performance

Runtime vs.number of dataloader workers and batch size

PyTorch / datasets / dataloader / data transfer to GPU – II – dataloader too slow on CPU?

by eremo
17 Mar 202518 Mar 2025
PyTorch datasets

In the last post of this mini-series we saw that some Pytorch torchvision datasets have a directly accessible property “data“. There we find image data in a dataset specific format. In the case of MNIST and FashionMNIST (and for many other sets) these data are already torch tensors. However, due to the fact that these tensors are squeezed, they do… Read More »PyTorch / datasets / dataloader / data transfer to GPU – II – dataloader too slow on CPU?

Preliminary test of a Nvidia RTX 4060 TI 16GB with neural networks

by eremo
16 Oct 202316 Dec 2023
Dev tools / equipment, Hardware

Recently I had the opportunity to test a Nvidia RTX 4060 TI (vendor: MSI, model:Ventus ) on my Linux system against a Geforce GTX 960. For private consumers as me who are not interested in gaming, but in Machine Learning [ML] this type of card can be interesting. I name three reasons: Some of the readers of this blog may… Read More »Preliminary test of a Nvidia RTX 4060 TI 16GB with neural networks

Criteria for ML capable graphic cards: Amount of VRAM or raw GPU power?

by eremo
14 Oct 202314 Oct 2023
General ML-topics, Opinions

Some of my readers may be interested in having a private environment to study Machine Learning [ML] techniques and perform experiments with complex Neural Network algorithms. I do not talk about AI professionals, but about people (as myself) who are students or privately interested in ML-techniques. And about people who have a limited budget for their AI and ML interests.… Read More »Criteria for ML capable graphic cards: Amount of VRAM or raw GPU power?