execution of probabilistic computing algorithms require electrically programmable stochasticity to encode arbitrary probability functions and controlled stochastic interaction or correlation between probabilistic (p-) bits. the latter is implemented with complex electronic components leaving a large footprint on a chip and dissipating excessive amount of energy. Here, we show an elegant implementation with just two dipole-coupled magneto-tunneling junctions (MtJ), with magnetostrictive soft layers, fabricated on a piezoelectric film. The resistance states of the two MTJs (high or low) encode the p-bit values (1 or 0) in the two streams. The first MTJ is driven to a resistance state with desired probability via a current or voltage that generates spin transfer torque, while the second MTJ's resistance state is determined by dipole coupling with the first, thus correlating the second p-bit stream with the first. The effect of dipole coupling can be varied by generating local strain in the soft layer of the second MTJ with a local voltage (~ 0.2 V) and that varies the degree of anticorrelation between the resistance states of the two MTJs and hence between the two streams (from 0 to 100%). This paradigm generates the anti-correlation with "wireless" dipole coupling that consumes no footprint on a chip and dissipates no energy, and it controls the degree of anti-correlation with electrically generated strain that consumes minimal footprint and is extremely frugal in its use of energy. It can be extended to arbitrary number of bit streams. This realizes an "all-magnetic" platform for generating correlations or anti-correlations for probabilistic computing. it also implements a simple 2-node Bayesian network. There is an emerging focus on "probabilistic computing" with probabilistic (p-) bits encoded in the resistance states of magneto-tunneling junctions (MTJs) whose soft layers are nanomagnets possessing low energy barriers 1. This paradigm has been shown to be successful in solving computationally-hard problems such as factorization 2 , combinatorial optimization 3 , population coding 4 , invertible logic 5 , and has been used in restricted Boltzmann machines 6 and belief networks 7. p-bit based computing requires stochastic interaction and controlled correlation between p-bits. Controlled correlations are also needed for some graphical circuit models of stochastic computing, computer vision and image processing applications 8-12. These correlations are typically generated with the aid of complex electronic hardware that may involve shift registers, Boolean logic gates, random number generators, multiplexers, binary counters, comparators, etc. or microcontrollers for generating synaptic weights 2-5. They consume large areas on a chip, dissipate enormous amounts of energy, and are expensive to implement. In this paper, we show how to implement an ultra-compact and ultra-energy-efficient p-bit correlator with dipolecoupled MTJs fabricated on a piezoelectric film, with each MTJ hosting a p-bit. The dipole coupling corr...

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