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7nm AMD EPYC "Rome" CPU w/ 64C/128T to Cost $8K (56 Core Intel Xeon: $25K-50K)
Yesterday, we shared the core and thread counts of AMD's Zen 2 based Epyc lineup, with the lowest-end chip going as low as 8 cores while the top-end 7742 boasting 64 and double the threads. Today, the prices of these server parts have also surfaced, and it seems like they are going to be quite a bit cheaper than the competing Intel Xeon Platinum processors.
The top-end Epyc 7742 with a TDP of 225W (128 threads @ 3.4GHz) is said to sell for a bit less than $8K, while the lower clocked 7702 and 7702P (single-socket) are going to cost $7,215 and $4,955 (just) respectively. That's quite impressive, you're getting 64 Zen 2 cores for just $5,000, while on the other hand Intel's 28-core Xeon Platinum 8280 costs a whopping $18K and is half as powerful.
(Score: 0) by Anonymous Coward on Monday June 24 2019, @08:16AM (2 children)
Quantum supremacy isn't all that supreme.
The thing about quantum computers is that they don't actually solve that many problems. Everyone knows about factorization, but that mostly causes more real-world problems than it solves. I think much of the research into quantum computing has been driven by the need to make sure that nobody invents them in secret, so they can decrypt everyone's communications. But everyone will have switched to quantum-proof cryptography before that happens. So this ability is not very important.
Mainly, the thing they would be useful for is simulation of quantum systems. It might be that the main thing we get out of quantum computers is... much better regular computers. And for that, you don't need an actual quantum computer on your desk to get the benefits from them.
(Score: 2) by takyon on Monday June 24 2019, @10:37AM (1 child)
I thought the same exact thing, but:
https://en.wikipedia.org/wiki/Quantum_algorithm [wikipedia.org]
With the caveat that this would not apply to an annealer like D-Wave.
If quantum computers running classical code turns out to be slow and impractical, I think you could still see applications for quantum computing on home computers, such as simulating real world systems within open world video games, or machine learning. If a quantum computer can be done near room temperature, without significant cooling, you could see it integrated onto a smartphone SoC or as an add-on card for desktops. Make it available, and people will figure out what to do with it.
[SIG] 10/28/2017: Soylent Upgrade v14 [soylentnews.org]
(Score: 2) by bzipitidoo on Monday June 24 2019, @12:56PM
Not to be facetious, but there's a lot of uncertainty around quantum computing. We don't even have a firm grasp of just what problems they can solve quickly that classical computers cannot, and we won't, until the famous question of whether P!=NP is solved. Most people strongly suspect that P!=NP, but if somehow it should turn out the opposite, that P=NP, then quantum computing may be of no value. So far, it is thought that BQP, the problems that a quantum computer can solve within a bounded amount of error in polynomial time, lies somewhere between P and NP, that is, that P is a subset of BQP, which is a subset of NP.
In the efforts to move closer to solving whether P!=NP, researchers have come up with an awful lot of problem classifications. Fro instance, there's RP, the set of problems that can be solved in polynomial time with a randomized algorithm. RP is also somewhere between P and NP. RP might be equal to P. Whether it contains BQP or BQP contains it, or neither, is not known. Primality testing was known to be in RP, until recently when someone discovered a deterministic way to test for primality, placing that problem firmly in P.