synaptogen 0.2.0

A fast generative model for stochastic memory cells

Synaptogen.py

This is a quick translation of Synaptogen into Python.

The code is not highly optimized and is considerably slower than the Julia version.

Installation

pip install synaptogen

Examples

This basic example does the following:

• Initialize a million memory cells (in their high resistance states)
• Apply -2 V to each cell, putting them into their low resistance states
• Apply a random voltage to each cell
• Make a current readout of all the cells individually (at a default of 0.2 V)
• Perform a "Vector Matrix Multiplication" by 1024×1024 crossbar readout

from synaptogen import *
import numpy as np
M = 1024 * 1024
cells = CellArrayCPU(M)

applyVoltage(cells, -2)

voltages = np.random.randn(M)
applyVoltage(cells, voltages)

I = Iread(cells)

col_voltages = np.random.randn(2**5) * .2
row_currents = cells @ col_voltages