Hewlett Packard Enterprise Development LP

Thomas Van Vaerenbergh

Giacomo Pedretti

Catherine Graves

Tobias Frederic Ziegler

Raymond G Beausoleil

John Paul Strachan

Suhas Kumar

Xian Xiao

Todd Richmond

Examples of the present technology provide 'tensorized' integrated coherent Ising machines that improve scalability by leveraging a tensorized optical coupling matrix comprising layers of multi-wavelength photonic tensor-train (TT) cores cascaded together via passive optical cross-connects. A multi-wavelength photonic TT core may comprise a Mach Zehnder interferometer (MZI) mesh (i.e., a lattice/array of interconnected MZIs) that modulates the phase and/or amplitude of optical signals. Tensorized integrated CIMs of the present technology can achieve further scalability optimizations by implementing bistable Ising nodes via one or more multi-wavelength Ising node collections. A multi-wavelength Ising node collection may comprise a bistable Ising nodes implemented on a common MZI, where each bistable Ising node of the multi-wavelength Ising node collection is associated with a separate wavelength of light.

Tensorized integrated coherent Ising machine

Examples of the presently disclosed technology provide CAM-based circuits specially constructed to implement Boolean satisfiability problems involving k-XOR-SAT clauses. With the strategic addition of auxiliary counting and logic circuits that evaluate match line voltage outputs of a CAM at k discrete times in order to determine whether a counted number of matches returned by a match line satisfies a pre-determine parity condition—where k represents a number of literals of a k-XOR-SAT clause of a Boolean satisfiability problem—a circuit of the present technology can leverage a common CAM (i.e., the same CAM) to implement the k-XOR-SAT clause and k-SAT clauses. Accordingly, this extremely versatile circuit can be used to implement k-XOR-SAT and k-SAT-k-XOR-SAT hybrid problems in less time, and with less hardware and power consumption than existing hardware accelerators.

Compact k-XOR-SAT filtering with cams

The disclosure generally provides for a method of solving a K-SAT problem. The method comprises programming one or more clauses of a Boolean expression for a K-SAT problem written in negated disjunctive normal form (DNF) to a ternary-CAM (TCAM) array comprising columns and rows of TCAM cells, applying an interpretation comprising one or more binary variables expected to solve the Boolean expression as an input along the columns to the TCAM array, returning a binary value for each clause and updating one or more variables within the interpretation if at least one clause is violated.

Compact K-SAT verification with TCAMs

The disclosure generally provides for a method of solving a K-SAT problem. The method comprises programming one or more clauses of a Boolean expression for a K-SAT problem written in negated disjunctive normal form (DNF) to a ternary-CAM (TCAM) array comprising columns and rows of TCAM cells. The method further includes applying an interpretation comprising one or more binary variables expected to solve the Boolean expression as an input along the columns to the TCAM array, returning a binary value for each clause, randomly selecting one matched match line, determining a selected clause from one or more violated clause, and altering one or more literals within the interpretation using a break count for each variable of the selected clause.

Stochastic local search accelerator based on cams for solving constraint satisfaction problems

Systems and methods are configured to provide a first problem to be solved to a network of memristors. A second problem to be solved can be gradually provided to the network of memristors. Controlled noise can be applied to the network of memristors for at least a portion of time during which the second problem is 'gradually' provided to the network of memristors. A solution to the second problem can be determined.

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Diegem, Belgium

Thomas Van Vaerenbergh