Floating Point

The key highlight improvement for floating point performance is full AVX2 support. AMD has increased the execution unit width from 128-bit to 256-bit, allowing for single-cycle AVX2 calculations, rather than cracking the calculation into two instructions and two cycles. This is enhanced by giving 256-bit loads and stores, so the FMA units can be continuously fed. AMD states that due to its energy aware scheduling, there is no predefined frequency drop when using AVX2 instructions (however frequency may be reduced dependent on temperature and voltage requirements, but that’s automatic regardless of instructions used)

In the floating point unit, the queues accept up to four micro-ops per cycle from the dispatch unit which feed into a 160-entry physical register file. This moves into four execution units, which can be fed with 256b data in the load and store mechanism.

Other tweaks have been made to the FMA units than beyond doubling the size – AMD states that they have increased raw performance in memory allocations, for repetitive physics calculations, and certain audio processing techniques.

Another key update is decreasing the FP multiplication latency from 4 cycles to 3 cycles. That is quite a significant improvement. AMD has stated that it is keeping a lot of the detail under wraps, as it wants to present it at Hot Chips is August. We’ll be running a full instruction analysis for our reviews on July 7th.

Decode Integer Units, Load and Store
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  • nandnandnand - Tuesday, June 11, 2019 - link

    Shouldn't we be looking at highest transistors per square millimeter plotted over time? The Wikipedia article helpfully includes die area for most of the processors, but the graph near the top just plots number of transistors without regard to die size. If Intel's Xe hype is accurate, they will be putting out massive GPUs (1600 mm^2?) made of multiple connected dies, and AMD already does something similar with CPU chiplets.

    I know that the original Moore's law did not take into account die size, multi chip modules, etc. but to ignore that seems cheaty now. Regardless, performance is what really matters. Hopefully we see tight integration of CPU and L4 DRAM cache boosting performance within the next 2-3 years.
    Reply
  • Wilco1 - Wednesday, June 12, 2019 - link

    Moore's law is about transistors on a single integrated chip. But yes density matters too, especially actual density achieved in real chips (rather than marketing slides). TSMC 7nm does 80-90 million transistors/mm^2 for A12X, Kirin 980, Snapdragon 8cx. Intel is still stuck at ~16 million transistors/mm^2. Reply
  • FunBunny2 - Wednesday, June 12, 2019 - link

    enough about Moore, unless you can get it right. Moore said nothing about transistors. He said that compute capability was doubling about every second year. This is what he actually wrote:

    "The complexity for minimum component costs has increased at a rate of roughly a factor of two per year. Certainly over the short term this rate can be expected to continue, if not to increase. Over the longer term, the rate of increase is a bit more uncertain, although there is no reason to believe it will not remain nearly constant for at least 10 years. "

    [the wiki]

    the main reason the Law has slowed is just physics: Xnm is little more (teehee) than propaganda for some years, at least since the end of agreed dimensions of what a 'transistor' was. couple that with the coalescing of the maths around 'the best' compute algorithms; complexity has run into the limiting factor of the maths. you can see it in these comments: gimme more ST, I don't care about cores. and so on. Mother Nature's Laws are fixed and immutable; we just don't know all of them at any given moment, but we're getting closer. in the old days, we had the saying 'doing the easy 80%'. we're well into the tough 20%.
    Reply
  • extide - Monday, June 17, 2019 - link

    "The complexity for minimum component costs..."

    He was directly referring to transistor count with the word "complexity" in your quote -- so yes he was literally talking about transistor count.
    Reply
  • crazy_crank - Tuesday, June 11, 2019 - link

    Actually the number of cores doesn't matter AFAIK, as Moores Law originally only was about transistor density, so all you need to compare is transistors per square millimeter. Looked at it like this, it actually doesn't even look that bad Reply
  • chada - Wednesday, June 12, 2019 - link

    Moore's law specifically talks about density doubling. If they can fit 6 cores into the same footprint, you can absolutely consider 6 cores for a density comparison. That being said, we have been off this pace for a while. Reply
  • III-V - Wednesday, June 12, 2019 - link

    >Moore's law specifically talks about density doubling.

    No it doesn't.

    Jesus Christ, why is Moore's Law so fucking hard for people to understand?
    Reply
  • LordSojar - Thursday, June 13, 2019 - link

    Why it ever became known as a "law" is totally beyond me. More like Moore's Theory (and that's pushing it, as he made a LOT of suppositions about things he couldn't possibly predict, not being an expert in those areas. ie material sciences, quantum mechanics, etc) Reply
  • sing_electric - Friday, June 14, 2019 - link

    This. He wasn't describing something fundamental about the way nature works - he was looking at technological advancements in one field over a short time frame. I guess 'Moore's Observation" just didn't sound as good.

    And the reason why no one seems to get it right is that Moore wrote and said several different things about it over the years - he'd OBSERVED that the number of transistors you could get on an IC was increasing at a certain rate, and from there, that this lead to performance increases, so both the density AND performance arguments have some amount of accuracy behind them.

    And almost no one points out that it's ultimately just a function of geometry: As process decreases linearly (say, 10 units to 7 units) , you get a geometric increase in the # of transistors because you get to multiply that by two dimensions. Other benefits - like decreased power use per transistor, etc. - ultimately flow largely from that as well (or they did, before we had to start using more and more exotic materials to get shrinks to work.)
    Reply
  • FunBunny2 - Thursday, June 13, 2019 - link

    "Jesus Christ, why is Moore's Law so fucking hard for people to understand?"

    because, in this era of truthiness, simplistic is more fun than reality. Moore made his observation in 1965, at which time IC fabrication had not even reached LSI levels. IOW, the era when node size was dropping like a stone and frequency was rising like a Saturn rocket; performance increases with each new iteration of a device were obvious to even the most casual observer. just like prices in the housing market before the Great Recession, the simpleminded still think that both vectors will continue forevvvvaaahhh.
    Reply

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