TDS Buys D-Wave 2000Q
Quantum Computer for $15M
Cyber security firm Temporal Defense Systems has purchased a D-Wave Quantum Computer. With 2000 qubits and new control features, the new system can solve larger problems than was previously possible, with faster performance, providing a big step toward production applications in optimization, cybersecurity, machine learning, and sampling.
"D-Wave's leap from 1000 qubits to 2000 qubits is a major technical
achievement and an important advance for the emerging field of quantum
computing," said Earl Joseph, IDC program vice president for high
performance computing. "D-Wave is the only company with a product
designed to run quantum computing problems, and the new D-Wave 2000Q
system should be even more interesting to researchers and application
developers who want to explore this revolutionary new approach to
•In benchmark tests, D-Wave QPUs outperformed competitive classical algorithms by 1000 to 10000 times in pure computation time. For these tests, D-Wave developed efficient CPU- and GPU-based implementations of highly specialized algorithms that are recognized as the stiffest competition to D-Wave QPUs, and ran them on the latest-generation classical computer servers. These benchmark problems in sampling and optimization were created to represent the structure of common real-world problems, while maximizing the size of the problem that could fit on the 2000-qubit QPU. The benchmark comparisons were relative to single CPU cores and 2500-core GPUs at the largest problem size.
•The D-Wave 2000Q system outperformed the GPU-based implementations by 100 times in equivalent problem solving performance per watt. Power efficiency is a serious and growing issue in large-scale computing. The power draw of D-Wave’s systems has remained constant in successive generations, and is expected to continue to do so while the computational power increases dramatically. As a result, the computational power per watt is expected to increase much more rapidly for D-Wave QPUs than for classical systems.
•The new anneal offsets feature provided a remarkable improvement over
baseline performance in a small-scale demonstration of integer
factoring, in some cases making the computation more than 1000 times
faster than when the problem was run without this feature.