Accelerating Recommender Systems using GPUs
Abstract
We describe GPU implementations of the matrix recommender algorithms CCD++ and ALS. We compare the processing time and predictive ability of the GPU implementations with existing multi-core versions of the same algorithms. Results on the GPU are better than the results of the multi-core versions (maximum speedup of 14.8).
- Publication:
-
arXiv e-prints
- Pub Date:
- November 2015
- DOI:
- 10.48550/arXiv.1511.02433
- arXiv:
- arXiv:1511.02433
- Bibcode:
- 2015arXiv151102433V
- Keywords:
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- Computer Science - Information Retrieval;
- Computer Science - Distributed;
- Parallel;
- and Cluster Computing
- E-Print:
- SAC '15 Proceedings of the 30th Annual ACM Symposium on Applied Computing Pages 879-884 ACM New York, NY, USA