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TensorDash: Exploiting Sparsity to Accelerate Deep Neural Network Training and Inference., , , , , , and . CoRR, (2020)A Matrix-Inversion Technique for FPGA-Based Real-Time EMT Simulation of Power Converters., , , and . IEEE Trans. Ind. Electron., 66 (2): 1224-1234 (2019)FPRaker: A Processing Element For Accelerating Neural Network Training., , , , , , , and . MICRO, page 857-869. ACM, (2021)Deep Learning Language Modeling Workloads: Where Time Goes on Graphics Processors., , and . IISWC, page 131-142. IEEE, (2019)GOBO: Quantizing Attention-Based NLP Models for Low Latency and Energy Efficient Inference., , , and . MICRO, page 811-824. IEEE, (2020)Schrödinger's FP: Dynamic Adaptation of Floating-Point Containers for Deep Learning Training., , , , , , and . CoRR, (2022)TensorDash: Exploiting Sparsity to Accelerate Deep Neural Network Training., , , , , , and . MICRO, page 781-795. IEEE, (2020)GOBO: Quantizing Attention-Based NLP Models for Low Latency and Energy Efficient Inference., and . CoRR, (2020)FPRaker: A Processing Element For Accelerating Neural Network Training., , , , , , , and . CoRR, (2020)Atalanta: A Bit is Worth a "Thousand" Tensor Values., , , , , , , and . ASPLOS (2), page 85-102. ACM, (2024)