Performance Modeling of Computer Systems: A Comprehensive Guide to Microarchitectural Simulation

Ananya Pareek

Jul 2026 · Springer Nature

About this ebook

This book addresses the gap between performance modeling theory and practice by providing a systematic approach for learning and applying performance modeling relevant principles. It covers essential hardware systems including CPUs, GPUs, accelerators, and memory systems. For each system category, a three-pronged approach is employed: teaching the theoretical background succinctly, presenting modeling methodologies and detailed microarchitectural (cycle-accurate or other) techniques, and providing hands-on implementation guidance using freely available open source simulation frameworks. Furthermore, exercises reinforce learning through combined theoretical analysis and practical implementation.

This comprehensive approach offers multiple advantages. It provides thorough coverage of diverse systems, enabling professionals to build expertise without depending on specific job opportunities for learning. It allows students and new professionals to explore multiple areas before specializing with greater confidence. Finally, it serves as a practical reference for quick refreshers and skill development throughout one's career progression.

What You'll Learn

• Master performance modeling of CPUs, GPUs, accelerators, and memory systems using top open-source tools.
• Refresh core computer architecture concepts essential for accurate modeling.
• Apply best practices to real-world scenarios and start contributing with confidence.
• Build hands-on skills through exercises using widely adopted simulation frameworks.
• Adapt modeling techniques to new hardware and emerging technologies.

Who Is This Book For

Beginner to Intermediate for learning and as a refresher for advanced users. Students and new professionals.

About the author

Ananya Pareek is a senior Engineer specializing in computer system performance modeling and architecture. With well over a decade of industry experience spanning well known firms such as Google, Apple, Samsung, and AMD, he brings exceptional expertise in cycle accurate simulation and performance analysis across diverse computing domains. Over the years he has worked on multiple well known products, developing cutting edge simulation techniques and frameworks spanning Full System, CPU, GPU, etc.

He has also delivered lectures and talks on Hardware Performance with an audience spanning new undergrade students to experienced academics.