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What Is 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.
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.
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