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Story of Nvidia

Authors

As the most import infrastructure of modern technology topics (AI, Machine Learning, Blockchain, etc.), let's witness how Nvidia reaches the pinnacle of the semi-silicon industry, and the unique role of computer hardwares.

@Author: Garfield Zhu

Story about NVIDIA

The new star in "Trillion Club". (2023)


And... The Man

History

0. Stock - Nasdaq: NVDA

See the history of the stock Nvidia first.
🌊 The tide of cutting-edge technologies bring NVIDIA where it is today.

1. Begining

  • 1993: Founded in Santa Clara, California, USA.

  • Founders: Jensen Huang, Chris Malachowsky, Curtis Priem.
  • Produce Graphic Cards for bussiness customers.
  • 3D Graphics for gaming and multimedia markets.

2. Developing

  • 1999: GeForce 256, the first GPU.

  • 1999: Nasdaq IPO.
  • 2000: 3DFX (Voodoo, first customer-facing graphic card), the competitor, went bankrupt.
    Nvidia acquired 3DFX.
  • As OEM, Nvidia produced GPUs for PC manufacturers.

3. New Vision

  • Facing to gaming market. (GeForce)
  • Decoupling the GPU from the PC. Face to customers directly.
  • 2008: CUDA, the first GPU computing platform.

  • Iterate GPU every 2-year. Keeping optimize the performance.
  • 2010: General Purpose GPU (GPGPU) concept for scientific computing supported by CUDA API.

4. AI, AR, VR, Auto-pilot, Blockchain, Cloud

  • 2015: CUDA enforced the Deep Learning neural network.
  • 2016: Nvidia Drive PX, the first AI Auto-pilot platform.
  • 2018: Nvidia announced Nvidia RTX™ for real-time ray tracing.

  • The raising of Blockchain and Cloud Computing make Nvidia widely adopted.

5. Bitcoin, Mining age

  • 2020: Bitcoin price raised to $20,000. The RTX 30 series was released.
  • The mining age makes the GPU price doubled, trippled and even higher. 30 series are almost all mining cards.

6. AI, Big Language Model, Metaverse

  • 2017: Google announced their Transformer model for LLM. See What is a transformer model
  • 2021: GPT-3, one of the largest language model, was released by OpenAI.
  • 2022: The ChatGPT is publicly announce. The big language model is popular.
  • 2022: NVIDIA Omniverse™ platform is released as fundational role of building metaverse.
  • As the core infrastructure of training LLM, Nvidia is again on the top of the tide.

7. Today

[Updates June. 18th, 2024] 😱 Nvidia is temporarily No.1 today.


Product Series

Nvidia had many product series, now it has 3 main series:

  • GeForce: Desktop, Gaming e.g. GeForce RTX 3090, GeForce RTX 4090.
  • Quadro: Workstation
  • Tesla: Data Center
  • Others: Jetson, Ada, Tegra, etc.

Anecdotes

1. NVIDIA naming

Nvidia's first chip was named as dot-NV. "NV" is the abbreviation of NEXT, for they enjoy developing the next generation of products.

For corp name, they try to find a latin word with "NV" in it. They found "invidia" in Latin, the envy. They want to be the envy of the industry. So they remove the "i" and named the company as "Nvidia". 🤣

Actually, they did it.

2. NVIDIA vs. AMD ？
  • Jensen Huang (黄仁勋) and Lisa Su (苏姿丰) are both Americans born in Taiwan.
  • They are relatives. Su's maternal grandfather is the eldest brother of Huang's mother. Huang is the "uncle" of Su.
  • Jensen Huang
  • Lisa Su
3. The nick names
  • Jensen Huang is called "老黄" and Lisa Su is called "苏妈" in China.
  • Jensen Huang is more popular as "皮衣刀客":
  • The "皮衣":

  • The "刀法":
    • Card30603060Ti30703070Ti30803080Ti30903090Ti
    SM count2838464868808284
    VRAM12GB8GB8GB8GB10GB12GB24GB24GB

    Semiconductor etching is error-prone, especially for 7nm, 5nm even 3nm process. The yield rate is not high.

    The chips are design to be error tolerable. Each area on the chip is standalone and can be disabled via firmware if there is an error. If the 84 SM chip has 2 SMs disabled, it will be written as a 82 SM chip and wrapped as 3090. 😆

4. The most popular CEO
  • The rank voted by Silicon Valley employees in Aug. 2023
  • Huang has a tatoo of "Nvidia" logo on his shoulder. (as he promised if the stock value reach $100)
  • Huang made the correct decisions to push the Nvidia where it is now:
    1. Forsee to gaming market as a "Billion". Build chip for gaming.
    2. Persist technology innovation to iterate the GPU.
    3. Make GPU general-purpose, become the hardware arsenal of new era.


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