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Exploiting software information for an efficient memory hierarchy

. University of Illinois Urbana-Champaign, USA, (2014)

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DeNovoND: efficient hardware support for disciplined non-determinism., , and . ASPLOS, page 13-26. ACM, (2013)Parallel SAH k-D tree construction., , , , , , and . High Performance Graphics, page 77-86. Eurographics Association, (2010)Understanding data storage and ingestion for large-scale deep recommendation model training: industrial product., , , , , , , , , and 7 other author(s). ISCA, page 1042-1057. ACM, (2022)DeNovoND: Efficient Hardware for Disciplined Nondeterminism., , and . IEEE Micro, 34 (3): 138-148 (2014)Understanding and Co-designing the Data Ingestion Pipeline for Industry-Scale RecSys Training., , , , , , , , , and 7 other author(s). CoRR, (2021)Exploiting software information for an efficient memory hierarchy. University of Illinois Urbana-Champaign, USA, (2014)Learning to Collide: Recommendation System Model Compression with Learned Hash Functions., , , , , , and . CoRR, (2022)Software-hardware co-design for fast and scalable training of deep learning recommendation models., , , , , , , , , and 43 other author(s). ISCA, page 993-1011. ACM, (2022)HPVM: heterogeneous parallel virtual machine., , , , , and . PPoPP, page 68-80. ACM, (2018)Eliminating on-chip traffic waste: are we there yet?, , , and . ISPASS, page 163-164. IEEE Computer Society, (2015)