Quantum Simulator Beats Quantum Hardware
+ Why wait for quantum computers to be perfected “someday,” when you can use Toshiba’s quasi-quantum optimization algorithm on Microsoft’s Azure cloud in 2021? It outperforms today’s fledgling quantum computer speeds through the use of that proprietary algorithm on conventional digital computers accelerated with cloud GPUs [graphic processing units].
“We also expect further improvements in our algorithms,” said Goto, “and further development of digital parallel computing technologies, both of which will accelerate our quasi-quantum bifurcation solution.”
+ “It will take a very long time for quantum computers to achieve the high performance of our [GPU and FPGA-powered] optimization solutions for large-size problems,” said Hayato Goto, chief research Scientist at Toshiba Corp. in Japan. In fact, Goto said, “So far, no one has even been able to prove that any future quantum computer will be able to solve combinatorial optimization problems faster, which leaves room for our classical machines to surpass quantum computers.”
+ The key to its high-speed large-problem optimization solutions, according to Toshiba, is the use of simulated bifurcation (SB), which is digitally accelerated with GPUs or FPGAs, both of which outperform both traditional digital optimization algorithms on CPUs (central processing units) and current quantum bifurcation hardware that emulates thermodynamic adiabatic annealing (as in D-Wave’s hardware).
+ “Toshiba’s simulated bifurcation algorithm is promising for a solver of optimization problems, especially its high-performance implementations using GPUs and FPGAs, ” said processor research team leader Kentaro Sano at Japan’s independent government-funded Institute of Physical and Chemical Research (RIKEN). “I also think that it can be favorably compared with present hardware of quantum [D-Wave] or digital [Fujitsu] annealers.”
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