Cross - Layer Approximation and In - Network Acceleration
Category: eBooks
- views: 187
- date: 7 July 2026
- posted by: BeMyLove
CrosLayer Approximation and In - Network Acceleration | 74.9 MB
Title: CrosLayer Approximation and In - Network Acceleration
Author: Zahra Ebrahimi, Akash Kumar
Category: Nonfiction, Science & Nature, Technology, Electronics, Circuits, Engineering, Computers
Language: English | 230 Pages | ISBN: 9783032217127
Description:
This book presents a novel Cross-Layer Approximation and Distribution architecture and methodology that advances the design of high-performance, high-throughput, energy-efficient, and sustainable reconfigurable computing systems. By leveraging the error tolerance inherent in modern AI and signal processing workloads, it enables performance and energy gains across hardware and software layers. The authors introduce innovative approximate multipliers, dividers, and coarse-grained processing elements for FPGA and CGRA platforms, coupled with an error-resiliency analysis and a heuristic-driven optimization framework that dynamically balance performance and accuracy. Extending beyond conventional architectures, the methodology described also integrates novel In-Network Computing (INC) techniques to bring computation closer to data sources within 5G/6G infrastructures. The result is a cohesive, scalable approach that redefines how energy-efficient and adaptive computing can be achieved across the edge-to-cloud continuum.
DOWNLOAD:
https://rapidgator.net/file/ff7258f050a63d9831034898776d2b11/978-3-032-21712-7.rar
https://nitroflare.com/view/4F7617D416F075E/978-3-032-21712-7.rar
This book presents a novel Cross-Layer Approximation and Distribution architecture and methodology that advances the design of high-performance, high-throughput, energy-efficient, and sustainable reconfigurable computing systems. By leveraging the error tolerance inherent in modern AI and signal processing workloads, it enables performance and energy gains across hardware and software layers. The authors introduce innovative approximate multipliers, dividers, and coarse-grained processing elements for FPGA and CGRA platforms, coupled with an error-resiliency analysis and a heuristic-driven optimization framework that dynamically balance performance and accuracy. Extending beyond conventional architectures, the methodology described also integrates novel In-Network Computing (INC) techniques to bring computation closer to data sources within 5G/6G infrastructures. The result is a cohesive, scalable approach that redefines how energy-efficient and adaptive computing can be achieved across the edge-to-cloud continuum.
- Describes a unified perspective on how approximation techniques can be applied across multiple abstraction levels;
- Discusses how FPGAs, CGRAs and In-Network Computing can enable scalable, distributed, and low-latency computation;
- Introduces architectural designs such as approximate multipliers, dividers, and hybrid SIMD/MIMD processing elements.
DOWNLOAD:
https://rapidgator.net/file/ff7258f050a63d9831034898776d2b11/978-3-032-21712-7.rar
https://nitroflare.com/view/4F7617D416F075E/978-3-032-21712-7.rar
We need your support!
Make a donation to help us stay online
Bitcoin (BTC)
bc1q08g9d22cxkawsjlf8etuek2pc9n2a3hs4cdrld
Bitcoin Cash (BCH)
qqvwexzhvgauxq2apgc4j0ewvcak6hh6lsnzmvtkem
Ethereum (ETH)
0xb55513D2c91A6e3c497621644ec99e206CDaf239
Litecoin (LTC)
ltc1qt6g2trfv9tjs4qj68sqc4uf0ukvc9jpnsyt59u
USDT (ERC20)
0xb55513D2c91A6e3c497621644ec99e206CDaf239
USDT (TRC20)
TYdPNrz7v1P9riWBWZ317oBgJueheGjATm
Information |
|||
 |
Users of GUESTS are not allowed to comment this publication. | ||