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I think he is not wrong at all, but personally, I've been on both sides of the debate, and then I kind of formed the opinion that it's not worth debating about.

I think he is not wrong at all, but personally, I've been on both sides of the debate, and then I kind of formed the opinion that it's not worth debating about. The one thing I would strongly, strongly push for is general purpose hardware (we are kind of headed in that direction with OpenCL and CUDA, but industry-wide interest in these things is really low). Don't force me to use rasterization or raytracing (or even triangles), just give me a really powerful, flexible parallel processor...even if that means sacrificing a bit of speed. I think above all Carmack would appreciate such hardware...there was a kind of beauty in his old code you don't find any more -- you can do lots of tricks with GPUs, but overall it is a much more limited, less creative programming experience.

Peaker 14y ago
Typically limitations aid creativity, not hamper it.
- gavanwoolery 14y ago
  Limitations force you to come up with creative solutions to problems that should have been easier in the first place. :) But sometimes limitations force you to focus on the important things (if you could render absolutely anything, you could spend forever building an engine instead of a game).
  - Peaker 14y ago
    I think sometimes the creative solutions end up being better than the simple "obvious" solutions that were apparent before the limitations were put in place.
duaneb 14y ago
> just give me a really powerful, flexible parallel processor Isn't that exactly what a GPU is? They aren't terribly fantastic at traditional computation, but then again we're talking parallelism here.
- gavanwoolery 14y ago
  Yes, GPUs are becoming increasingly flexible, but they are still limited by CPU-GPU bottleneck, GPU memory (which for the most part has been limited to 2 GB per card), really poor branching performance and limited ability to modify data in any other way than 1:1 correspondence. They are first and foremost designed to pump out polygons at high fill rates, which is fine unless you want to do some untraditional rendering or computation. :) Again, CUDA and OpenCL are paving the way for a new path, but I still think we should be using general purpose silicon underneath it instead of hardware designed to to do things like MSAA, interpolation, triangle setup, etc.
  - duaneb 14y ago
    Sure, but I still believe it's far closer to the ideal parallel hardware than this n-core-shared-memory business that is really hard to program well.

Peaker 14y ago

Typically limitations aid creativity, not hamper it.

gavanwoolery 14y ago
Limitations force you to come up with creative solutions to problems that should have been easier in the first place. :) But sometimes limitations force you to focus on the important things (if you could render absolutely anything, you could spend forever building an engine instead of a game).
- Peaker 14y ago
  I think sometimes the creative solutions end up being better than the simple "obvious" solutions that were apparent before the limitations were put in place.

duaneb 14y ago

> just give me a really powerful, flexible parallel processor Isn't that exactly what a GPU is? They aren't terribly fantastic at traditional computation, but then again we're talking parallelism here.

gavanwoolery 14y ago
Yes, GPUs are becoming increasingly flexible, but they are still limited by CPU-GPU bottleneck, GPU memory (which for the most part has been limited to 2 GB per card), really poor branching performance and limited ability to modify data in any other way than 1:1 correspondence. They are first and foremost designed to pump out polygons at high fill rates, which is fine unless you want to do some untraditional rendering or computation. :) Again, CUDA and OpenCL are paving the way for a new path, but I still think we should be using general purpose silicon underneath it instead of hardware designed to to do things like MSAA, interpolation, triangle setup, etc.
- duaneb 14y ago
  Sure, but I still believe it's far closer to the ideal parallel hardware than this n-core-shared-memory business that is really hard to program well.