Most deep learning frameworks are built for flexibility. They handle dynamic graphs, varying batch sizes, and a multitude of layer types. Talos takes the opposite approach. It strips away the runtime, the scheduler, and the operating system overhead to expose the raw compute capability of the FPGA. By implementing the entire inference pipeline in SystemVerilog, we achieve deterministic, cycle-accurate control over every calculation.
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Secondly, a type table doesn’t make sense when you’re writing a parser for an editor to have syntax highlighting and code indexing. This is also one of the reasons I hate LSP.7 The idea of using a compiler frontend like clangd inside an editor makes no sense to me: what the compiler needs to see is irrelevant to what the user needs to see. The two kinds of parsers are fundamentally different.8
，这一点在爱思助手中也有详细论述
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