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NVIDIA

NVIDIA Corporation is an American multinational technology company headquartered in Santa Clara, California. It’s best known for:

  • GPUs (Graphics Processing Units) → powering gaming, professional visualization, and AI
  • CUDA platform → enabling General Purpose GPU (GPGPU) computing
  • AI and HPC solutions → hardware + software stack for deep learning, simulation, and data centers

Today, NVIDIA is a leader in AI computing, supercomputing, autonomous vehicles, and data center acceleration.


Short History of NVIDIA

  • 1993 → Founded by Jensen Huang, Chris Malachowsky, and Curtis Priem.
  • 1995 → First product: NV1 graphics card (not very successful).
  • 1999 → Launch of the GeForce 256, the world’s first "GPU".
  • 2006 → Introduction of CUDA, revolutionizing GPGPU computing.
  • 2010s → GPUs adopted in deep learning, HPC, and scientific computing.
  • 2017–2020 → Rise of Volta, Turing, and Ampere architectures, AI-focused with Tensor Cores.
  • 2022+ → Release of Hopper and Ada Lovelace architectures, dominance in AI supercomputing (e.g., powering ChatGPT training clusters).
  • Today → NVIDIA is central to AI, HPC, robotics, data centers, and autonomous driving.

NVIDIA HPC Libraries & Software Ecosystem

NVIDIA provides a comprehensive HPC software stack, often bundled as part of NVIDIA HPC SDK. These libraries accelerate linear algebra, deep learning, signal processing, communication, and parallel programming.

Core HPC Libraries

  • cuBLAS → GPU-accelerated BLAS (Basic Linear Algebra Subprograms).
  • cuSOLVER → Dense & sparse linear algebra solvers (LU, QR, eigenvalue problems).
  • cuSPARSE → Sparse matrix computations.
  • cuFFT → Fast Fourier Transforms on GPUs.
  • cuRAND → Random number generation (pseudo & quasi-random).
  • cuTENSOR → High-performance tensor operations for HPC & AI.

AI & Deep Learning Libraries

  • cuDNN → Deep Neural Network primitives (convolutions, pooling, RNNs).
  • TensorRT → Inference optimization and deployment.
  • NCCL (NVIDIA Collective Communications Library) → Multi-GPU and multi-node communication (all-reduce, broadcast, etc.).

HPC SDK & Tools

  • NVIDIA HPC SDK → Compilers, libraries, and tools for C, C++, Fortran on GPUs/CPUs.

    • Includes nvfortran, nvcc, nvc++ compilers.
  • Nsight Systems / Nsight Compute → Profiling and debugging tools.

  • CUDA Toolkit → Core developer toolkit with compiler, debugger, profiler, and libraries.

Other HPC/AI Frameworks & Platforms

  • NVIDIA Magnum IO → I/O and communication acceleration for HPC clusters.
  • NVIDIA Triton Inference Server → Deploy trained AI models at scale.
  • NVIDIA Omniverse → Simulation and collaboration platform (used in robotics, digital twins).
  • NVIDIA RAPIDS → GPU-accelerated data science and analytics libraries (cuDF, cuML, cuGraph).

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