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Hardware Acceleration
With Moore’s law and Dennard’s scaling no longer fueling the improvement in computing performance, new avenues for increasing performance are needed....
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Hardware Acceleration of Computational Holography
This book explains the hardware implementation of computational holography and hardware acceleration techniques, along with a number ofconcrete...
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Hardware Acceleration for SLAM in Mobile Systems
The emerging mobile robot industry has spurred a flurry of interest in solving the simultaneous localization and map** (SLAM) problem. However,...
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HILP: hardware-in-loop pruning of convolutional neural networks towards inference acceleration
Successful deployment of convolutional neural networks on resource-constrained hardware platforms is challenging for ubiquitous AI applications. For...
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The Good, the Bad and the Ugly: Practices and Perspectives on Hardware Acceleration for Embedded Image Processing
Modern embedded image processing deployment systems are heterogeneous combinations of general-purpose and specialized processors, custom ASIC...
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Hardware Acceleration of Explainable AI
The “black-box” nature of machine learning models raises concerns related to accountability and trustworthiness. Explainable AI is a promising...
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Hardware Acceleration of Microwave Imaging Algorithms
Microwave Imaging (MWI) is a technique that allows to reconstruct an image of the internal structure of an object by irradiating the object with a...
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Hardware acceleration of YOLOv7-tiny using high-level synthesis tools
FPGAs have emerged as a promising platform for implementing neural networks due to their reconfigurability, parallelism, and low power consumption....
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Energy-Efficient Single-Core Hardware Acceleration
This chapter deals with designing and implementing single-core specialized hardware accelerators for Machine learning (ML) applications, one...
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Hardware-Software Co-design for Deep Neural Network Acceleration
Deep neural networks are widely utilized in many fields. However, the extensive requirement of computation is usually difficult to meet to support...
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Hardware acceleration design of the SHA-3 for high throughput and low area on FPGA
In sensitive communications, the cryptographic hash function plays a crucial role, including in the military, healthcare, and banking, ensuring...
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Hardware acceleration for object detection using YOLOv4 algorithm on **linx Zynq platform
With the technological improvement in artificial intelligence, particularly deep learning is providing effective outcomes along with hardware...
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Multiwindow Rendering on a Cockpit Display Using Hardware Acceleration
AbstractThe modern display of a civil aircraft cockpit is based on a new interface ideology—it helps improve the perception of flight data received...
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A hardware-friendly logarithmic quantization method for CNNs and FPGA implementation
Convolutional Neural Networks (CNNs) have been widely used in various fields due to their high accuracy and efficiency. The performance of CNNs is...
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Hardware Acceleration of NTT-Based Polynomial Multiplication in CRYSTALS-Kyber
CRYSTALS-Kyber is a promising post-quantum encryption candidate and has been selected for standardization. However, its operational efficiency faces...
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Practical solutions in fully homomorphic encryption: a survey analyzing existing acceleration methods
Fully homomorphic encryption (FHE) has experienced significant development and continuous breakthroughs in theory, enabling its widespread...
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FPGA-Based Hardware-Accelerated Design of Linear Prediction Analysis for Real-Time Speech Signal
Linear prediction analysis is a crucial technique used in speech coding to compress speech signals and facilitate their reliable transmission over...
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ChamelIoT: a tightly- and loosely-coupled hardware-assisted OS framework for low-end IoT devices
The evergrowing Internet of Things (IoT) ecosystem continues to impose new requirements and constraints on every device. At the edge, low-end devices...
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Memristor-based hardware accelerators for artificial intelligence
Satisfying the rapid evolution of artificial intelligence (AI) algorithms requires exponential growth in computing resources, which, in turn,...
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Efficient tasks scheduling in multicore systems integrated with hardware accelerators
Multicore systems integrated with hardware accelerators provide better performance for executing real-time applications in time-critical fields, such...
