General Purpose Computing On Graphics Processing Units

The term "general-purpose computing on graphics processing units" (also known as "general-purpose computing on GPUs") refers to the practice of employing a graphics processing unit (GPU), which ordinarily performs computation only for the purpose of computer graphics, to carry out computation in programs that are typically performed by the central processing unit (CPU). The already parallel nature of graphics processing may be further parallelized by using numerous video cards in a single computer or a large number of graphics processors.

How You Will Benefit

(I) Insights, and validations about the following topics:

Chapter 1: General-purpose computing on graphics processing units

Chapter 2: Supercomputer

Chapter 3: Flynn's taxonomy

Chapter 4: Graphics processing unit

Chapter 5: Physics processing unit

Chapter 6: Hardware acceleration

Chapter 7: Stream processing

Chapter 8: BrookGPU

Chapter 9: CUDA

Chapter 10: Close to Metal

Chapter 11: Larrabee (microarchitecture)

Chapter 12: AMD FireStream

Chapter 13: OpenCL

Chapter 14: OptiX

Chapter 15: Fermi (microarchitecture)

Chapter 16: Pascal (microarchitecture)

Chapter 17: Single instruction, multiple threads

Chapter 18: Multidimensional DSP with GPU Acceleration

Chapter 19: Compute kernel

Chapter 20: AI accelerator

Chapter 21: ROCm

(II) Answering the public top questions about general purpose computing on graphics processing units.

(III) Real world examples for the usage of general purpose computing on graphics processing units in many fields.

(IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of general purpose computing on graphics processing units' technologies.

Who This Book Is For

Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of general purpose computing on graphics processing units.