# amazon-archives/amazon-dsstne

Deep Scalable Sparse Tensor Network Engine (DSSTNE) is an Amazon developed library for building Deep Learning (DL) machine learning (ML) models

Repository: https://github.com/amazon-archives/amazon-dsstne
Canonical: https://ross.abutalabs.com/products/amazon-dsstne
Language: C++
License: Apache-2.0
License Family: permissive
Archived: true
Last push: 2020-03-02T05:35:24+00:00

## Health v2 (maintenance only)
Score: 10/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3814, "days_push": 2375, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, archived
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 4390, forks 723 (observed 2026-08-28T04:08:47.215861+00:00)

## What it is
DSSTNE (Deep Scalable Sparse Tensor Network Engine) is a C++ GPU library from Amazon for training and deploying deep learning recommendation models with sparse inputs and outputs. It uses model-parallel multi-GPU scaling to handle weight matrices too large for a single GPU.

## Use cases
- train recommendation models on sparse data
- scale deep learning training across multiple GPUs
- build personalized product recommendation engines
- train neural networks with layers too large for one GPU
- generate recommendations at production scale

## When to choose
- you need fast training on very sparse recommendation datasets
- your model's weight matrices exceed single-GPU memory
- you want production-oriented speed over experimental flexibility

## When to avoid
- you need actively maintained software with recent updates
- you want flexible experimentation with modern architectures
- you need general-purpose deep learning beyond recommendation workloads
- you prefer a rich ecosystem like PyTorch or TensorFlow

## Facets
- artifact type: library
- maturity: abandoned
- function: machine-learning, deep-learning, gpu-computing
- domain: machine-learning, deep-learning, large-language-models
- platform: cpp
- tags: recommendation-systems, sparse-tensors, model-parallelism, multi-gpu, cuda, linux, gpu, docker

## Member repositories
- amazon-archives/amazon-dsstne (main) score 10

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:47.215861+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:21:12.574792+00:00, confidence not recorded.
  - readme: https://github.com/amazon-archives/amazon-dsstne (fetched 2026-08-28T04:08:47.215861+00:00, sha 21b9cc37a641)
- Data as of 2026-08-30T08:39:29.467469+00:00.