Chips Are Important, But It's The Software That Matters

For

Nvidia chips, the primary software platform is CUDA, which is based on extensions to C, C++, and Fortran. For AMD chips, the main platform is ROCm, which features the HIP programming language—a portable C++-based API. 

Here is a breakdown of the software for programming Nvidia and AMD GPUs.

Nvidia (CUDA)

The Compute Unified Device Architecture (CUDA) is Nvidia's proprietary parallel computing platform and programming model. 

• Key languages: The core of CUDA is an extension to C and C++.
• Other languages: CUDA also has official support and libraries for other popular languages, including:
  • Python (via wrappers like CuPy and Numba)
  • Fortran
  • Julia
  • MATLAB
• Performance: CUDA is known for having a mature, well-optimized ecosystem that provides superior performance for AI and High-Performance Computing (HPC) tasks on Nvidia hardware. 

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AMD (ROCm)

AMD's open-source platform for GPU programming is the Radeon Open Compute (ROCm) software stack. 

• HIP: The main programming language for ROCm is the Heterogeneous-computing Interface for Portability (HIP). HIP is a C++ runtime API that is intentionally similar to CUDA, allowing developers to port applications from CUDA to ROCm with minimal changes.
• Other languages: The ROCm platform also supports:
  • OpenCL
  • OpenMP
  • Python (via libraries like hip-python)
  • Fortran
• Flexibility: As an open-source platform, ROCm offers greater flexibility and customization options for developers.
• Ecosystem: While its ecosystem and tools are less mature than CUDA's, ROCm is rapidly gaining support within the AI and HPC communities. 

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Key difference and compatibility

• Proprietary vs. Open-Source: CUDA is a proprietary platform tied exclusively to Nvidia hardware, while ROCm is an open-source alternative for AMD GPUs.
• Compatibility Layer: HIP and the associated hipify tool provide a crucial bridge for developers. It allows code written for CUDA to be automatically translated into HIP, making it relatively simple to port applications from Nvidia to AMD hardware