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Timeloop: A Systematic Approach to DNN Accelerator Evaluation., , , , , , , , , and . ISPASS, page 304-315. IEEE, (2019)Full Stack Optimization of Transformer Inference: a Survey., , , , , , , , , and 2 other author(s). CoRR, (2023)DiffuseLoco: Real-Time Legged Locomotion Control with Diffusion from Offline Datasets., , , , , , , and . CoRR, (2024)DOSA: Differentiable Model-Based One-Loop Search for DNN Accelerators., , , , and . MICRO, page 209-224. ACM, (2023)RoSÉ: A Hardware-Software Co-Simulation Infrastructure Enabling Pre-Silicon Full-Stack Robotics SoC Evaluation., , , , , and . ISCA, page 64:1-64:15. ACM, (2023)MoCA: Memory-Centric, Adaptive Execution for Multi-Tenant Deep Neural Networks., , , , , and . HPCA, page 828-841. IEEE, (2023)Simba: Scaling Deep-Learning Inference with Multi-Chip-Module-Based Architecture., , , , , , , , , and 7 other author(s). MICRO, page 14-27. ACM, (2019)ISA-independent workload characterization and its implications for specialized architectures., and . ISPASS, page 245-255. IEEE Computer Society, (2013)Aladdin: A pre-RTL, power-performance accelerator simulator enabling large design space exploration of customized architectures., , , and . ISCA, page 97-108. IEEE Computer Society, (2014)Learning A Continuous and Reconstructible Latent Space for Hardware Accelerator Design., , , , and . ISPASS, page 277-287. IEEE, (2022)