AI technology, particularly generative AI, is rapidly evolving, revealing a significant memory bottleneck in traditional IT architectures which hampers performance despite advancements in CPUs and GPUs.
The introduction of Compute Express Link (CXL) is significant as it allows for pooling and sharing of memory resources, potentially lowering costs and addressing AI's performance limitations.
As large language models grow and traditional IT designs struggle, it becomes clear that memory bandwidth has stalled in relation to CPU core expansion, leading to performance inefficiencies.
The memory bottleneck not only causes latency but also leads to excessive memory copying, high storage I/O demands, and problems with buffering and memory overflow, complicating AI operations.
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