Kód: 54493780
You Can Read Machine Code. So Why Does Your Kernel Still Stall?Understanding GPU instructions is only the beginning. You know how to read disassembly, follow register allocation, and navigate the memory hierarchy. Yet your tensor ... celý popis
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Anotace knihy
You Can Read Machine Code. So Why Does Your Kernel Still Stall?
Understanding GPU instructions is only the beginning. You know how to read disassembly, follow register allocation, and navigate the memory hierarchy. Yet your tensor cores remain underutilized, profiler reports reveal unfamiliar stall reasons, and a hand-built asynchronous pipeline hangs without an obvious explanation.
This is where GPU performance engineering becomes serious.
Who Is This Book For?
This volume is written for readers who have completed Book 1 or possess equivalent hands-on GPU programming experience. It is ideal for performance engineers, kernel developers, compiler specialists, and researchers ready to progress from understanding machine instructions to engineering complete, high-performance GPU systems.
What You Will Learn in This Second Volume
Why This Book Is Different
Every major technique is demonstrated through working programs, exact correctness tests, and repeatable measurements you can perform on your own hardware. You will learn how to investigate problems systematically, validate solutions, and make performance decisions based on evidence rather than assumptions.
The book also includes valuable reference material covering instruction tables, architectural limits, and toolchain commands, giving you a practical resource beyond the initial reading.
A Note on the Two-Volume Series
This is Book 2 of a two-volume series. It builds directly on Book 1, which covers GPU architecture, instruction sets, execution, registers, scheduling, and the memory hierarchy. The foundational knowledge from Book 1 is assumed rather than repeated.
If you are ready to move beyond understanding GPU machine code and start engineering reliable, optimized, high-performance kernels, this volume takes you further.
Stop guessing at performance. Find the bottleneck, prove the solution, and build better GPU systems.
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