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A 0.32-128 TOPS, Scalable Multi-Chip-Module-Based Deep Neural Network Inference Accelerator With Ground-Referenced Signaling in 16 nm., , , , , , , , , and 7 other author(s). IEEE J. Solid State Circuits, 55 (4): 920-932 (2020)SCNN: An Accelerator for Compressed-sparse Convolutional Neural Networks., , , , , , , , and . ISCA, page 27-40. ACM, (2017)Buffets: An Efficient and Composable Storage Idiom for Explicit Decoupled Data Orchestration., , , , , , , , and . ASPLOS, page 137-151. ACM, (2019)Eyeriss v2: A Flexible Accelerator for Emerging Deep Neural Networks on Mobile Devices., , , and . IEEE J. Emerg. Sel. Topics Circuits Syst., 9 (2): 292-308 (2019)Performance Considerations for Distributed Services: A Case Study: Mass Storage., and . ICDCS, page 289-297. IEEE Computer Society, (1988)Understanding error propagation in deep learning neural network (DNN) accelerators and applications., , , , , , and . SC, page 8. ACM, (2017)A 0.11 pJ/Op, 0.32-128 TOPS, Scalable Multi-Chip-Module-based Deep Neural Network Accelerator with Ground-Reference Signaling in 16nm., , , , , , , , , and 7 other author(s). VLSI Circuits, page 300-. IEEE, (2019)Mentoring Opportunities in Computer Architecture: Analyzing the Past to Develop the Future., , , , , , and . WCAE, page 1-9. IEEE, (2021)A Characterization of Processor Performance in the VAX-11/780., and . ISCA, page 301-310. ACM, (1984)A Characterization of Processor Performance in the VAX-11/780., and . 25 Years ISCA: Retrospectives and Reprints, page 274-283. ACM, (1998)