GPUs are specialized processors designed for mathematically intense and massively parallel computations. NVIDIA GPUs today power many of the top 500 fastest supercomputers, including the fastest petascale systems in the world. NVIDIA and MathWorks have collaborated to deliver the power of GPU computing in MATLAB. Learn more about MATLAB GPU Computing with NVIDIA GPUs from MathWorks.
The GPU computing capabilities in MATLAB enables users enjoy the performance of massively parallel computation without having to be an expert in CUDA, C, or Fortran. Users can also scale up to large GPU clusters using MATLAB Parallel Server.
GPU Coder enables users to generate optimized CUDA code from MATLAB for deep learning, embedded vision, and autonomous systems. The generated code automatically calls optimized NVIDIA CUDA libraries, including TensorRT, cuDNN, and cuBLAS, to run on NVIDIA GPUs with low latency and high-throughput.
2788 San Tomas Expressway
Santa Clara, CA 95051
MATLAB Computing on NVIDIA GPUs
Related Connections Views: Embedded Hardware - MCU, DSP, FPGA, HPC Platforms and Schedulers, Desktop, Web and Enterprise Deployment, Digital Signal Processing, Image Processing and Computer Vision, MATLAB Programming, Aerospace and Defense, Automotive, Consumer Electronics, Financial Services, Medical Devices