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Comment by Andys | Hacker News Reader

Nice try, Nvidia. This article is some fact and the rest FUD.

  "If you currently have access to MIC chips and have been testing
  real applications, I would love to hear from you"

The information that was used to judge Intel's solution was based only on press releases and not any practical working knowledge.

  "We can no longer reduce voltage in proportion to transistor size"

The "we" here refers to Nvidia, and not Intel, because Nvidia uses TSMC to fab their GPU chips.

  "there is no such thing as a “magic” compiler that will
  automatically parallelize your code"

That is funny because Nvidia's newest GPU design offloads scheduling decisions on to the compiler instead of handling it dynamically on-core.

So perhaps Nvidia is warming up the FUD machines because of their newest range of GPUs which focus on gaming at the expense of computing.

eg. the Double Precision FLOP/s is now less than 10% of the Single Precision FLOP/s performance

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Your reply contains some weird non-sequiters. Nvidia is right on target when they say there is no "magic" autoparallelizing compiler. The autoparallelization they talk about, and the scheduling issues you talk about, are completely unrelated except that they both contain the word "compiler" :/

As for double-precision performance, it is also well known that the GTX 680 is only for consumers. The HPC version of Kepler is due later this year and I will not be surprised to see it offer much improve double precision performance compared to current Teslas. Intel MIC is not a consumer product, so it is unfair to compare it to consumer products like GTX 680.

The compiler comment is pretty strange for a company that is (or was) aggressively Pushing OpenACC [1].

[1] http://www.nvidia.com/object/openacc-gpu-directives.html

For GTX 680 the double precision is actually 1/24 of the single precision so it is closer to 4%. Pretty sad when comparing the performance to similar priced Radeon cards.

This is a silicon surface area trade off between gaming and number crunching. It's a decision, not a flaw.

It not a trade-off. Consumer and HPC GPUs are using the exact same silicon... Nvidia artificially cripples, in software/firmware, the double precision performance of consumer GPUs: http://forums.nvidia.com/index.php?showtopic=204025

Artificial crippling is a bad practice, which I dislike. However, note that the GPU mentioned in your link is a low-end device.

Sometimes (I don't know about this case) the low end CPU's and GPU's are chips that have manufacturing errors in them and don't pass full quality control checks. The defective parts of the chip are then disabled with microcode (or equivalent) and sold as low-end chips. That's a good practice, a lot better than simply throwing the slightly defective chips to waste.

Even the high end consumer GPUs are crippled. For example the GTX 580 is identical to the Tesla M2090 (both 512 shaders, same GF110 chip), but the first has only a fraction of the DP performance of the second. What I am telling you is a pretty well-known fact...

All of you who want inexpensive DP performance should look at AMD Radeon cards. AMD does not cripple any of its GPUs.

Yes, they have disabled parts because NVidia was having serious yield issues that generation and didn't have enough perfect chips to make a product line from them. If you want to be an AMD partisan, just say that NVidia cripples their cards because their silicon engineers aren't good enough to get acceptable chip yields without doing so.

No, they did not disable it because of yield issues... The double precision logic is there, on the consumer GTX line, not disabled. Nvidia just limits the rate of DP instructions per clock for merely differentiating it from the enterprise Tesla line. Even Nvidia admits doing so.

I hate that, but I guess it makes sense from a business perspective.

Oh, I thought you were talking about the fused off shader groups. Yeah, you're totally right about the DP stuff.

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