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Load Balancing For High Performance Computing Using Quantum Annealing: Grid Based Application
This story was originally published on HackerNoon at: https://hackernoon.com/load-balancing-for-high-performance-computing-using-quantum-annealing-grid-based-application.
Exploring quantum annealing's efficacy in load balancing for high-performance computing with grid-based and off-grid simulations on quantum hardware.
Check more stories related to programming at: https://hackernoon.com/c/programming.
You can also check exclusive content about #load-balancing, #high-performance-computing, #quantum-annealing, #grid-based-simulation, #off-grid-simulation, #computational-physics, #exascale-computing, #parallel-computing, and more.
This story was written by: @loadbalancing. Learn more about this writer by checking @loadbalancing's about page,
and for more stories, please visit hackernoon.com.
Quantum annealing (QA) was used to partition a grid using a round robin protocol. QA and SA appear to surpass SD when computational work is distributed across a higher number of processors. A distinct “kink” is observed when partitioning across four processors. This kink indicates a drop in solution quality compared to the results achieved with Simulated Annealing (SA) and Steepest Descent (SD)
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By HackerNoonThis story was originally published on HackerNoon at: https://hackernoon.com/load-balancing-for-high-performance-computing-using-quantum-annealing-grid-based-application.
Exploring quantum annealing's efficacy in load balancing for high-performance computing with grid-based and off-grid simulations on quantum hardware.
Check more stories related to programming at: https://hackernoon.com/c/programming.
You can also check exclusive content about #load-balancing, #high-performance-computing, #quantum-annealing, #grid-based-simulation, #off-grid-simulation, #computational-physics, #exascale-computing, #parallel-computing, and more.
This story was written by: @loadbalancing. Learn more about this writer by checking @loadbalancing's about page,
and for more stories, please visit hackernoon.com.
Quantum annealing (QA) was used to partition a grid using a round robin protocol. QA and SA appear to surpass SD when computational work is distributed across a higher number of processors. A distinct “kink” is observed when partitioning across four processors. This kink indicates a drop in solution quality compared to the results achieved with Simulated Annealing (SA) and Steepest Descent (SD)