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Compressing DMA Engine: Leveraging Activation Sparsity for Training Deep Neural Networks.

, , , , , and . HPCA, page 78-91. IEEE Computer Society, (2018)

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Tensor Casting: Co-Designing Algorithm-Architecture for Personalized Recommendation Training., , and . HPCA, page 235-248. IEEE, (2021)Compressing DMA Engine: Leveraging Activation Sparsity for Training Deep Neural Networks., , , , , and . HPCA, page 78-91. IEEE Computer Society, (2018)NeuMMU: Architectural Support for Efficient Address Translations in Neural Processing Units., , , , and . ASPLOS, page 1109-1124. ACM, (2020)ASPLOS 2020 was canceled because of COVID-19..Centaur: A Chiplet-based, Hybrid Sparse-Dense Accelerator for Personalized Recommendations., , , and . ISCA, page 968-981. IEEE, (2020)LazyDP: Co-Designing Algorithm-Software for Scalable Training of Differentially Private Recommendation Models., , , , , and . CoRR, (2024)Training personalized recommendation systems from (GPU) scratch: look forward not backwards., and . ISCA, page 860-873. ACM, (2022)TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning., , and . MICRO, page 740-753. ACM, (2019)Understanding the Implication of Non-Volatile Memory for Large-Scale Graph Neural Network Training., , and . IEEE Comput. Archit. Lett., 20 (2): 118-121 (2021)Fabrication of Microarrays for the Analysis of Serological Antibody Isotypes against Food Antigens., , , , , , , and . Sensors, 19 (18): 3893 (2019)Beyond the Memory Wall: A Case for Memory-Centric HPC System for Deep Learning., and . MICRO, page 148-161. IEEE Computer Society, (2018)