Training a neural network in phase-change memory beats GPUs
In Summary : Compared to a typical CPU, a brain is remarkably energy-efficient, in part because it combines memory, communications, and p...
https://updatesinfosec.blogspot.com/2018/06/training-neural-network-in-phase-change.html
In Summary :
Compared to a typical CPU, a brain is remarkably energy-efficient, in part because it combines memory, communications, and processing in a single execution unit, the neuron. A brain also has lots of them, which lets it handle lots of tasks in parallel. Attempts to run neural networks on traditional CPUs run up against these fundamental mismatches. Only a few things can be executed at a time, and shuffling data to memory is a slow process. As a result, neural networks have tended to be both computationally and energy intensive. A few years back, IBM announced a new processor design that was a bit closer to a collection of neurons and could execute neural networks far more efficiently. But this didn't help much with training the networks in the first place.[...]
kindly refer the following link as follow up :
https://arstechnica.com/?p=1322933
Compared to a typical CPU, a brain is remarkably energy-efficient, in part because it combines memory, communications, and processing in a single execution unit, the neuron. A brain also has lots of them, which lets it handle lots of tasks in parallel. Attempts to run neural networks on traditional CPUs run up against these fundamental mismatches. Only a few things can be executed at a time, and shuffling data to memory is a slow process. As a result, neural networks have tended to be both computationally and energy intensive. A few years back, IBM announced a new processor design that was a bit closer to a collection of neurons and could execute neural networks far more efficiently. But this didn't help much with training the networks in the first place.[...]
kindly refer the following link as follow up :
https://arstechnica.com/?p=1322933
