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Classical Computing Fights Back!

Something that gets lost in all the noise and hype associated with quantum computing is the fact that innovations in classical computing keep on coming. We’ve seen two recent examples that show how innovations in classical computing algorithms may be able provide competitive solutions for hard combinatorial optimization problems.  These types of problems are common in industrial settings and have applications in finance, logistics, forecasting, routing, machine learning and other problems that can be expressed as an optimization.

 

The second development is from a company in San Diego, California called MemComputing Inc.  Using research originally developed at the University of California, San Diego they have a technology they call the MemCPU™ Coprocessor technology. A key element in their approach is a device called a Self Organizing Logic Gate.  These gates are arranged in a network and each one can accept an input from any terminal. All the gates then work together collectively to achieve an optimal state. MemComputing has published several case studies and white papers on the MemComputing web site and is currently offering their technology on the cloud as SaaS (Software as a Service).  They indicate that even with their current approach of simulating their technology using CPU or GPU resources in a classical cloud data center they are already achieving very good performance. They are also planning in the future to develop an ASIC that will implement their algorithm in hardware and further improve their performance by several orders of magnitude. One notable paper posted on arXiv titled Stress-testing memcomputing on hard combinatorial optimization problems describes how they were able to handle a problem with 64×106 variables using a computer with 128GB of memory.