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

relapse

書目名稱NANO-CHIPS 2030影響因子(影響力)




書目名稱NANO-CHIPS 2030影響因子(影響力)學科排名




書目名稱NANO-CHIPS 2030網(wǎng)絡公開度




書目名稱NANO-CHIPS 2030網(wǎng)絡公開度學科排名




書目名稱NANO-CHIPS 2030被引頻次




書目名稱NANO-CHIPS 2030被引頻次學科排名




書目名稱NANO-CHIPS 2030年度引用




書目名稱NANO-CHIPS 2030年度引用學科排名




書目名稱NANO-CHIPS 2030讀者反饋




書目名稱NANO-CHIPS 2030讀者反饋學科排名

Postmenopause

Dennis Rich,Andrew Bartolo,Carlo Gilardo,Binh Le,Haitong Li,Rebecca Park,Robert M. Radway,Mohamed M.

Conflagration

Dealing with the Energy Versus Performance Tradeoff in Future CMOS Digital Circuit Design, never fully gone. Careful library design, optimal choice of supply voltages, plural and advanced architectural techniques to deal with timing variability impose themselves. In this chapter an overview of this scenery is given.

degradation

Enabling Domain-Specific Architectures with Programmable Devices,-level processing using CGRA (Coarse Grained Reconfigurable Architecture) is integrated on the same platform. Looking forward, we anticipate that the rising cost of building monolithic devices will also set a disaggregation trend towards using multiple dies. Building systems in the package will prov

和平

同來核對

燦爛

Heterogeneous 3D Nano-systems: The N3XT Approach?,new transistor and memory technologies, new integration approaches, and new architectures for computation immersed in memory. Nanosystems with such massive benefits are essential for enabling new frontiers of applications across a wide range of domains, from highly energy-constrained and deeply-embedded computing systems all the way to the cloud.

GEM

Digital Neural Network Accelerators, The focus of this chapter is on the inference phase of Deep Neural Networks which are used in many applications today. Their performance will be compared to multi-core-chips, graphics processing units, and field-programmable gate arrays. Based on current applications future requirements for digital accelerator chips will be outlined.

Eeg332

High-Performance Computing Trends,× improvements in energy efficiency and in throughput in the new decade, in order to limit and to manage the data explosion in the INTERNET and in the expected autonomous mobile world. The potential INTERNET energy crisis has been updated in 2018 to a required electric power of 928 GW in 2030, 21% of the expected total global need.

overshadow