Testing out a new M1 Macbook pro with Mathematica 13.0.0. I verified that I used the correct version and it is running natively on ARM.
Mathematica in general runs great, and much fast than on my previous 2015 Macbook (Intel).
The benchmarking function (
Benchmark) confirms this.
Now, when using the ML features of Mathematica this changes. Here is a simple LeNet example from https://reference.wolfram.com/language/tutorial/NeuralNetworksIntroduction.html#621730217
trainingData = ResourceData["MNIST", "TrainingData"]; testData = ResourceData["MNIST", "TestData"]; NetTrain[NetModel["LeNet"], trainingData, All, ValidationSet -> testData]
When I run this I'm getting slightly over 700 samples/second. Here is the NetTrain result object:
For comparison, my 2015 Intel Macbook (i7 4980HQ) manages close to 2000 examples/s on the same example using the CPU.
My question is if this is just the state of Mathematica and the new ARM architecture or is there something that can be done to speed up the ML functions for Apple Silicon based macs?
Thanks everyone, E