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Accelerating DLRM Training with Compression by ak.ayazulla is a document available to read on EtoBox.

What is Accelerating DLRM Training with Compression about?

This document presents a novel approach to accelerate the training of Deep Learning Recommendation Models (DLRMs) by utilizing error-bounded lossy compression to reduce communication overhead during the all-to-all data exchange across multiple GPUs. The proposed method includes a dual-level adaptive strategy for error-bound adjustment and a hybrid compression algorithm tailored for embedding lookups, achieving significant training speedups with minimal accuracy loss. Evaluation results indicate an 8.6× acce

Author
ak.ayazulla
Language
EN