This is the Windows app named DLRM whose latest release can be downloaded as dlrmsourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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SCREENSHOTS:
DLRM
DESCRIPTION:
DLRM (Deep Learning Recommendation Model) is Meta’s open-source reference implementation for large-scale recommendation systems built to handle extremely high-dimensional sparse features and embedding tables. The architecture combines dense (MLP) and sparse (embedding) branches, then interacts features via dot product or feature interactions before passing through further dense layers to predict click-through, ranking scores, or conversion probabilities. The implementation is optimized for performance at scale, supporting multi-GPU and multi-node execution, quantization, embedding partitioning, and pipelined I/O to feed huge embeddings efficiently. It includes data loaders for standard benchmarks (like Criteo), training scripts, evaluation tools, and capabilities like mixed precision, gradient compression, and memory fusion to maximize throughput.
Features
- Hybrid architecture combining sparse embeddings and dense MLP branches
- Efficient feature interaction (e.g. dot product, permutation) between sparse and dense features
- Multi-GPU and distributed training with embedding partitioning and gradient synchronization
- Support for quantization, memory optimization, and pipelined embedding I/O
- Training / evaluation support for large-scale datasets like Criteo, Avazu
- Baseline reference for industry and academic recommendation models
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/dlrm.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.