Google needs to achieve next is to implement quantum error correction in large-scale quantum computing, which can result in less than one error occurring in one million calculations. This requires further enhancement of its ability in large-scale quantum error correction technology, with the ultimate goal of achieving a complete and reliable quantum error correction computer.
In addition to Google, Microsoft is also actively laying out in the field of quantum computing and has released a roadmap to build a large-scale reliable quantum computer. At the same time, it also launches academic solutions on quantum computing, providing quantum computing services for scientific discoveries in fields such as medicine and physics. In the field of quantum computing, IBM is a strong competitor to Google and Microsoft. It has also released a quantum computing roadmap and released 1121 quantum bit Condor quantum processors. In addition, it will gradually release quantum processors such as Flamingo and Kookaburra, and focus on developing software systems for quantum computing.
According to ICV TA& According to K's data, the global market size for quantum computing is expected to reach 1.08 billion US dollars in 2023 and 19.7 billion US dollars by 2030, with a compound annual growth rate of 60%. According to calculations by Bank of Communications International, by 2030, China's quantum technology market (including quantum computing, quantum communication, and quantum measurement, with quantum computing accounting for the majority) will account for 15% of the global scale. In China, listed companies and startups such as Guodun Quantum and Benyuan Quantum are also making efforts in the field of quantum computing.