Computer Architecture: From the Stone Age to the Quantum Age

Not since the 1980s has computer architecture been so exciting! This book captures the moment, mining the history of computing to teach key concepts in modern hardware design and introduce the neural and quantum architectures of the future.

Computer Architecture is an in-depth exploration of the principles and designs that have shaped computer hardware through the ages, from counting devices like the abacus, to Babbage’s Difference Engine, to modern GPUs and the frontiers of quantum computing.

This engaging blend of history, theory, hands-on exercises, and real-world examples is sure to make for an insightful romp through a fast-changing world. You won’t just read about computer architecture, you’ll also gain the understanding to touch, build, and program it. You’ll explore the basic structures of a CPU by learning to program a Victorian Analytical Engine. You’ll extend electronic machines to 8-bit and 16-bit retro gaming computers, learning to program a Commodore 64 and an Amiga. You’ll delve into x86 and RISC-V architectures, cloud and supercomputers, and ideas for future technologies. 

You’ll also learn:
• How to represent data with different coding schemes and build digital logic gates 
• The basics of machine and assembly language programming
• How pipelining, out-of-order execution, and parallelism work, in context
• The power and promise of neural networks, DNA, photonics, and quantum computing 

Whether you’re a student, a professional, or simply a tech enthusiast, after reading this book, you’ll grasp the milestones of computer architecture and be able to engage directly with the technology that defines today’s world. Prepare to be inspired, challenged, and above all, see and experience the digital world, hands-on.

Charles Fox is an award-winning senior lecturer at the University of Lincoln, UK. With degrees from Cambridge, Oxford, and the University of Edinburgh, Fox has published over 100 research papers, which often apply embedded, smart, parallel, and neural architectures to AI and robotics. He’s a Fellow of the Higher Education Academy (FHEA) and the author of Data Science for Transport (Springer, 2018).