Summary:
- This article discusses the use of Tensor Cores, specialized hardware in NVIDIA GPUs, to accelerate the performance of floating-point operations in the cuBLAS library.
- Tensor Cores can provide significant performance improvements for machine learning and scientific computing applications that rely on matrix multiplications and other linear algebra operations.
- The article explains how the cuBLAS library can leverage Tensor Cores through a floating-point emulation technique, allowing developers to take advantage of this specialized hardware without having to modify their existing code.