Research Infrastructures for Hardware Accelerators - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Research Infrastructures for Hardware Accelerators write by Yakun Sophia Shao. This book was released on 2022-05-31. Research Infrastructures for Hardware Accelerators available in PDF, EPUB and Kindle. Hardware acceleration in the form of customized datapath and control circuitry tuned to specific applications has gained popularity for its promise to utilize transistors more efficiently. Historically, the computer architecture community has focused on general-purpose processors, and extensive research infrastructure has been developed to support research efforts in this domain. Envisioning future computing systems with a diverse set of general-purpose cores and accelerators, computer architects must add accelerator-related research infrastructures to their toolboxes to explore future heterogeneous systems. This book serves as a primer for the field, as an overview of the vast literature on accelerator architectures and their design flows, and as a resource guidebook for researchers working in related areas.
Hardware Accelerators in Data Centers
Hardware Accelerators in Data Centers - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Hardware Accelerators in Data Centers write by Christoforos Kachris. This book was released on 2018-08-21. Hardware Accelerators in Data Centers available in PDF, EPUB and Kindle. This book provides readers with an overview of the architectures, programming frameworks, and hardware accelerators for typical cloud computing applications in data centers. The authors present the most recent and promising solutions, using hardware accelerators to provide high throughput, reduced latency and higher energy efficiency compared to current servers based on commodity processors. Readers will benefit from state-of-the-art information regarding application requirements in contemporary data centers, computational complexity of typical tasks in cloud computing, and a programming framework for the efficient utilization of the hardware accelerators.
Hardware Accelerator Systems for Artificial Intelligence and Machine Learning
Hardware Accelerator Systems for Artificial Intelligence and Machine Learning - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Hardware Accelerator Systems for Artificial Intelligence and Machine Learning write by . This book was released on 2021-03-28. Hardware Accelerator Systems for Artificial Intelligence and Machine Learning available in PDF, EPUB and Kindle. Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Volume 122 delves into arti?cial Intelligence and the growth it has seen with the advent of Deep Neural Networks (DNNs) and Machine Learning. Updates in this release include chapters on Hardware accelerator systems for artificial intelligence and machine learning, Introduction to Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Deep Learning with GPUs, Edge Computing Optimization of Deep Learning Models for Specialized Tensor Processing Architectures, Architecture of NPU for DNN, Hardware Architecture for Convolutional Neural Network for Image Processing, FPGA based Neural Network Accelerators, and much more. Updates on new information on the architecture of GPU, NPU and DNN Discusses In-memory computing, Machine intelligence and Quantum computing Includes sections on Hardware Accelerator Systems to improve processing efficiency and performance
Data Orchestration in Deep Learning Accelerators
Data Orchestration in Deep Learning Accelerators - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Data Orchestration in Deep Learning Accelerators write by Tushar Krishna. This book was released on 2022-05-31. Data Orchestration in Deep Learning Accelerators available in PDF, EPUB and Kindle. This Synthesis Lecture focuses on techniques for efficient data orchestration within DNN accelerators. The End of Moore's Law, coupled with the increasing growth in deep learning and other AI applications has led to the emergence of custom Deep Neural Network (DNN) accelerators for energy-efficient inference on edge devices. Modern DNNs have millions of hyper parameters and involve billions of computations; this necessitates extensive data movement from memory to on-chip processing engines. It is well known that the cost of data movement today surpasses the cost of the actual computation; therefore, DNN accelerators require careful orchestration of data across on-chip compute, network, and memory elements to minimize the number of accesses to external DRAM. The book covers DNN dataflows, data reuse, buffer hierarchies, networks-on-chip, and automated design-space exploration. It concludes with data orchestration challenges with compressed and sparse DNNs and future trends. The target audience is students, engineers, and researchers interested in designing high-performance and low-energy accelerators for DNN inference.
Quantum Computer Systems
Quantum Computer Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Quantum Computer Systems write by Yongshan Ding. This book was released on 2022-05-31. Quantum Computer Systems available in PDF, EPUB and Kindle. This book targets computer scientists and engineers who are familiar with concepts in classical computer systems but are curious to learn the general architecture of quantum computing systems. It gives a concise presentation of this new paradigm of computing from a computer systems' point of view without assuming any background in quantum mechanics. As such, it is divided into two parts. The first part of the book provides a gentle overview on the fundamental principles of the quantum theory and their implications for computing. The second part is devoted to state-of-the-art research in designing practical quantum programs, building a scalable software systems stack, and controlling quantum hardware components. Most chapters end with a summary and an outlook for future directions. This book celebrates the remarkable progress that scientists across disciplines have made in the past decades and reveals what roles computer scientists and engineers can play to enable practical-scale quantum computing.
