Tag: free book

Exploring Zynq MPSoc – free book

This book introduces the Zynq® MPSoC (Multi-Processor System-on-Chip), an embedded device from Xilinx® that combines a processing system that includes Arm® Cortex®-A53 application and Arm Cortex-R5 real-time processors, alongside FPGA programmable logic.

The book covers the architecture of the device, the design tools and methods, conventional hardware/software co-design approach, and the newer software-defined methodology, as well as hardware and software development, multiprocessing, safety, security and platform management, system booting, and  special features on PYNQ (a Python-based framework)  and machine learning applications.

This book should serve as a useful guide for those getting starting with, and the working with Zynq MPSoC, and equally as a reference for technical managers wishing to gain familiarity with the device and its associated design methodologies.

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Prototypical – FPGA prototyping free book

Making FPGA prototyping part of the design process early means actually thinking about how the design will be prototyped via an FPGA

In Prototypical – The Emergence of FPGA prototyping for SoC Design book, the authors tell the history of FPGA-based prototyping and three leading system providers – S2C, Cadence, and Synopsys.

First, the book describes how the need for co-verification evolved with chip complexity, where FPGAs got their start in verification, and why ASIC design benefits from prototyping technology.

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Introduction to signal processing – free book

Text adapted from the book website:

The book provides an applications-oriented introduction to digital signal processing written primarily for electrical engineering undergraduates. Practicing engineers and graduate students may also find it useful as a first text on the subject.

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Parallel Programming for FPGAs

Parallel Programming for FPGAs is an open-source book aimed at teaching hardware and software developers how to efficiently program FPGAs using high-level synthesis (HLS). The authors developed the book as we noticed a lack of material aimed at teaching people to effectively use HLS tools.

The book was developed over many years to serve as a primary reference for UCSD 237C — a hardware design class targeting first-year graduate students and advanced undergraduate students. We hope that you find it useful for learning more about HLS, FPGAs, and system-on-chip design.

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Finding Your Way Through Formal Verification – free book

Finding Your Way Through Formal Verification provides an introduction to formal verification methods. This book was written as a way to dip a toe in formal waters. You may be curious about formal verification, but you’re not yet sure it is right for your needs. Or you may need to plan and supervise formal verification activity as a part of a larger verification objective.

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FreeRange – Logic/Verilog free books & courses

Free Range’s author James Mealy has a long trajectory in the free diffusion of logic design.

On this site, you can find free books (Logic foundation and Verilog), selected chapters of the course on video, and solutions to the course’s lab exercises.

From the author page :

I started collecting digital design textbooks after arriving at Cal Poly; I was sure that writing books meant having all the books possible on the subject and arranging the information differently. What I found was that I simply didn’t like the approach taken in every digital design textbook I’ve ever read. This led me to take a different approach, which I’ve done in the FreeRange series of courseware. I put more comments regarding the approach on a different page and in the actual textbooks as well.

Free Range – Digital Design and Verilog Modeling

You may also want to check: Free Range VHDL (free book)

Understanding Machine Learning – free book

Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of the textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way.

The book, “Understanding Machine Learning: From Theory to Algorithms”, provides a theoretical account of the fundamentals underlying machine learning and the mathematical derivations that transform these principles into practical algorithms. Following a presentation of the basics, the book covers a wide array of central topics unaddressed by previous textbooks. These include a discussion of the computational complexity of learning and the concepts of convexity and stability; important algorithmic paradigms including stochastic gradient descent, neural networks, and structured output learning; and emerging theoretical concepts such as the PAC-Bayes approach and compression-based bounds.

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