可组合性而非计算性决定了模拟EML硬件织物的成本
Composability rather than computation sets the cost of an analog EML hardware fabric
- Portland State University（波特兰州立大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文研究模拟EML算子织物的成本，发现其计算高效但可组合性差，导致整体成本高昂，通用原语在机器层面失效。
AI中文摘要：
算子 eml(x, y) = exp(x) - ln(y) 与常数 1 结合可生成初等函数，是 NAND 的连续对应物。此前未曾有硬件研究探讨该算子能否构成有用的织物。我们在网络模型、电路仿真和 SkyWater 130 nm 版图中进行了探究。四个双极结以 13 fJ 的能量评估该算子，比宽度匹配的数字数据通路快 4-134 倍。然而，由这些算子组装的织物并不廉价：它输给了资源匹配的基线，且在实数域上其语法排除了三角函数。维持这些结工作点的放大器消耗了单元电流的 74.5%，因此一个单元的成本是其消耗的 3000 倍。提取的非理想性在单元需保持数值时造成 2.6 倍开销，而仅需可重复时则无开销。跨单元共享这些非理想性可恢复三个数量级中的两个。该前提是通用原语可授权统一机器，此前提在原语层面成立，但在机器层面失效。
英文摘要：
The operator eml(x, y) = exp(x) - ln(y) with the constant 1 generates the elementary functions, a continuous counterpart to NAND. Whether it yields a useful fabric had not been asked of hardware. We ask in network models, circuit simulation and SkyWater 130 nm layout. Four bipolar junctions evaluate the operator for 13 fJ, beating a width-matched digital datapath by 4-134x. The fabric assembled from them is not cheap: it loses to resource-matched baselines, and over the reals its grammar excludes trigonometry. Amplifiers holding those junctions' operating points take 74.5% of a cell's current, so a cell costs 3000 times what they spend. Extracted non-idealities cost 2.6x when a cell must hold a value and nothing when it need only be repeatable. Sharing them across cells recovers two of the three orders. The premise was that a universal primitive licenses a uniform machine. It survives in the primitive and fails in the machine.
