Titlebook: NANO-CHIPS 2030; On-Chip AI for an Ef Boris Murmann,Bernd Hoefflinger Book 2020 Springer Nature Switzerland AG 2020 Nano-Electronics.Artifi

思想上升

3D for Efficient FPGA,plus independent routing programmable level. This leads to?a futuristic FPGA in which structure and process similar to that of 3D NAND provide FPGA with lower cost and higher density than 2D Standard Cell design.

GIST

NATTY

crease

Coarse-Grained Reconfigurable Architectures,ccelerator architectures. Coarse-Grained Reconfigurable Architectures (CGRAs) have been shown to achieve higher performance and energy efficiency compared to conventional instruction-based architectures by avoiding instruction overheads with reconfigurable data and control paths. CGRAs also avoid th

CLIFF

,A 1000× Improvement of the Processor-Memory Gap,y—the so-called “Memory Wall.” This barrier is even more limiting for AI applications in which massive amounts of data need to go through relatively simple processing. The 2018 3DVLSI DARPA program is focused on addressing this challenge. Alternative technologies are covered in which layers of logic

發(fā)誓放棄

High-Performance Computing Trends,the 5-year period 2014–2019 saw a 5-times increase in the throughput of the TOP 10 supercomputers with constant electric power, which means a 5-times improvement in energy efficiency. With this jump in efficiency, two of these TOP 10 have also taken the lead among the TOP GREEN supercomputers. 3D in

avarice

健談的人

Machine Learning at the Edge,gh-end FPGAs and GPUs. As this rise of machine learning applications continues, some of these algorithms must move “closer to the sensor,” thereby eliminating the latency of cloud access and providing a scalable solution that avoids the large energy cost per bit transmitted through the network. This

Oration

The Memory Challenge in Ultra-Low Power Deep Learning,owever, to achieve this goal, we need to address memory organization challenges, as current machine learning (ML) models (e.g., deep neural networks) have storage requirements for both weights and activations that are often not compatible with on-chip memories and/or low cost, low power external mem

JAUNT