Abstract: A system for converting a machine learning algorithm includes: a programmatic interface layer configured to construct a data-flow diagram of an original machine learning algorithm based on a preset data flow generation tool; an operator placement and evaluation module configured to calculate placement costs of each operator in the data-flow diagram when the operator is executed by different participants; a data-flow diagram dividing and scheduling module configured to divide the data-flow diagram into multiple sub-diagrams according to the placement costs, and schedule each of the sub-diagrams to a target participant for execution; and a compilation and execution layer configured to compile the sub-diagrams into a new data-flow diagram based on a greedy algorithm strategy, and generate an instruction for each operator in the new data-flow diagram to obtain a distributed privacy protection machine learning algorithm.

Abstract: This invention relates to a Fe-Ni based high permeability amorphous alloy consisting of, in atom percent Ni 30-45%, Cr 0.5-1.2%, Si 5-14%, B 5-15%, P 1.0-3.0%, the balance Fe and inevitable impurities. The alloy is made by the rapid quenching melt method. It can be heat-treated in air and the excellent magnetic properties can be obtained as follows: B.sub.10 7900 Gs, B.sub.r 7500 Gs, H.sub.C 0.008 Oe, u.sub.m 68.times.10.sup.4. The present alloy is applied to make various magnetic devices which are used in electric apparatus and equipments.