| OmniDRL: An Energy-Efficient Mobile Deep Reinforcement Learning Accelerators with Dual-mode Weight Compression and Direct Processing of Compressed Data
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Juhyoung Lee; Korea Advanced Institute of Science and Technology |
| Exynos 1080 high-peformance, low-power CPU and GPU with AMIGO
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Taehee Lee; Samsung |
| An Energy-efficient Floating-Point DNN Processor using Heterogeneous Computing Architecture with Exponent-Computing-in-Memory
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Juhyoung Lee; Korea Advanced Institute of Science and Technology |
| Dynamic Neural Accelerator for Reconfigurable and Energy-efficient Neural Network Inference
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Sakyasingha Dasgupta; EdgeCortix |
| SM6: A 16nm System-on-Chip for Accurate and Noise-Robust Attention-Based NLP Applications
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Thierry Tambe; Harvard |
| ENIAD: A Reconfigurable Near-data Processing Architecture for Web-Scale AI-enriched Big Data Service
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Jialiang Zhang; U Penn |
| A Plug-and-Play Universal Photonic Processor for Quantum Information Processing
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Caterina Taballione; QuiX |
| Industry’s First 7.2 Gbps 512 GB DDR5 Memory Module with 8-Stacked DRAMs: A Promising Memory Solution for Next-Gen Servers
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Sung Joo Park; Samsung |
| LightOn Optical Processing Unit: Scaling-up AI and HPC with a Non von Neumann co-processor
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Laurent Daudet; LightOn |
| System-on-Chip Implementation of Trusted Execution Environment with Heterogeneous Architecture
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Trong-Thuc Hoang; University of Electro-Communications |
| A CORDIC-based Trigonometric Hardware Accelerator with Custom Instruction in 32-bit RISC-V System-on-Chip
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Khai-Duy Nguyen; University of Electro-Communications |
| A photonic neural network using < 1 photon per scalar multiplication
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Tianyu Wang; Cornell |
| Edge Inference Engine for Deep & Random Sparse Neural Networks with 4-bit Cartesian-Product MAC Array and Pipelined Activation Aligner
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Kota Ando; Tokyo Institute of Technology |
| Photonic co-processors in HPC: using LightOn OPUs for Randomized Numerical Linear Algebra
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Daniel Hesslow; LightOn |
| Elpis: High Performance Low Power Controller for Data Center SSDs
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Seungwon Lee; Samsung |
| SOT-MRAM – Third generation MRAM memory opens new opportunities
|
Jean-Pierre Nozières; Antaios |
| PNNPU: A Fast and Efficient 3D Point Cloud-based Neural Network Processor with Block-based Point Processing for Regular DRAM Access
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Sangjin Kim; Korea Advanced Institute of Science and Technology |
| Samsung NPU: An AI accelerator and SDK for flagship mobile AP
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Jun-Seok Park; Samsung |