HybridBackend Accelerates GPU-Based Recommendation Model Training for Ximalaya AI Cloud

Ximalaya AI Cloud adopted the open‑source HybridBackend framework to overcome sparse‑data bottlenecks, enabling columnar Parquet reads and hybrid parallel GPU training that boost GPU utilization by over threefold, cut recommendation model training time by more than half, and now powers all TensorFlow and DeepRec production models.

AI cloudDistributed TrainingGPU training

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HybridBackend Accelerates GPU-Based Recommendation Model Training for Ximalaya AI Cloud

Alibaba Cloud Big Data AI Platform

Apr 11, 2023 · Artificial Intelligence

How DeepRec Boosted Sparse Model Training and Inference for Large‑Scale Recommendations

This article details how the metaapp advertising team adopted Alibaba Cloud's open‑source DeepRec to overcome parameter‑server bottlenecks, compress terabyte‑scale embeddings, leverage GPU‑accelerated distributed training, and build a low‑maintenance, high‑performance inference service using DeepRec's Processor and oneDNN optimizations.

DeepRecDistributed TrainingEmbeddingVariable

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How DeepRec Boosted Sparse Model Training and Inference for Large‑Scale Recommendations

Alibaba Cloud Big Data AI Platform

Mar 20, 2023 · Artificial Intelligence

How HybridBackend Supercharged Ximalaya’s Recommendation Engine with GPU Acceleration

This article details how Ximalaya’s AI Cloud adopted the open‑source HybridBackend framework to overcome sparse data access and distributed training bottlenecks, achieving multi‑GPU utilization gains, faster model training, and significant cost reductions across its recommendation services.

Distributed TrainingGPU AccelerationHybridBackend

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How HybridBackend Supercharged Ximalaya’s Recommendation Engine with GPU Acceleration