The document provides an introduction to GPUs, explaining their role in processing 3D graphics as efficient processors designed to manage complex mathematical processes. It contrasts GPUs with CPUs, outlining their functionalities and components, including the GPU pipeline and memory structure. Additionally, it discusses NVIDIA's CUDA platform, which facilitates general-purpose computing on GPUs through a parallel computing model.

1. INTRODUCTION TO GPU

2. GPU
Designed specifically for processing 3D graphics
The processor is built with integrated transform, lighting, triangle setup/clipping
and rendering engines, capable of handling millions of math-intensive processes
per second
Heart of the modern graphic cards

3. WHAT IS GPU?
A dedicated processor efficient at manipulating and displaying computer
graphics
VPU (Visual Processing Unit)
Like CPU, it’s a single chip processor
Main objective is to enable a representation of 3D world as realistically as
possible

4. GPU VS CPU
CPU GPU
Serial Parallel
APP CODE

5. GPU

6. GPU
Without GPU With GPU

7. COMPONENTS OF GPU
Graphics Processor
Graphics Co - Processor
Graphics Accelerator
Frame Buffer
Memory
Graphics BIOS
DAC
Display Connector
Bus Connector

8. GPU PIPELINE
MEMORY
Input Assembly
Rasterization
Render Target OP
Vertex Shading
Pixel Shading
Vertex/Index
Buffer
Textures
Textures

9. GPU PIPELINE
Vertex Shading
Rasterization
Pixel Shading

10. NVIDIA GPU ARCHITECTURE
CUDA (Compute Unified Device Architecture) is a parallel
computing platform and application programming interface (API)
model created by NVIDIA.
GPGPU (General-Purpose computing on Graphics Processing Units)
The CUDA platform is a software layer that gives direct access to the GPU's
virtual instruction set and parallel computational elements, for the execution
of compute kernels
The CUDA platform is designed to work with programming languages such
as C, C++, and Fortran

11. DATAPATH OF MULTITHREADED
SIMD PROCESSOR

12. NVIDIA GPU MEMORY STRUCTURE

13. GPU