Name
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).
|
Year | DOI | Venue |
|---|---|---|
2015 | 10.1145/2695664.2695850 | SAC 2015: Symposium on Applied Computing
Salamanca
Spain
April, 2015 |
Keywords | Field | DocType |
Recommender Systems, Parallel Systems, NVIDIA CUDA | Recommender system,Matrix (mathematics),CUDA,Computer science,Parallel computing,Implementation,Computational science,Speedup | Journal |
Volume | ISSN | ISBN |
abs/1511.02433 | SAC '15 Proceedings of the 30th Annual ACM Symposium on Applied
Computing Pages 879-884 ACM New York, NY, USA | 978-1-4503-3196-8 |
Citations | PageRank | References |
4 | 0.38 | 10 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| André Valente Rodrigues | 1 | 4 | 0.38 |
| Alípio Jorge | 2 | 749 | 73.03 |
| Inês Dutra | 3 | 61 | 10.35 |