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Unverified Commit 349a48bd authored by Joseph Spisak's avatar Joseph Spisak Committed by GitHub
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Update README.md (#1306)

parent 1c4bfb62
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```
## Performance and Scalability
**Microbenchmark on speed and memory usage**: While leaving tensor and autograd functions to backend frameworks (e.g. PyTorch, MXNet, and TensorFlow), DGL aggressively optimizes storage and computation with its own kernels. Here's a comparison to another pupular package -- PyG. The short story is that raw speed is similar, but DGL has much better memory management.
**Microbenchmark on speed and memory usage**: While leaving tensor and autograd functions to backend frameworks (e.g. PyTorch, MXNet, and TensorFlow), DGL aggressively optimizes storage and computation with its own kernels. Here's a comparison to another popular package -- PyG. The short story is that raw speed is similar, but DGL has much better memory management.
| Dataset | Model | Accuracy | Time <br> PyG &emsp;&emsp; DGL | Memory <br> PyG &emsp;&emsp; DGL |
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