Last updated: 17:39 UTC
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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顺利把数据搬到新家后，最后也是最关键的一步，彻底清理在 OpenAI 留下的痕迹。
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