I'm not sure how you managed to get that much wrong. Most applications perform synchronous filesystem I/O. Async filesystem I/O is a rare curiosity implemented

I'm not sure how you managed to get that much wrong. Most applications perform synchronous filesystem I/O. Async filesystem I/O is a rare curiosity implemented in a handful of high end databases. You also seem completely unaware of the super scalar and out of order nature of modern processors or why hyperthreading/SMT is even a thing. The way a processor works nowadays is more akin to treating the instruction sequence as a graph for which it is possible to find subgraphs, which can be processed in parallel and that includes memory accesses. Then finally you didn't consider how frequent a remote memory access or how expensive a remote memory access is without CXL. Since CXL is cache coherent, you only need to load from remote memory when the data is not in local DRAM or your local cache. This means that remote memory accesses are relatively rare. In the case that you do nothing but remote memory accesses, you have to consider your competition as a baseline. The competition used to be RDMA over infiniband or Ethernet and the total latency for those is significantly higher. This means that if remote memory access is important to you, CXL is faster than the alternatives. You seem to be thinking of a hypothetical situation in which no one uses remote memory accesses at all. That is not a fair comparison. The reason why CXL is unsuitable for AI is already mentioned in the article. AI doesn't care about cache coherence, only bandwidth but NVLink is even worse at what you are concerned about.