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FPGA-Based Remote Power Side-Channel Attacks.

, and . IEEE Symposium on Security and Privacy, page 229-244. IEEE Computer Society, (2018)

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FPGA-Based Remote Power Side-Channel Attacks., and . IEEE Symposium on Security and Privacy, page 229-244. IEEE Computer Society, (2018)Tectonic-Shift: A Composite Storage Fabric for Large-Scale ML Training., , , , , , , , , and 7 other author(s). USENIX Annual Technical Conference, page 433-449. USENIX Association, (2023)Understanding and Co-designing the Data Ingestion Pipeline for Industry-Scale RecSys Training., , , , , , , , , and 7 other author(s). CoRR, (2021)cedar: Composable and Optimized Machine Learning Input Data Pipelines., , and . CoRR, (2024)To Centralize or Not to Centralize: A Tale of Swarm Coordination., , , , , , , , , and . CoRR, (2018)RecD: Deduplication for End-to-End Deep Learning Recommendation Model Training Infrastructure., , , , , , , , , and 2 other author(s). CoRR, (2022)Llama: A Heterogeneous & Serverless Framework for Auto-Tuning Video Analytics Pipelines., , , and . SoCC, page 1-17. ACM, (2021)ShEF: Shielded Enclaves for Cloud FPGAs., , and . CoRR, (2021)HyperFlow: A Processor Architecture for Nonmalleable, Timing-Safe Information Flow Security., , , and . CCS, page 1583-1600. ACM, (2018)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)