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This graph shows transistors basically maintaining pace and completely disregards multi-core performance. Of course single core perf will rise more slowly when

This graph shows transistors basically maintaining pace and completely disregards multi-core performance. Of course single core perf will rise more slowly when a chip now has 8-64x as many cores.

StillBored 4y ago
Which is great if you have a traditional server application servicing a lot of independent requests, or giant linear equations that can be solved in parallel. OTOH, the graph has an amadal's law section, which for many tasks is pretty out of steam (aka desktop web browsing/javascript JIT/etc). I'm not going to be so stupid as to say 8 cores should be enough for anyone (while attached to a machine with 128) but you have to wonder if the stable diffusion style apps running on your desktop are going to be mainstream, or isolated to the few who choose to _need_ them as a hobby or a smaller part of the public that uses them for commercial success. AKA, I can utilize just about every core i'm given with parallel compiles, or rendering a 4K video, but I'm pretty sure i'm the only one in my immediate family that needs that. My wife in the past might have done some simulation work, but these days the heaviest thing she runs on her PC is office products. This really gets back at the Arm big.little thing, where you really want 99% of your application usage to run on the big cores. The little cores only exist for background/latency insensitive tasks, and the odd case where the problem actually can utilize a large number of parallel cores and needs to maximize efficiency in the power envelope to maximize computation. AKA throw a lot of lower power transistors at the people rendering video/etc, and leave them powered off most of the time. AKA, put another way, the common use case is a few big powerful cores for normal use, playing games, whatever with one or two high efficiency processors for everything else and a pile of dark silicon for the rare application that actually can utilize dozens of cores because its trivial to parallelize and doesn't work better being offloaded to a GPU. I suspect long term intel was probably right with larrabee, they were just a decade or two early. So, economically I don't see people buying machines with a couple hundred cores that sit dark most of the time. Which will drive the price up even more, and make them less popular.
- eru 4y ago
  > I'm not going to be so stupid as to say 8 cores should be enough for anyone (while attached to a machine with 128) but you have to wonder if the stable diffusion style apps running on your desktop are going to be mainstream, or isolated to the few who choose to _need_ them as a hobby or a smaller part of the public that uses them for commercial success. AKA, I can utilize just about every core i'm given with parallel compiles, or rendering a 4K video, but I'm pretty sure i'm the only one in my immediate family that needs that. My wife in the past might have done some simulation work, but these days the heaviest thing she runs on her PC is office products. See GAN Theft Auto at https://www.youtube.com/watch?v=udPY5rQVoW0 https://www.youtube.com/watch?v=udPY5rQVoW0 Someone trained a neural network to convert controller input into video output that simulates the game Grand Theft Auto. If technology keeps improving, I expect many future games will be such 'dreams' of neural networks. You are right that running Word or Excel won't really benefit from more cores.
ummonk 4y ago
How does it disregard multi-core performance? As you said, it's showing the transistor counts going up, and it's also showing the rise in the number of logical cores.
- Rufbdbskrufb473 4y ago
  The missing thing that's critical for most multi-core performance use cases is memory bandwidth. Maybe not easy to summarize on a graph like this, but for any workload that can't fit within L1 cache, you're unlikely to get close to linear performance scaling with cores. Sometimes a single core can fully saturate the available memory bandwidth.
deleted 4y ago
[deleted]
mrandish 4y ago
> This graph shows transistors basically maintaining pace... I'm no expert in silicon scaling but from reading technical papers, my (naive) understanding is that transistor density has almost kept up but now that scaling comes with increasingly stringent design constraints which architects must make trade-offs over. Broadly speaking, things like "You can have 2x last gen's density but they can't all be fully powered on for very long." That's a greatly simplified example but much of what I've seen has been far "thornier" in terms of interacting constraints along multiple dimensions. My sense is that in the 90s we usually got "denser, faster AND cheaper" with every generation. Now we're lucky to get one and even that comes with implementation requirements which can be increasingly arcane. My understanding is that different fabs are having to roll more of their own design libraries which embody their chosen sets of trade-offs per node. In addition to limiting overall performance and being harder to design, this apparently makes reusing or migrating designs more challenging. While certain headline metrics like node density may appear to be scaling as usual. The reality under the hood is more complex and far less rosy.
- Dylan16807 4y ago
  > My sense is that in the 90s we usually got "denser, faster AND cheaper" with every generation. Now we're lucky to get one You can still get all three, though you can only pick "cheaper" so many times before you fall off the mainstream product stack. Two generations ago in 2019, the 3700X launched at $329. This generation, the 7600X launched at $299. The 7600X has fewer cores, but they're about 50% faster individually and 25% faster total. And it's N5 instead of N7.
  - sitkack 4y ago
    You made me think that maybe computing is a deflationary force (I am not a libertarian, this isn't some free market bro idea, I think)d, the more that can be subsumed by computation, the more things that can get cheaper over time not more expensive, even if the face of rising material costs. The relative price of steel has remained flat, while the steel performance has greatly increased. https://www.metalbulletinresearch.com/Article/3532290/Commodity-prices-A-100-year-history.html https://www.metalbulletinresearch.com/Article/3532290/Commod... Between material science and cheaper compute, we can build higher tech parts and techniques. The cycles/consumed/per/person/per/year is an exponential, what are some important points on that curve? When the computation to design something is on the order as the same amount of energy to create it? This interesting, https://www.in2013dollars.com/New-cars/price-inflation/1980-to-2022?amount=5000 https://www.in2013dollars.com/New-cars/price-inflation/1980-... You could buy a Honda Civic new in 1980 for 5000$, that would only be just under 10k in todays dollars. What 1980 Honda Civic quality car can you buy today for 10k? Or am I a being nostalgic. And look at the bump in inflation during the recession, https://blog.cheapism.com/average-car-price-by-year/#slide=67 https://blog.cheapism.com/average-car-price-by-year/#slide=6... of car prices. Was the 2008 recession triggered by excessively inflated car prices? Like causing a bubble in a pipeline, an economic embolism. Current average price has dropped 10k$ from 35k to 25k in the years since 2008.
therealcamino 4y ago
Cause and effect is backwards there. Designers only went to multicore because single core performance improvement was leveling off. It's not that people wanted multicore systems and were willing to sacrifice single core performance to get it.
- ReptileMan 4y ago
  Well we wanted multicore, but it was mostly because windows loved to become irresponsive on single core. I think that from consumer point 2 cored circa 2006 were enough. 4 is probably the absolute maximum.

This graph shows transistors basically maintaining pace and completely disregards multi-core performance. Of course single core perf will rise more slowly when a chip now has 8-64x as many cores.

StillBored 4y ago

Which is great if you have a traditional server application servicing a lot of independent requests, or giant linear equations that can be solved in parallel. OTOH, the graph has an amadal's law section, which for many tasks is pretty out of steam (aka desktop web browsing/javascript JIT/etc). I'm not going to be so stupid as to say 8 cores should be enough for anyone (while attached to a machine with 128) but you have to wonder if the stable diffusion style apps running on your desktop are going to be mainstream, or isolated to the few who choose to _need_ them as a hobby or a smaller part of the public that uses them for commercial success. AKA, I can utilize just about every core i'm given with parallel compiles, or rendering a 4K video, but I'm pretty sure i'm the only one in my immediate family that needs that. My wife in the past might have done some simulation work, but these days the heaviest thing she runs on her PC is office products. This really gets back at the Arm big.little thing, where you really want 99% of your application usage to run on the big cores. The little cores only exist for background/latency insensitive tasks, and the odd case where the problem actually can utilize a large number of parallel cores and needs to maximize efficiency in the power envelope to maximize computation. AKA throw a lot of lower power transistors at the people rendering video/etc, and leave them powered off most of the time. AKA, put another way, the common use case is a few big powerful cores for normal use, playing games, whatever with one or two high efficiency processors for everything else and a pile of dark silicon for the rare application that actually can utilize dozens of cores because its trivial to parallelize and doesn't work better being offloaded to a GPU. I suspect long term intel was probably right with larrabee, they were just a decade or two early. So, economically I don't see people buying machines with a couple hundred cores that sit dark most of the time. Which will drive the price up even more, and make them less popular.

eru 4y ago
> I'm not going to be so stupid as to say 8 cores should be enough for anyone (while attached to a machine with 128) but you have to wonder if the stable diffusion style apps running on your desktop are going to be mainstream, or isolated to the few who choose to _need_ them as a hobby or a smaller part of the public that uses them for commercial success. AKA, I can utilize just about every core i'm given with parallel compiles, or rendering a 4K video, but I'm pretty sure i'm the only one in my immediate family that needs that. My wife in the past might have done some simulation work, but these days the heaviest thing she runs on her PC is office products. See GAN Theft Auto at https://www.youtube.com/watch?v=udPY5rQVoW0 https://www.youtube.com/watch?v=udPY5rQVoW0 Someone trained a neural network to convert controller input into video output that simulates the game Grand Theft Auto. If technology keeps improving, I expect many future games will be such 'dreams' of neural networks. You are right that running Word or Excel won't really benefit from more cores.

ummonk 4y ago

How does it disregard multi-core performance? As you said, it's showing the transistor counts going up, and it's also showing the rise in the number of logical cores.

Rufbdbskrufb473 4y ago
The missing thing that's critical for most multi-core performance use cases is memory bandwidth. Maybe not easy to summarize on a graph like this, but for any workload that can't fit within L1 cache, you're unlikely to get close to linear performance scaling with cores. Sometimes a single core can fully saturate the available memory bandwidth.

deleted 4y ago

[deleted]

mrandish 4y ago

> This graph shows transistors basically maintaining pace... I'm no expert in silicon scaling but from reading technical papers, my (naive) understanding is that transistor density has almost kept up but now that scaling comes with increasingly stringent design constraints which architects must make trade-offs over. Broadly speaking, things like "You can have 2x last gen's density but they can't all be fully powered on for very long." That's a greatly simplified example but much of what I've seen has been far "thornier" in terms of interacting constraints along multiple dimensions. My sense is that in the 90s we usually got "denser, faster AND cheaper" with every generation. Now we're lucky to get one and even that comes with implementation requirements which can be increasingly arcane. My understanding is that different fabs are having to roll more of their own design libraries which embody their chosen sets of trade-offs per node. In addition to limiting overall performance and being harder to design, this apparently makes reusing or migrating designs more challenging. While certain headline metrics like node density may appear to be scaling as usual. The reality under the hood is more complex and far less rosy.

Dylan16807 4y ago
> My sense is that in the 90s we usually got "denser, faster AND cheaper" with every generation. Now we're lucky to get one You can still get all three, though you can only pick "cheaper" so many times before you fall off the mainstream product stack. Two generations ago in 2019, the 3700X launched at $329. This generation, the 7600X launched at $299. The 7600X has fewer cores, but they're about 50% faster individually and 25% faster total. And it's N5 instead of N7.
- sitkack 4y ago
  You made me think that maybe computing is a deflationary force (I am not a libertarian, this isn't some free market bro idea, I think)d, the more that can be subsumed by computation, the more things that can get cheaper over time not more expensive, even if the face of rising material costs. The relative price of steel has remained flat, while the steel performance has greatly increased. https://www.metalbulletinresearch.com/Article/3532290/Commodity-prices-A-100-year-history.html https://www.metalbulletinresearch.com/Article/3532290/Commod... Between material science and cheaper compute, we can build higher tech parts and techniques. The cycles/consumed/per/person/per/year is an exponential, what are some important points on that curve? When the computation to design something is on the order as the same amount of energy to create it? This interesting, https://www.in2013dollars.com/New-cars/price-inflation/1980-to-2022?amount=5000 https://www.in2013dollars.com/New-cars/price-inflation/1980-... You could buy a Honda Civic new in 1980 for 5000$, that would only be just under 10k in todays dollars. What 1980 Honda Civic quality car can you buy today for 10k? Or am I a being nostalgic. And look at the bump in inflation during the recession, https://blog.cheapism.com/average-car-price-by-year/#slide=67 https://blog.cheapism.com/average-car-price-by-year/#slide=6... of car prices. Was the 2008 recession triggered by excessively inflated car prices? Like causing a bubble in a pipeline, an economic embolism. Current average price has dropped 10k$ from 35k to 25k in the years since 2008.

therealcamino 4y ago

Cause and effect is backwards there. Designers only went to multicore because single core performance improvement was leveling off. It's not that people wanted multicore systems and were willing to sacrifice single core performance to get it.

ReptileMan 4y ago
Well we wanted multicore, but it was mostly because windows loved to become irresponsive on single core. I think that from consumer point 2 cored circa 2006 were enough. 4 is probably the absolute maximum.