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2. Evolution of the Graphics Processing Unit (GPU)
 
 # Evolution of the Graphics Processing Unit (GPU)

  ![Publication image](/sites/default/files/styles/wide/public/default_images/default.jpeg?itok=qUFsuJCP "Publication image")

 Graphics processing units (GPUs) power today’s fastest supercomputers, are the dominant platform for deep learning, and provide the intelligence for devices ranging from self-driving cars to robots and smart cameras. They also generate compelling photorealistic images at real-time frame rates. GPUs have evolved by adding features to support new use cases. NVIDIA’s GeForce 256, the first GPU, was a dedicated processor for real-time graphics, an application that demands large amounts of floating-point arithmetic for vertex and fragment shading computations and high memory bandwidth. As real-time graphics advanced, GPUs became programmable. The combination of programmability and floating-point performance made GPUs attractive for running scientific applications. Scientists found ways to use early programmable GPUs by casting their calculations as vertex and fragment shaders. GPUs evolved to meet the needs of scientific users by adding hardware for simpler programming, double-precision floating-point arithmetic, and resilience.



 ## Authors



[William Dally](/person/william-dally)

[Steve Keckler](/person/stephen-keckler)

David B. Kirk (NVIDIA)

 

 

 ## Publication Date



Wednesday, December 1, 2021

 

 ## Published in



[IEEE Micro Special Issue of the 50th Anniversary of the Microprocessor](https://ieeexplore.ieee.org/document/9623445)

 

 ## Research Area



[Computer Architecture](/research-area/computer-architecture)

 

 

 ## External Links



[Published manuscript (IEEE Digital Library)](https://ieeexplore.ieee.org/document/9623445)

 

 

 ## Copyright



This material is posted here with permission of the IEEE. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to <pubs-permissions@ieee.org>.