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Tensor cores (e.g. SIMD matrix FMAs) are extremely useful for training. There is nothing shaky about it. I do not get why you're being so bizarrely negative ab
by endorphone 8y ago
Tensor cores (e.g. SIMD matrix FMAs) are extremely useful for training. There is nothing shaky about it.
I do not get why you're being so bizarrely negative about this card. Yes, there are an enormous number of applications, for both training and inference, where an 11GB ridiculously powerful card (both in OPS and in memory speed) can be enormously useful.
- bitL 8y agoYes, I agree, tensor cores are awesome, if your framework of choice doesn't have some rough edges you inevitably hit when you try to do advanced models on e.g. V100, but which work just fine on TPU. I think the presented Turing card is a masterpiece, just given I was hitting 11GB limit with some semantic segmentation and multi-object detection a year ago, I am obviously disappointed that this wasn't increased, and I am forced to buy RTX 5000 instead ($2300) or used K80/P40. Also, for a gaming card outside a few RTX games I doubt it will give adequate value to gamers that expected 144Hz or faster VR and similar goodies. For raytracing and as a fusion of RT and DL it's truly redefining computer graphics.
- shaklee3 8y agoTensors cores were built for training. For inference they added the int8 instructions (dp4a) which have lower precision. The Turing also has int4, and for inference this card blows the Volta out of the water since the v100 was only ~TOPS for int8. The Turing is 250 TOPS for int8 and 500 TOPS for int4.