According to SK Hynix Executive Vice President Joo Young-pyo at the Intel AI Summit Seoul 2026 on November 12, the company proposed a "rack-scale" memory architecture to address memory bottlenecks in AI workloads. Instead of attaching multiple memory modules directly to individual GPUs, the solution centralizes hundreds of terabytes of memory in dedicated racks shared by GPU and CPU clusters. SK Hynix internal experiments showed faster response times with this configuration. The company plans to validate the approach with partners including Intel.

View Source

Disclaimer: This content is for informational purposes only and does not constitute investment advice or encourage the buying or selling of crypto assets. It is intended to provide information about industry developments and is not directly related to the services offered by Gate TR. Although information obtained from third-party sources has been carefully reviewed, Gate TR assumes no responsibility for any errors or omissions. Crypto assets involve high risks and may experience significant price fluctuations. Before making any investment decisions, you should assess your financial situation and risk tolerance, conduct your own research, and make decisions independently.