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Supporting Massive DLRM Inference through Software Defined Memory., , , , , , , , , и 10 other автор(ы). ICDCS, стр. 302-312. IEEE, (2022)Bandana: Using Non-volatile Memory for Storing Deep Learning Models., , , , , , , и . CoRR, (2018)A Block-Oriented, Parallel and Collective Approach to Sparse Indefinite Preconditioning on GPUs., , , и . IA3@SC, стр. 1-10. IEEE, (2018)Deep Learning Recommendation Model for Personalization and Recommendation Systems, , , , , , , , , и 14 other автор(ы). (2019)cite arxiv:1906.00091Comment: 10 pages, 6 figures.Low-Precision Hardware Architectures Meet Recommendation Model Inference at Scale., , , , , , , , , и 8 other автор(ы). CoRR, (2021)Disaggregated Multi-Tower: Topology-aware Modeling Technique for Efficient Large-Scale Recommendation., , , , , , , , , и 4 other автор(ы). CoRR, (2024)On Periodic Functions as Regularizers for Quantization of Neural Networks., , , , , и . CoRR, (2018)Shared Microexponents: A Little Shifting Goes a Long Way., , , , , , , , , и 12 other автор(ы). CoRR, (2023)MTIA: First Generation Silicon Targeting Meta's Recommendation Systems., , , , , , , , , и 46 other автор(ы). ISCA, стр. 80:1-80:13. ACM, (2023)The Architectural Implications of Facebook's DNN-Based Personalized Recommendation., , , , , , , , , и 6 other автор(ы). HPCA, стр. 488-501. IEEE, (2020)