Precise writing of multi-level weights to memory devices for compute-in-memory

A method, comprising:

• generating a base current to provide to a non-volatile memory capable of storing a plurality of discrete current levels, wherein the discrete current levels correspond to synaptic weights to be provided to an artificial neural network (ANN);
• generating an interval current above the base current, based at least in part on the generated base current;
• calculating a ceiling current that is the sum of the base current and interval current;
• reading a current from a memory cell of a non-volatile memory;
• writing repeatedly, while the current from the memory cell is less than the ceiling current, a voltage to the memory cell that induces the current read from the memory cell to incrementally increase;
• and
• stopping the writing when the current from the memory cell exceeds the base current,
• wherein the base current is generated based upon a selected discrete current level, from the plurality of discrete current levels, that corresponds to a provided synaptic weight.

A computing device, comprising:

• a processor;
• a multi-level memory coupled to the processor, the memory adapted to store a level of a plurality of levels of an electrical parameter that indicates a synaptic weight for an artificial neural network;
• and
• memory controller logic coupled to the processor and the memory,
• wherein the memory controller logic is configured to:
• generate a base reference of the electrical parameter;
• generate a ceiling reference of the electrical parameter that is a predetermined interval above the base reference;
• read a stored electrical parameter from the multi-level memory;
• write repeatedly, while the stored electrical parameter from the memory is less than the ceiling reference, an electrical signal to the memory that causes the stored electrical parameter in the memory to incrementally increase;
• and
• discontinue the write when the stored electrical parameter is greater than the base reference.