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D-Wave's 2,000-Qubit Quantum Annealing Computer Now 1,000x Faster Than Previous Generation (tomshardware.com)
An anonymous reader quotes a report from Tom's Hardware: D-Wave, a Canadian company developing the first commercial "quantum computer," announced its next-generation quantum annealing computer with 2,000 qubits, which is twice as many as its previous generation had. One highly exciting aspect of quantum computers of all types is that beyond the seemingly Moore's Law-like increase in number of qubits every two years, their performance increases much more than just 2x, unlike with regular microprocessors. This is because qubits can hold a value of 0, 1, or a superposition of the two, making quantum systems able to deal with much more complex information. If D-Wave's 2,000-qubit computer is now 1,000 faster than the previous 1,000-qubit generation (D-Wave 2X), that would mean that, for the things Google tested last year, it should now be 100 billion times faster than a single-core CPU. The new generation also comes with control features, which allows users to modify how D-Wave's quantum system works to better optimize their solutions. These control features include the following capabilities: The ability to tune the rate of annealing of individual qubits to enhance application performance; The ability to sample the state of the quantum computer during the quantum annealing process to power hybrid quantum-classical machine learning algorithms that were not previously possible; The ability to combine quantum processing with classical processing to improve the quality of both optimization and sampling results returned from the system. D-Wave's CEO, Vern Brownell, also said that D-Wave's quantum computers could also be used for machine learning task in ways that wouldn't be possible on classical computers. The company is also training the first generation of programmers to develop applications for D-Wave quantum systems. Last year, Google said that D-Wave's 1,000 qubit computer proved to be 100 million times faster than a classical computer with a single core: "We found that for problem instances involving nearly 1,000 binary variables, quantum annealing significantly outperforms its classical counterpart, simulated annealing. It is more than 10^8 times faster than simulated annealing running on a single core," said Hartmut Neven, Google's Director of Engineering.
Nothing you cannot do much better and much faster on a much cheaper conventional computer.
Most ACs are not even worth the keystrokes to insult them. Be generically insulted by this and ignored otherwise.
Can you provide links?
Seriously, I (and I suspect many others) have a decent idea of the *concept* of quantum computers, but understanding actual application is... elusive.
whois gawk date unzip strip find touch finger mount join nice man top fsck grep eject more yes exit umount sleep dump
First these fucks said d-wave wasnt doing any quantum stuff. Then these fucks said it was slower than conventional hardware. Now these fucks say its still slower than conventional hardware if you use a different algorithms that wont solve the same set of problems...
This is not accurate. The first statement is that it wasn't clear that the D-Wave system was engaging in any quantum computation. That's still not clear. Part of the issue here is that it simply isn't completely clear what one means by quantum computation in this context. For example, your laptop's transistors use quantum mechanics in a critical fashion, but they aren't doing quantum computations. The question has always been twofold a) is non-trivial entanglement going on and b) is that entanglement being used to do processing that cannot be easily simulated on a classical system. Those are both strongly connected to questions of efficiency. Right now, the answer to a seems to be yes (although it took forever for the evidence to actually come out).
Your second two sentences are even more wrong. The fact is that it is slower than cheap conventional hardward if one *uses the best known classical algorithms*. That's being used to solve the same problems, as would be clear, if you read the link I gave.
Your insistence that one must use the "the same algorithms" to benchmark is also incredibly wrong in this context, since one cannot use the same algorithms on both at a fundamental level. D-Wave's system uses a variant of an annealing algorithm and cannot run classical algorithms in any meaningful way. In that context, the classical computers are in this sense essentially emulating an annealing process. If you insist that one must use the same algorithms rather than look actual time for solving problems, then the systems are simply incomparable. Actually looking at cost and time to solve problems makes more sense.
As someone else noted.. Google, NASA, etc must be complete idiots for not bowing to the clearly rational flying goalpost these fucks swing around.
Let's recall for a moment that the primary "fuck" you are talking about is Scott Aaronson who is one of the world's most respected quantum computing experts. He's responsible for many major results including the algebraization barrier http://www.scottaaronson.com/papers/alg.pdf and the first substantially non-trivial lower bounds on the basic collision problem http://www.scottaaronson.com/papers/collision.pdf among other work.
But let's for a moment think about what is going on with Google and NASA and consider other explanations that are relevant here. First, both Google and NASA both have major interests in basic research, and there's a valid basic research interest in what D-Wave is pursuing. (I personally consider it unlikely to go anywhere that useful compared to gate-based quantum computing research but that's a judgment call.) Moreover, large corporations and governments like fads: it doesn't take much for some mid-level manager to decide that quantum computing is a shining new thing and realize that the easiest way to jump on the bandwagon is to buy a D-Wave machine.
Aaaaand, fail. You do not compare the same algorithms if the computing devices have fundamentally different characteristics. For example, you do not compare a single CPU computer and a large cluster using the same algorithm. You compare them using algorithms that deliver the same results, but one gets a classical algorithm and the other gets a parallelized one. That is actually benchmarking 101.
Because if you insist in the same algorithm, you will find that one device has to simulate the other in order to be even able ti run that algorithm. That is not a relevant comparison in any way. May as well compare the speed of an airplane and a bicycle and require the bicycle to fly for that. Stupid.
Most ACs are not even worth the keystrokes to insult them. Be generically insulted by this and ignored otherwise.
Gee, you use lots of foul language. You must be right.
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