Accelerating Multi-GPU Embedding Retrieval with PGAS-Style Communication for Deep Learning Recommendation Systems

In this paper, we propose using Partitioned Global Address Space (PGAS) GPU one-sided asynchronous small messages to replace the widely used collective communication calls for sparse input multi-GPU embedding retrieval in deep learning recommendation systems. This GPU PGAS communication approach ach...

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Veröffentlicht in:	SC24-W: Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis S. 1262 - 1273
Hauptverfasser:	Chen, Yuxin, Buluc, Aydin, Yelick, Katherine, Owens, John D.
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 17.11.2024
Schlagworte:	Analytical models Collective Calls Communication Computational modeling Conferences Deep learning Deep Learning Recommendation Model Electronics packaging Graphics processing units High performance computing PGAS Recommender systems
Online-Zugang:	Volltext
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