Approximate computing
著者
書誌事項
Approximate computing
Springer, 2022
大学図書館所蔵 件 / 全3件
-
該当する所蔵館はありません
- すべての絞り込み条件を解除する
注記
Includes bibliographical references and index
内容説明・目次
内容説明
This book explores the technological developments at various levels of abstraction, of the new paradigm of approximate computing. The authors describe in a single-source the state-of-the-art, covering the entire spectrum of research activities in approximate computing, bridging device, circuit, architecture, and system levels. Content includes tutorials, reviews and surveys of current theoretical/experimental results, design methodologies and applications developed in approximate computing for a wide scope of readership and specialists.
Serves as a single-source reference to state-of-the-art of approximate computing;
Covers broad range of topics, from circuits to applications;
Includes contributions by leading researchers, from academia and industry.
目次
Part I Approximate Arithmetic and Circuits
1-Approximate Arithmetic Circuits: Design and Applications
2-An Automated Logic Level Framework for Approximate Modular Arithmetic Circuits
3-Approximate Multiplier Design for Energy Efficiency: From Circuit to Algorithm
4-Low-Precision Floating-Point Formats: From General-Purpose to Application-Specific
5-Spintronic Solutions for Approximate Computing
6-Majority Logic Based Approximate Multipliers for Error-Tolerant Applications
Part II Design Automation and Test
7-Approximate Logic Synthesis for FPGA by Decomposition
8-Design Techniques for Approximate Realization of Data-Flow Graphs
9-Approximation on Data Flow Graph Execution for Energy Efficiency
10-Test and Reliability of Approximate Hardware
Part III Security
11-SecurityVulnerabilities in Approximate Circuits
12-Voltage Overscaling Techniques for Security Applications
13-Approximate Computing for Cryptography
14-Towards Securing Approximate Computing Systems: Security Threats and Attack Mitigation
Part IV Neural Networks and Machine Learning
15-Approximate Computing for Machine Learning Workloads: A circuits and systems perspective
16-Approximate Computing for Efficient Neural Network Computation:
17-Enabling Efficient Inference of Convolutional Neural Networks via Approximation
18-Approximate Computing for Energy-Constrained DNN-based Speech Recognition
19-Efficient Approximate DNN Accelerators for Edge Devices
Part V Applications
20-Cross-Level Design of Approximate Computing for Continuous Perception System
21-Approximate Computing in Image Compression and Denoising
22-Approximate Computation for Baseband Processing
「Nielsen BookData」 より