---
# System prepended metadata

title: Comparison between Recommendation Systems
tags: [Accelerator]

---

# Comparison between Recommendation Systems
###### tags: `Accelerator`
root: [Storage Accelerator](https://hackmd.io/@nycu-cas/H1_tZ2_y9)

### Config
![](https://i.imgur.com/OahuVJO.png =300x)

![](https://i.imgur.com/2T42kVt.png =900x)

![](https://i.imgur.com/R2FvcBc.png =700x)

### Operator Breakdown
![](https://i.imgur.com/t8roqg7.png =800x)

![](https://i.imgur.com/tXo9LaT.png =400x)

![](https://i.imgur.com/Im3BBRd.png =500x)
```
Attention-dominated models are used to capture more complex feature interactions
```

### Performance Evaluation
![](https://i.imgur.com/Ih8SytX.png =800x)

![](https://i.imgur.com/ssODRmI.png =800x)

![](https://i.imgur.com/JSFBXHt.png =800x)

![](https://i.imgur.com/kQAr6p5.png =300x)

![](https://i.imgur.com/n39fBW8.png =300x)

### Existing Solution
* 2021 ACM, FlashEmbedding
* 2021 ACM, RecSSD
    * ![](https://i.imgur.com/xmtUWNC.png =400x)
* 2020 ACM, EMB-SSD

### Reference
1. 2020 HPCA, [The Architectural Implications of Facebook’s DNN-based Personalized Recommendation](https://arxiv.org/pdf/1906.03109.pdf)
2. 2020 IEEE, [Cross-Stack Workload Characterization of Deep Recommendation Systems](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9251259)
3. 2014 IEEE, [A top-down method for performance analysis and counters architecture](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9251259)
4. 2021 ACM, [RecSSD: Near Data Processing for Solid State Drive Based Recommendation Inference](https://arxiv.org/pdf/2102.00075.pdf)
5. 2020 ISCA, [DeepRecSys: A System for Optimizing End-To-End At-Scale Neural Recommendation Inference](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9138960)
6. [Deep Recommender Systems at Facebook feat. Carole-Jean Wu | Stanford MLSys Seminar Episode 24](https://www.youtube.com/watch?v=5xcd0V9m6Xs)