Dwave CTO Geordie Rose had talked about a recent paper about whether or not Dwave was using quantum effects for its superconducting processor.
Geordie has discussed in the comments the advantages of their superconducting system and that more benchmarking is under way.
The original motivation for building superconducting processors had nothing to do with quantum computation. There were two factors.
1) Superconducting device timescales are shorter than semiconductor devices. Clocked superconducting digital circuits have been run at around 700GHz and it’s entirely feasible that you could build a complex ASIC type processor clocked at say 100GHz. For certain types of problems that type of advantage is significant.
2) You can operate superconducting chips using tiny fractions of the power that semiconducting chips consume. Studies have been done of reasonable expectations of total all-in energy cost where the same computational load could have energy needs cut by factors of about 100, even with all of the cryogenics etc.
The architecture we’ve build has both these advantages, even if you put aside scaling advantages.
As to the choice of instance types for benchmarking — this work is underway! I expect that the groups doing this research will publish some results shortly (within a few months).
Read more »
Geordie has discussed in the comments the advantages of their superconducting system and that more benchmarking is under way.
The original motivation for building superconducting processors had nothing to do with quantum computation. There were two factors.
1) Superconducting device timescales are shorter than semiconductor devices. Clocked superconducting digital circuits have been run at around 700GHz and it’s entirely feasible that you could build a complex ASIC type processor clocked at say 100GHz. For certain types of problems that type of advantage is significant.
2) You can operate superconducting chips using tiny fractions of the power that semiconducting chips consume. Studies have been done of reasonable expectations of total all-in energy cost where the same computational load could have energy needs cut by factors of about 100, even with all of the cryogenics etc.
The architecture we’ve build has both these advantages, even if you put aside scaling advantages.
As to the choice of instance types for benchmarking — this work is underway! I expect that the groups doing this research will publish some results shortly (within a few months).
Read more »