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Pod-racing: bulk-bitwise to floating-point compute in racetrack memory for machine learning at the edge.

, , , , , and . IEEE Micro, 42 (6): 9-16 (2022)

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DownShift: Tuning Shift Reduction With Reliability for Racetrack Memories., , , , and . IEEE Trans. Computers, 72 (9): 2585-2599 (September 2023)Sustainable AI Processing at the Edge., , , , , , , , , and . IEEE Micro, 43 (1): 19-28 (2023)Tuning Memory Fault Tolerance on the Edge., , , , , and . ACM Great Lakes Symposium on VLSI, page 421-424. ACM, (2021)Sustainable AI Processing at the Edge., , , , , , , and . CoRR, (2022)DNA Pre-Alignment Filter Using Processing Near Racetrack Memory., , , , and . IEEE Comput. Archit. Lett., 21 (2): 53-56 (2022)Leveraging Transverse Reads to Correct Alignment Faults in Domain Wall Memories., , , , , and . DSN, page 375-387. IEEE, (2019)FPIRM: Floating-point Processing in Racetrack Memories., , , , , and . CoRR, (2022)Pod-racing: bulk-bitwise to floating-point compute in racetrack memory for machine learning at the edge., , , , , and . IEEE Micro, 42 (6): 9-16 (2022)CORUSCANT: Fast Efficient Processing-in-Racetrack Memories., , , , , and . MICRO, page 784-798. IEEE, (2022)PREMSim: A Resilience Framework for Modeling Traditional and Emerging Memory Reliability., , , , , and . MASCOTS, page 396-409. IEEE Computer Society, (2019)