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About R For Deep Learning (II) - Achieve High-Performance DNN With Parallel Acceleration - ParallelR
This document discusses achieving high performance deep neural network computation with parallel acceleration in R. It profiles the performance of R's DNN implementation compared to H2O's implementation on MNIST data, finding that R's is much slower. The document analyzes the R DNN runtime and finds that matrix multiplication is the most time consuming operation.
Detailed Information
| Author: | ['Joshua Laferriere'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 12 |
| Language: | English |
| Format: | |
| Price: | FREE |
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