---
# System prepended metadata

title: DLRM training
tags: [Accelerator]

---

# DLRM training
###### tags: `Accelerator`

paper: [link](https://arxiv.org/pdf/2005.04680.pdf)

* In a typical DL framework, a training iteration consist of 3 passes.
    1. forward pass which computes **loss** with respect to model parameters.
    2. backward pass which computes **gradients** with respect to model parameters.
    3. update pass (typically run by an optimizer) which takes learning rate and computed gradients from backward pass and **updates the model parameters**.

![](https://i.imgur.com/k7EZCxI.png =400x)
![](https://i.imgur.com/YUUcNoI.png =400x)
![](https://i.imgur.com/uurVt7V.png =400x)
