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A 95.6-TOPS/W Deep Learning Inference Accelerator With Per-Vector Scaled 4-bit Quantization in 5 nm.

, , , , , , , , and . IEEE J. Solid State Circuits, 58 (4): 1129-1141 (2023)

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Joint impact of random variations and RTN on dynamic writeability in 28nm bulk and FDSOI SRAM., , , , , and . ESSDERC, page 98-101. IEEE, (2014)Simba: scaling deep-learning inference with chiplet-based architecture., , , , , , , , , and 7 other author(s). Commun. ACM, 64 (6): 107-116 (2021)Reprogrammable Redundancy for SRAM-Based Cache Vmin Reduction in a 28-nm RISC-V Processor., , , and . IEEE J. Solid State Circuits, 52 (10): 2589-2600 (2017)Resilient Design Techniques for Improving Cache Energy Efficiency.. University of California, Berkeley, USA, (2015)Simba: Scaling Deep-Learning Inference with Multi-Chip-Module-Based Architecture., , , , , , , , , and 7 other author(s). MICRO, page 14-27. ACM, (2019)A 95.6-TOPS/W Deep Learning Inference Accelerator With Per-Vector Scaled 4-bit Quantization in 5 nm., , , , , , , , and . IEEE J. Solid State Circuits, 58 (4): 1129-1141 (2023)A 1.17-pJ/b, 25-Gb/s/pin Ground-Referenced Single-Ended Serial Link for Off- and On-Package Communication Using a Process- and Temperature-Adaptive Voltage Regulator., , , , , , , , , and 3 other author(s). IEEE J. Solid State Circuits, 54 (1): 43-54 (2019)AutoCRAFT: Layout Automation for Custom Circuits in Advanced FinFET Technologies., , , , , , , , , and . ISPD, page 175-183. ACM, (2022)On-chip supply power measurement and waveform reconstruction in a 28nm FD-SOI processor SoC., , , , , , , , and . A-SSCC, page 125-128. IEEE, (2016)VS-Quant: Per-vector Scaled Quantization for Accurate Low-Precision Neural Network Inference., , , , , and . CoRR, (2021)