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It's absurd to make up formulae about energy consumption for something so complicated. Let's see the electricity bill for the data center. Yes, this will requir
by blt 5y ago
It's absurd to make up formulae about energy consumption for something so complicated. Let's see the electricity bill for the data center. Yes, this will require some effort to kick out other tasks and make sure the machines are fully saturated.
edit: the paper does not actually try to compute footprint as a function of "choice of algorithm" like the article implies - it's closer to "the electricity bill for the data center". See my comment below.
- jeffbee 5y agoThat doesn’t make a lot of sense. Removing the other workloads reduces the efficiency of the datacenter. The whole point of cloud computing, really.
- blt 5y agoI think this workload is big enough to saturate a lot of machines. But I should have read the original paper instead of the article. The article says: > This latest Google-led research... defines the footprint of a model as a function of several variables. They include the choice of algorithm, the program that implements it, the number of processors that run the program, the speed and power of those processors, a datacenter’s efficiency in delivering power and cooling the processors, and the energy supply mix... This, in my opinion, would be absurd. There is no way to directly map the choice of algorithm to energy consumption. But in fact, this is not the paper's definition of the footprint, it is only a list of things that influence it. The actual definition is Footprint = (electrical_energy_train + queries * electrical_energy_inference) * CO2e/KWh. In other words, the definition only uses total energy consumption. They compute electrical_energy_train by directly instrumenting the power consumption per machine. It's not a formula involving quantities like "choice of algorithm".