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This is great progress, and the inevitable way we're going to head for compute heavy workloads. Once the ability to program the GPU side really becomes commonpl
by fidotron 13y ago
This is great progress, and the inevitable way we're going to head for compute heavy workloads. Once the ability to program the GPU side really becomes commonplace then the CPU starts to look a lot less important and more like a co-ordinator.
The question is, what are those compute bound workloads? I'm not persuaded that there are too many of them anymore, and the real bottleneck for some time with most problems has been I/O. This even extends to GPUs where fast memory makes a huge difference.
Lack of bandwidth has ended up being the limiting factor for every program I've written in the last 5 years, so my hope is while this is great for compute now the programming models it encourages us to adopt can help us work out the bandwidth problem further down the road.
Still, this is definitely the most exciting time in computing since the mid 80s.
- weland 13y ago> The question is, what are those compute bound workloads? I'm not persuaded that there are too many of them anymore, and the real bottleneck for some time with most problems has been I/O. This even extends to GPUs where fast memory makes a huge difference. The bottlenecks in the problems themselves shouldn't be underestimated though. Some types of problems are intrinsically difficult or outright impossible to reformulate so as to take advantage of vectorized processing. That being said, there are a lot of other problems which do. I'm quite enthusiastic about this.