The History of Graphics Processing Units (GPU): From the Beginning to Artificial Intelligence

Graphics Processing Units (GPUs) have become essential components in modern computing, playing a central role in rendering graphics, video processing, and training AI models. But how did GPUs come to be? What was the first GPU, and how has this technology evolved into a pillar of modern innovation?

The Beginnings: The First Spark

● The First Use of the Term "GPU"

The term "GPU" officially emerged in 1999, but the early foundations of graphics processing go back to the 1980s.

● The First Programmable Graphics Processor

• Chip: GeForce 256 (by NVIDIA – 1999)

  • The first product officially labeled as a "GPU."

  • Marketed by NVIDIA as “the world’s first single-chip GPU.”

  • Supported hardware-based Transform and Lighting (T&L), offloading this from the CPU.

  • Transistor count: Around 23 million.

  • Architecture: 220nm process.

Before GeForce 256, graphics cards mainly relied on the CPU with some 2D acceleration chips such as:

• IBM 8514 (1986): One of the earliest dedicated 2D graphics accelerators.

• Early pioneers like S3 Graphics, Matrox, and 3Dfx pushed forward 3D graphics in the '90s.

The Evolution of GPUs: From Rendering to Computing

● Second Generation (2000 – 2005): 3D Graphics and Pixel Shading

• ATI Radeon 9700 Pro (2002): The first card to support DirectX 9.

• Introduced shader pipelines, enabling developers to create programmable effects.

● Third Generation (2006 – 2012): CUDA and Compute Revolution

• NVIDIA CUDA (2006): Transformed the GPU into a general-purpose computing unit (GPGPU), enabling:

  • Physical simulations.

  • Data analysis.

  • Deep learning model training.

• ATI became AMD (2006) after AMD acquired ATI, kicking off fierce competition with NVIDIA.

● Fourth Generation (2012 – 2020): AI and Deep Learning

• Introduction of NVIDIA’s Pascal, then Volta, then Turing architectures, offering:

  • Tensor Cores for AI workloads.

  • RT Cores for real-time ray tracing.

The Leading GPU Companies

1. NVIDIA

• The dominant player since 1999.

• Creator of CUDA and Tensor Cores.

• Leads in AI, professional graphics, and high-performance computing.

2. AMD (formerly ATI)

• Strong competitor in gaming and price-performance.

• Known for its RDNA and CDNA architectures.

3. Intel

• Officially entered the discrete GPU market with Intel Arc in 2022.

• Has long produced integrated GPUs (Intel HD Graphics, Iris Xe).

4. Apple

• Develops integrated GPUs for its M1 and M2 ARM-based chips.

• Offers high-efficiency GPU performance for mobile and desktop.

Modern Applications of GPUs

Ways GPUs Are Integrated in Computers

1. Integrated GPU

   • Built into the CPU (e.g., Intel UHD, Apple M1 GPU).

   • Lower power consumption, limited performance.

   • Suitable for everyday computing and office work.

2. Dedicated/Discrete GPU

   • A standalone graphics card with its own VRAM.

   • Much higher performance.

   • Used for gaming, design, AI, and scientific computation.

3. External GPU (eGPU)

   • Connected via Thunderbolt or USB-C.

   • Boosts GPU power for laptops and compact systems.

The Importance of GPUs Today

• Accelerated Computing: Capable of running thousands of threads in parallel.

• Technological Innovation: Powering AI, AR, autonomous vehicles, and more.

• Transforming PCs into Creative or Scientific Workstations.

• Revolutionizing Gaming: Realistic graphics, 4K/8K support, immersive VR experiences.

GPUs have evolved from simple display accelerators into high-performance computing units capable of processing massive amounts of data. As AI, parallel computing, and realistic graphics continue to expand, GPUs remain at the core of modern computing — and a key to the future.