Posts by Logan Grado

ResNet for image classification using AMD GPUs

In this blog, we demonstrate training a simple ResNet model for image classification on AMD GPUs using ROCm on the CIFAR10 dataset. Training a ResNet model on AMD GPUs is simple, requiring no additional work beyond installing ROCm and appropriate PyTorch libraries.

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Scale AI applications with Ray

Most machine-learning (ML) workloads today require multiple GPUs or nodes to achieve the performance or scale required by applications. However, scaling workloads beyond single node/single GPU workloads is difficult and require some expertise in distributed processing.

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Automatic mixed precision in PyTorch using AMD GPUs

As models increase in size, the time and memory needed to train them–and consequently, the cost–also increases. Therefore, any measures we take to reduce training time and memory usage can be highly beneficial. This is where Automatic Mixed Precision (AMP) comes in.

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