AMD Zen 2 Microarchitecture Analysis: Ryzen 3000 and EPYC Rome
by Dr. Ian Cutress on June 10, 2019 7:22 PM EST- Posted in
- CPUs
- AMD
- Ryzen
- EPYC
- Infinity Fabric
- PCIe 4.0
- Zen 2
- Rome
- Ryzen 3000
- Ryzen 3rd Gen
Fetch/Prefetch
Starting with the front end of the processor, the prefetchers.
AMD’s primary advertised improvement here is the use of a TAGE predictor, although it is only used for non-L1 fetches. This might not sound too impressive: AMD is still using a hashed perceptron prefetch engine for L1 fetches, which is going to be as many fetches as possible, but the TAGE L2 branch predictor uses additional tagging to enable longer branch histories for better prediction pathways. This becomes more important for the L2 prefetches and beyond, with the hashed perceptron preferred for short prefetches in the L1 based on power.
In the front end we also get larger BTBs, to help keep track of instruction branches and cache requests. The L1 BTB has doubled in size from 256 entry to 512 entry, and the L2 is almost doubled to 7K from 4K. The L0 BTB stays at 16 entries, but the Indirect target array goes up to 1K entries. Overall, these changes according to AMD affords a 30% lower mispredict rate, saving power.
One other major change is the L1 instruction cache. We noted that it is smaller for Zen 2: only 32 KB rather than 64 KB, however the associativity has doubled, from 4-way to 8-way. Given the way a cache works, these two effects ultimately don’t cancel each other out, however the 32 KB L1-I cache should be more power efficient, and experience higher utilization. The L1-I cache hasn’t just decreased in isolation – one of the benefits of reducing the size of the I-cache is that it has allowed AMD to double the size of the micro-op cache. These two structures are next to each other inside the core, and so even at 7nm we have an instance of space limitations causing a trade-off between structures within a core. AMD stated that this configuration, the smaller L1 with the larger micro-op cache, ended up being better in more of the scenarios it tested.
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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.
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.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%.
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.
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 badchada - 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.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?
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)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.)
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.