Mastering High Speed And Low Power Hardware System Design
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Mastering High-speed and Low Power Hardware System Design
Author: Mr. Kush Desai , Ms. Khushbu Shah
language: en
Publisher: QUILL TECH PUBLICATIONS
Release Date: 2025-03-11
Mastering High-speed and Low Power Hardware System Design is an authoritative guide that delves into the intricate world of high-speed and low-power hardware design, offering comprehensive insights into the principles, techniques, and best practices that drive the development of efficient, high-performance hardware systems. This book addresses the critical challenges of optimizing hardware systems for both speed and power consumption—two fundamental aspects that are increasingly important in the design of modern electronic systems. Beginning with an introduction to the basic concepts of digital systems, signal integrity, and power consumption, this book progressively moves into more advanced topics such as high-frequency signal design, clock management, power-efficient circuit design, and the integration of cutting-edge technologies. It explores the trade-offs and strategies involved in achieving the ideal balance between system speed and energy efficiency, with a focus on real-world applications in industries such as telecommunications, consumer electronics, automotive, and embedded systems. Through clear explanations, practical examples, and case studies, the book empowers engineers, students, and professionals to master the complexities of hardware design while fostering an understanding of how to create systems that are both high-speed and low-power. Whether designing communication systems, processors, or integrated circuits, Mastering High-speed and Low Power Hardware System Design provides the knowledge and tools needed to push the boundaries of hardware performance while adhering to stringent power consumption requirements. With contributions from leading experts in the field, this book offers invaluable insights into the future of hardware system design, making it an essential resource for anyone looking to excel in the design and optimization of advanced hardware systems in today’s rapidly evolving technological landscape.
Mastering Azure Machine Learning
Author: Christoph Korner
language: en
Publisher: Packt Publishing Ltd
Release Date: 2022-05-10
Supercharge and automate your deployments to Azure Machine Learning clusters and Azure Kubernetes Service using Azure Machine Learning services Key Features Implement end-to-end machine learning pipelines on Azure Train deep learning models using Azure compute infrastructure Deploy machine learning models using MLOps Book Description Azure Machine Learning is a cloud service for accelerating and managing the machine learning (ML) project life cycle that ML professionals, data scientists, and engineers can use in their day-to-day workflows. This book covers the end-to-end ML process using Microsoft Azure Machine Learning, including data preparation, performing and logging ML training runs, designing training and deployment pipelines, and managing these pipelines via MLOps. The first section shows you how to set up an Azure Machine Learning workspace; ingest and version datasets; as well as preprocess, label, and enrich these datasets for training. In the next two sections, you'll discover how to enrich and train ML models for embedding, classification, and regression. You'll explore advanced NLP techniques, traditional ML models such as boosted trees, modern deep neural networks, recommendation systems, reinforcement learning, and complex distributed ML training techniques - all using Azure Machine Learning. The last section will teach you how to deploy the trained models as a batch pipeline or real-time scoring service using Docker, Azure Machine Learning clusters, Azure Kubernetes Services, and alternative deployment targets. By the end of this book, you'll be able to combine all the steps you've learned by building an MLOps pipeline. What you will learn Understand the end-to-end ML pipeline Get to grips with the Azure Machine Learning workspace Ingest, analyze, and preprocess datasets for ML using the Azure cloud Train traditional and modern ML techniques efficiently using Azure ML Deploy ML models for batch and real-time scoring Understand model interoperability with ONNX Deploy ML models to FPGAs and Azure IoT Edge Build an automated MLOps pipeline using Azure DevOps Who this book is for This book is for machine learning engineers, data scientists, and machine learning developers who want to use the Microsoft Azure cloud to manage their datasets and machine learning experiments and build an enterprise-grade ML architecture using MLOps. This book will also help anyone interested in machine learning to explore important steps of the ML process and use Azure Machine Learning to support them, along with building powerful ML cloud applications. A basic understanding of Python and knowledge of machine learning are recommended.
System Programming Essentials with Go
Go beyond web development to learn system programming, building secure, concurrent, and efficient applications with Go's unique system programming capabilities Key Features Get a deep understanding of how Go simplifies system-level memory management and concurrency Gain expert guidance on essential topics like file operations, process management, and network programming Learn cross-platform system programming and how to build applications that interact directly with the OS Book DescriptionAlex Rios, a seasoned Go developer and active community builder, shares his 15 years of expertise in designing large-scale systems through this book. It masterfully cuts through complexity, enabling you to build efficient and secure applications with Go's streamlined syntax and powerful concurrency features. In this book, you’ll learn how Go, unlike traditional system programming languages (C/C++), lets you focus on the problem by prioritizing readability and elevating developer experience with features like automatic garbage collection and built-in concurrency primitives, which remove the burden of low-level memory management and intricate synchronization. Through hands-on projects, you'll master core concepts like file I/O, process management, and inter-process communication to automate tasks and interact with your system efficiently. You'll delve into network programming in Go, equipping yourself with the skills to build robust, distributed applications. This book goes beyond the basics by exploring modern practices like logging and tracing for comprehensive application monitoring, and advance to distributed system design using Go to prepare you to tackle complex architectures. By the end of this book, you'll emerge as a confident Go system programmer, ready to craft high-performance, secure applications for the modern world.What you will learn Understand the fundamentals of system programming using Go Grasp the concepts of goroutines, channels, data races, and managing concurrency in Go Manage file operations and inter-process communication (IPC) Handle USB drives and Bluetooth devices and monitor peripheral events for hardware automation Familiarize yourself with the basics of network programming and its application in Go Implement logging, tracing, and other telemetry practices Construct distributed cache and approach distributed systems using Go Who this book is for This book is for software engineers looking to expand their understanding of system programming concepts. Professionals with a coding foundation seeking profound knowledge of system-level operations will also greatly benefit. Additionally, individuals interested in advancing their system programming skills, whether experienced developers or those transitioning to the field, will find this book indispensable.