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In July 2015 AMD released a 28nm chip with more GCN compute units than this card at a lower price - the Radeon R9 Fury X had the full 64 CUs / 4096 shaders enab

by DCKing 8y ago

In July 2015 AMD released a 28nm chip with more GCN compute units than this card at a lower price - the Radeon R9 Fury X had the full 64 CUs / 4096 shaders enabled for $649. And it was considered a bit of a dud as a product. This Radeon VII is 2.5 process nodes better, but launches with 60 CUs / 3840 shaders enabled. All still on essentially the GCN architecture. And it launches at $699, more than three and a half years after the former. Yet due to sheer clock speed increases and HBM improvements (16GB, 1 TB/s, wow) they actually seem surpisingly competitive. I'm both incredibly impressed and incredibly underwhelmed.

dogma1138 8y ago
Depends on how you define competitive, in gaming which this card at least partially is aimed at its about as fast as a 1080ti a card launched 2 years ago for $700.
- CoolGuySteve 8y ago
  I'm hoping a 8gb or 12 gb version comes out for $500 or so. 16gb seems like overkill for the next couple years of game releases.
  - dogma1138 8y ago
    They can’t do 8 GB there are no 2GB HBM2 modules apparently and they can’t cut the amount of modules without cutting the CUs in half. It’s essentially just to keep up some production volume this is their HPC die sold to the consumer market its the Titan V equivalent die of AMD minus the Tensor Cores just for much much cheaper. It’s likely going to be a flop gaming wise, 2x8 pin power connectors put it at 300W TDP with performance only matching that of a 1089ti/2080 in the best case scenarios AMD currently has. The 1080ti can be had for under $600 if you can find it the 2080 is around $700 but you get RTX and DLSS which while isn’t that useful yet is going to be more useful for gaming than 16GB of memory.
    - AlphaSite 8y ago
      The 2080 isn't great perf/w either, not like the 1080 was.
  - Yizahi 8y ago
    It would all depend on next generation of consoles and their release year. I bought 3Gb card 4 years ago, when top cards from both manufacturers had 3 and 4 Gb and it was an overkill. Now it seems that 8 Gb is a normal thing (same as PS4) and at least 4 is mandatory for AAA games.
dragontamer 8y ago
Vega II is 60CUs at 1.8 GHz. AMD Fury is 64CUs at 1GHz. 60 CUs at 1.8GHz is way faster than AMD Fury ever was. Not only do you get the GHz advantage, but more L2 cache, more HBM2 Bandwidth, and architectural advancements (various instruction set improvements like double-speed FP16 support) EDIT: AMD Fury's main advantage was that 1GHz clock made all of the nanosecond-level timings super easy to understand. 10-clock cycles was 10-nano seconds. Hurrah!
philjohn 8y ago
I think it shows that GCN is reaching the end of its usable life. It's not been a bad microarchitecture - but hopefully Navi does something different so they aren't hamstrung in the same way.
- dogma1138 8y ago
  NAVI is still GCN likely the same 15-25% uptick over Polaris as we’ve seen with this new Vega, 2020-2021 is when the next gen uArch is going to come. GCN’s vector machine doesn’t scale as well as NVIDIA’s scalar architecture NVIDIA can add cores without caring about concurrency or ILP, since each core is an individually addressable scalar ALU, this is why “async” compute doesn’t benefit them as much as it does GCN cards that have a 4 wide SIMD array that is nearly as hard to feed as their old VILW arch and a massive external compute scheduler that sits idle when doing graphics.
  - atq2119 8y ago
    Your comment is extremely confused. Let's unpack some of the confusion... > NVIDIA’s scalar architecture NVidia doesn't have a scalar architecture in any meaningful sense of the word. Individual work items execute in warps, meaning (up to) 32 items execute the same instruction, at the same PC. If you have divergence, i.e. fewer than 32 items at the same instruction, you lose ALU throughput. This is the same as in AMD (and every other GPU architecture out there, for that matter). The difference to AMD's architecture since Volta is that there is hardware support for each SIMD lane having its own PC, which makes it easier to have independent forward progress and a bunch of other features. The separate lanes don't have separate instruction fetch, though -- they all execute the same instruction (and if they can't, then some lanes will be disabled). > this is why “async” compute doesn’t benefit them as much as it does GCN cards Nvidia literally cannot do async compute in the same way as AMD, because their micro-architecture cannot switch between graphics and compute on as finely grained a basis as GCN cards. That's why they don't benefit from async compute. (Though I'm not sure whether that's still true since Volta.) > GCN cards that have a 4 wide SIMD array GCN has 64-wide waves, though with a bit of a weird execution scheduling which means that 16 lanes out of the 64 are computing at a time. Nowhere in GCN are there any 4-wide SIMD arrays. > a massive external compute scheduler that sits idle when doing graphics. Also nonsense. Both AMD and Nvidia have the majority of die space allocated to the compute cores (whatever they're calling them). The pieces of fixed function logic that distribute work onto the cores (whether for graphics or compute) are comparatively tiny.

by DCKing 8y ago

dogma1138 8y ago

Depends on how you define competitive, in gaming which this card at least partially is aimed at its about as fast as a 1080ti a card launched 2 years ago for $700.

CoolGuySteve 8y ago
I'm hoping a 8gb or 12 gb version comes out for $500 or so. 16gb seems like overkill for the next couple years of game releases.
- dogma1138 8y ago
  They can’t do 8 GB there are no 2GB HBM2 modules apparently and they can’t cut the amount of modules without cutting the CUs in half. It’s essentially just to keep up some production volume this is their HPC die sold to the consumer market its the Titan V equivalent die of AMD minus the Tensor Cores just for much much cheaper. It’s likely going to be a flop gaming wise, 2x8 pin power connectors put it at 300W TDP with performance only matching that of a 1089ti/2080 in the best case scenarios AMD currently has. The 1080ti can be had for under $600 if you can find it the 2080 is around $700 but you get RTX and DLSS which while isn’t that useful yet is going to be more useful for gaming than 16GB of memory.
  - AlphaSite 8y ago
    The 2080 isn't great perf/w either, not like the 1080 was.
- Yizahi 8y ago
  It would all depend on next generation of consoles and their release year. I bought 3Gb card 4 years ago, when top cards from both manufacturers had 3 and 4 Gb and it was an overkill. Now it seems that 8 Gb is a normal thing (same as PS4) and at least 4 is mandatory for AAA games.

dragontamer 8y ago

Vega II is 60CUs at 1.8 GHz. AMD Fury is 64CUs at 1GHz. 60 CUs at 1.8GHz is way faster than AMD Fury ever was. Not only do you get the GHz advantage, but more L2 cache, more HBM2 Bandwidth, and architectural advancements (various instruction set improvements like double-speed FP16 support) EDIT: AMD Fury's main advantage was that 1GHz clock made all of the nanosecond-level timings super easy to understand. 10-clock cycles was 10-nano seconds. Hurrah!

philjohn 8y ago

I think it shows that GCN is reaching the end of its usable life. It's not been a bad microarchitecture - but hopefully Navi does something different so they aren't hamstrung in the same way.

dogma1138 8y ago
NAVI is still GCN likely the same 15-25% uptick over Polaris as we’ve seen with this new Vega, 2020-2021 is when the next gen uArch is going to come. GCN’s vector machine doesn’t scale as well as NVIDIA’s scalar architecture NVIDIA can add cores without caring about concurrency or ILP, since each core is an individually addressable scalar ALU, this is why “async” compute doesn’t benefit them as much as it does GCN cards that have a 4 wide SIMD array that is nearly as hard to feed as their old VILW arch and a massive external compute scheduler that sits idle when doing graphics.
- atq2119 8y ago
  Your comment is extremely confused. Let's unpack some of the confusion... > NVIDIA’s scalar architecture NVidia doesn't have a scalar architecture in any meaningful sense of the word. Individual work items execute in warps, meaning (up to) 32 items execute the same instruction, at the same PC. If you have divergence, i.e. fewer than 32 items at the same instruction, you lose ALU throughput. This is the same as in AMD (and every other GPU architecture out there, for that matter). The difference to AMD's architecture since Volta is that there is hardware support for each SIMD lane having its own PC, which makes it easier to have independent forward progress and a bunch of other features. The separate lanes don't have separate instruction fetch, though -- they all execute the same instruction (and if they can't, then some lanes will be disabled). > this is why “async” compute doesn’t benefit them as much as it does GCN cards Nvidia literally cannot do async compute in the same way as AMD, because their micro-architecture cannot switch between graphics and compute on as finely grained a basis as GCN cards. That's why they don't benefit from async compute. (Though I'm not sure whether that's still true since Volta.) > GCN cards that have a 4 wide SIMD array GCN has 64-wide waves, though with a bit of a weird execution scheduling which means that 16 lanes out of the 64 are computing at a time. Nowhere in GCN are there any 4-wide SIMD arrays. > a massive external compute scheduler that sits idle when doing graphics. Also nonsense. Both AMD and Nvidia have the majority of die space allocated to the compute cores (whatever they're calling them). The pieces of fixed function logic that distribute work onto the cores (whether for graphics or compute) are comparatively tiny.