Hello, I&#39;ve been getting a lot of enquiries about GPU quantum computer simulators recently, so I&#39;ll give an overview again. GPU stands for Graphics Processing Unit and is originally a processor for drawing screens, but its parallel processing is increasingly being used for scientific computing, and it has developed very well in recent years for AI. GPUs have recently been used for deep learning calculations, CG and VR/AR for the metaverse, but recently tools have emerged to use them in quantum computer hybrids and quantum computer simulations themselves, and are being used worldwide by Google IBM Amazon Microsoft and others have adopted it and it has become a hot topic. The tool is called cuQuantum and can be easily installed on a GPU-equipped server or PC and quickly turned into a full-fledged development tool. It is also extremely fast in terms of speed, recently using a GPU owned by the AIST of the Ministry of Economy, Trade and Industry, it easily broke the world&#39;s fastest speed record to date, and it has been announced that it will further double the speed by using the latest GPUs that have newly appeared on the market. Enquiries about the cuQuantum have increased dramatically, and there has been a huge increase in requests to use it for quantum human resource development applications and research. This cuQuantum can be used for programming methods called quantum gates, and it has tremendous versatility in that it can run the quantum gate programming software that has been created so far as it is without modification. The great thing about cuQuantum is that it can be used without modification for quantum gate programming. The great thing about cuQuantum is that it was developed in Japan, and as you may know if you have been attending our blueqat conferences for a while, the Japanese representatives at NVIDIA have been working on it as Qgate since around 2016, gradually improving it for quantum computers. This is an official commercialisation of a programme that we have been working hard on, so it is a product that can easily benefit from this in Japan. GPUs are also used in the fields of machine learning and AI, so tools can be shared for human resource development and other purposes, so there is no waste of investment. In addition, the number of companies using Quantum AI and existing AI in comparison has been increasing significantly recently, so you can learn both. Furthermore, all the tools are free of charge and are constantly being improved to make them faster. Installation is also easy. We are also listed on NVIDIA&#39;s website as one of the few official integration tools in the world, so please contact us if you are interested in offering on-premise or in the cloud. <a href="https://developer.nvidia.com/cuquantum-sdk" rel="noopener noreferrer" target="_blank">https://developer.nvidia.com/cuquantum-sdk</a>

We get so many enquiries about GPU quantum computer simulator cuQuantum

Yuichiro Minato