Nvidia, the company that started with gaming graphics cards, is now a leader in artificial intelligence (AI). Its path to success did not happen overnight, but after years of technology accumulation and strategic transformation.
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The rise of gaming graphics
Nvidia's origins can be traced back to 1993 when it was just a small company that provided graphics cards to gamers. However, as graphics technology continued to evolve, Nvidia jumped at the chance and quickly dominated the gaming graphics card market with the introduction of the powerful GeForce family of graphics cards.
A windfall for mining trucks
In the mid-2010s, the rise of cryptocurrency mining brought a windfall to Nvidia. The powerful computing power of its graphics cards makes it ideal for mining, leading to a surge in demand for mining cards. This has brought NVIDIA a lot of profits and accumulated a lot of technical experience for it.
AI transformation
With the rise of artificial intelligence technology, Nvidia is acutely aware of the huge potential of its graphics cards. In 2015, the company launched the CUDA parallel computing platform, which allows developers to take advantage of the parallel processing power of graphics cards to accelerate AI algorithms.
Advantages of CUDA
CUDA offers a number of advantages for AI development:
Parallel processing: With thousands of parallel cores, graphics cards can process large amounts of data at the same time.
High throughput: The graphics card has a high memory bandwidth and can quickly access large amounts of data.
Low latency: The graphics card has low latency and can process data quickly and return results.
A leader in AI
With the advantages of CUDA, NVIDIA quickly became a leader in the field of AI. Its graphics cards are widely used in a variety of AI applications such as image, speech, and natural language processing. The company has also developed software platforms such as TensorRT and Triton Inference Server to further simplify the deployment and inference of AI models.
Acquisition of Mellanox
In 2019, NVIDIA acquired Mellanox, a leading provider of high-performance networking solutions. The acquisition strengthens NVIDIA's business in the data center space and provides key interconnect technologies for its AI portfolio.
Continuous innovation
NVIDIA has always been committed to continuous innovation, constantly introducing new graphics cards and AI technologies. Its latest generation graphics cards, such as the GeForce RTX 4000 Series and NVIDIA H100, deliver unprecedented performance for AI applications.
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Tensor Cores: Tensor Cores offer up to 132 petaflops of AI performance to accelerate deep learning training and inference.
CUDA Cores: With 16,384 CUDA Cores, it provides superior parallel processing capabilities for large datasets and complex models.
RT Cores: The second-generation RT Cores deliver up to 191 ray-traced TFLOPS for accelerated ray-traced rendering and AI image generation.
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Transformer Engine: Designed to accelerate natural language processing (NLP) and computer vision tasks, it delivers up to 32 petaflops of AI performance.
Tensor Cores: With 8,192 Tensor Cores, it delivers up to 640 petaflops of AI performance for training and inferring large AI models.
HBM3 Memory: With 80GB of HBM3 memory, it provides the bandwidth and capacity to handle massive data sets.
Optimization
Nvidia also offers a variety of software optimizations to enhance the AI performance of its graphics cards:
CUDA-X AI: A set of libraries and tools that simplify the development and deployment of AI models.
TensorRT: An inference optimizer that transforms trained AI models into high-performance inference engines.
Triton Inference Server: A deployment platform to manage and deploy AI models at scale.
These optimizations enable developers to harness the power of NVIDIA graphics cards and deliver the best performance for a wide range of AI applications.
Large AI models
NVIDIA's graphics cards have been used to train and deploy a variety of large AI models, including:
GPT-4: A large language model developed by OpenAI for natural language generation and translation.
DALL-E 2: An image generation model developed by OpenAI that creates realistic images based on text prompts.
Stable Diffusion: An open-source image generation model that generates high-quality images and artwork. What's New GeForce RTX 4080 Super graphics card, available now.
NVIDIA's transformation from a gaming graphics card to an "AI overlord" is not accidental. It stems from its keen insight into technology trends, continuous investment in R&D, and decisive execution of strategic transformation. By embracing the power of AI, NVIDIA has become a key player in driving the AI revolution and will continue to shape the field in the future.
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