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The other reason (maybe the dominant reason) to prefer a TPU is to avoid paying for all the GPU functionality that is irrelevant to these workloads (FP32, FP64,
by philipkglass 9y ago
The other reason (maybe the dominant reason) to prefer a TPU is to avoid paying for all the GPU functionality that is irrelevant to these workloads (FP32, FP64, graphics-specific functionality, costs of writing graphics drivers that gets bundled into hardware unit prices...)
If I look at a GTX 1080 Ti and optimistically assume that I can keep it completely busy 24/7, operating at the 250 watt TDP, it would take 4.5 years for the retail electricity cost to match the initial purchase cost of $699. (I pay a bit under 7 cents/kWh). Now I do live in one of the cheapest-electricity regions of the US, but I would also assume that big data center operators are building facilities where electricity is cheap. And big customers get lower rates than households. I wouldn't be surprised if a GPU cluster's hardware is considered obsolete before its electricity costs match its initial hardware costs.
- DavidSJ 9y ago> costs of writing graphics drivers that gets bundled into hardware unit prices If Nvidia is smart, they consider only marginal, not fixed costs when pricing their products.
- matt4077 9y agoIf Nvidia is smart, costs have nothing to do with prices except as a lower bound.
- DavidSJ 9y agoLet Q(p) be quantity demanded at price p, and c be marginal cost. Then profit is Q(p)*(p-c). If e.g. Q(p) = 1/p^2 (price elasticity of demand of -2), then profit is 1/p - c/p^2, which is maximized at p = 2c. Note how optimal price depends on cost.
- walshemj 9y agoYou know that NVidia produce special cards for compute work?
- puzzle 9y agoHopefully, for customers, it also means not having to deal with proprietary Linux drivers and associated headaches.
- friedman23 9y ago>The other reason (maybe the dominant reason) to prefer a TPU is to avoid paying for all the GPU functionality that is irrelevant to these workloads (FP32, FP64, graphics-specific functionality, costs of writing graphics drivers that gets bundled into hardware unit prices...) Often bundling decreases cost. Bundling also has the additional advantage of producing more demand when selling excess capacity a la AWS.
- MR4D 9y agoNot in this case. Google wants a die as efficient as possible All of those take up die space, creating a larger processor. That increases the cost of defects, as well as overall manufacturing costs. For Amazon, you may be right, but for Google, they only want a specific function.