Titlebook: Deep Learning for Computer Architects; Brandon Reagen,Robert Adolf,David Brooks Book 2017 Springer Nature Switzerland AG 2017

Opulent

書目名稱Deep Learning for Computer Architects影響因子(影響力)




書目名稱Deep Learning for Computer Architects影響因子(影響力)學(xué)科排名




書目名稱Deep Learning for Computer Architects網(wǎng)絡(luò)公開度




書目名稱Deep Learning for Computer Architects網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Deep Learning for Computer Architects被引頻次




書目名稱Deep Learning for Computer Architects被引頻次學(xué)科排名




書目名稱Deep Learning for Computer Architects年度引用




書目名稱Deep Learning for Computer Architects年度引用學(xué)科排名




書目名稱Deep Learning for Computer Architects讀者反饋




書目名稱Deep Learning for Computer Architects讀者反饋學(xué)科排名

Meager

Neural Network Accelerator Optimization: A Case Study,focus on designing and optimizing hardware accelerators for executing inferences on fully connected neural networks. This narrow focus allows us to provide a detailed case study. None of the methods (or the methodology) are specific to fully connected neurons so can be applied to all other commonly

沖擊力

Introduction,ds are being felt far and wide. But the mathematical and computational foundations of machine learning are not magic: these are methods that have been developed gradually over the better part of a century, and it is a part of computer science and mathematics just like any other.

典型

habile

Computer Supported Cooperative Workds are being felt far and wide. But the mathematical and computational foundations of machine learning are not magic: these are methods that have been developed gradually over the better part of a century, and it is a part of computer science and mathematics just like any other.

一個(gè)攪動(dòng)不安

Book 2017ues in solving notoriously difficult classification and regression problems has resulted in their rapid adoption in solving real-world problems. The emergence of deep learning is widely attributed to a virtuous cycle whereby fundamental advancements in training deeper models were enabled by the avai

一個(gè)攪動(dòng)不安

1935-3235 learning tools and show how aspiring practitioners can use the tools with the workloads to characterize and optimize DNNs...The remainder of the book is dedicat978-3-031-00628-9978-3-031-01756-8Series ISSN 1935-3235 Series E-ISSN 1935-3243

lobster

Affable

Somber