20240012570. INTELLIGENT CLASSICAL/QUANTUM EXTENDED MEMORY FABRIC simplified abstract (Dell Products L.P.)

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INTELLIGENT CLASSICAL/QUANTUM EXTENDED MEMORY FABRIC

Organization Name

Dell Products L.P.

Inventor(s)

Kenneth Durazzo of Morgan Hill CA (US)

Stephen J. Todd of North Andover MA (US)

Michael Robillard of Shrewsbury MA (US)

Victor Fong of Melrose MA (US)

Brendan Burns Healy of Whitefish Bay WI (US)

Eric Bruno of Shirley NY (US)

INTELLIGENT CLASSICAL/QUANTUM EXTENDED MEMORY FABRIC - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240012570 titled 'INTELLIGENT CLASSICAL/QUANTUM EXTENDED MEMORY FABRIC

Simplified Explanation

The abstract of the patent application describes a method that involves receiving a hybrid/classical algorithm and determining its runtime characteristic. Based on this characteristic, the method checks if there is enough memory available for executing the algorithm. If there is inadequate memory, the method modifies a classical/quantum memory fabric to provide sufficient memory support for the algorithm. Finally, the method orchestrates the execution of the hybrid classical/quantum algorithm in an environment that includes the modified memory fabric.

  • The method receives a hybrid/classical algorithm.
  • It determines the runtime characteristic of the algorithm.
  • Based on the runtime characteristic, it checks the availability of memory for executing the algorithm.
  • If there is insufficient memory, the method modifies a classical/quantum memory fabric to provide enough memory support.
  • The method orchestrates the execution of the hybrid classical/quantum algorithm in an environment that includes the modified memory fabric.

Potential Applications:

  • Quantum computing: This technology could be applied in the field of quantum computing to optimize the execution of hybrid classical/quantum algorithms by ensuring sufficient memory availability.
  • Algorithm development: The method could be used in algorithm development to analyze the runtime characteristics of hybrid/classical algorithms and determine memory requirements for efficient execution.

Problems Solved:

  • Inadequate memory for hybrid/classical algorithm execution: The method solves the problem of insufficient memory availability for executing hybrid/classical algorithms by modifying the memory fabric to provide enough memory support.

Benefits:

  • Improved algorithm execution: By ensuring sufficient memory availability, the method enhances the execution of hybrid/classical algorithms, leading to improved performance and accuracy.
  • Optimal resource utilization: The method optimizes the utilization of memory resources by dynamically modifying the memory fabric based on the runtime characteristics of the algorithm.


Original Abstract Submitted

one example method includes receiving a hybrid/classical algorithm, determining a runtime characteristic of the hybrid/classical algorithm, based on the runtime characteristic, checking a memory availability for execution of the hybrid/classical algorithm, when adequate memory is not available to support execution of the hybrid/classical algorithm, modifying a classical/quantum memory fabric to provide enough memory to support execution of the hybrid/classical algorithm, and orchestrating the hybrid classical/quantum algorithm to an execution environment that includes the classical/quantum memory fabric.

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