Nvidia CUDA

컴, 하드웨어, IT : 2008.02.15 11:42

세계적인 프로그래머블 그래픽 프로세서 업체인 엔비디아는 엔비디아 GPU(graphics processing units) 또는 업계 최초의 GPU용 C-컴파일러(C-compiler) 개발환경에서의 스레드 컴퓨팅 작업을 위한 근본부터 새로운 컴퓨팅 아키텍쳐인 CUDA 기술을 발표했다.

http://www1.pcbee.co.kr/contents/news/na/40161.html



http://www.nvidia.com/object/cuda_home.html


The CUDA™ Toolkit is a C language development environment for CUDA-enabled GPUs. The CUDA development environment includes:

  • nvcc C compiler
  • CUDA FFT and BLAS libraries for the GPU
  • Profiler
  • gdb debugger for the GPU (alpha available in March, 2008)
  • CUDA runtime driver (now also available in the standard NVIDIA GPU driver)
  • CUDA programming manual

The CUDA Developer SDK provides examples with source code to help you get started with CUDA. Examples include:

  • Parallel bitonic sort
  • Matrix multiplication
  • Matrix transpose
  • Performance profiling using timers
  • Parallel prefix sum (scan) of large arrays
  • Image convolution
  • 1D DWT using Haar wavelet
  • OpenGL and Direct3D graphics interoperation examples
  • CUDA BLAS and FFT library usage examples
  • CPU-GPU C- and C++-code integration
  • Binomial Option Pricing
  • Black-Scholes Option Pricing
  • Monte-Carlo Option Pricing
  • Parallel Mersenne Twister (random number generation)
  • Parallel Histogram
  • Image Denoising
  • Sobel Edge Detection Filter
  • MathWorks MATLAB® Plug-in (click here to download)

New SDK Samples in CUDA version 1.1 is available now. To see the complete list and download code, click here (link to the CUDA Zone page with SDK Code Samples).

Technology Features

  • Standard C programming language enabled on a GPU
  • Unified hardware and software solution for parallel computing on CUDA-enabled NVIDIA GPUs
  • CUDA compatible GPUs range from lower power notebook GPUs to high performance, multi-GPU systems
  • CUDA-enabled GPUs support the Parallel Data Cache and Thread Execution Manager
  • Standard numerical libraries for FFT (Fast Fourier Transform) and BLAS (Basic Linear Algebra Subroutines)
  • Dedicated CUDA driver for computing
  • Optimized direct upload and download path from the CPU to CUDA-enabled GPU
  • CUDA driver interoperates with OpenGL and DirectX graphics drivers
  • Support for Linux 32/64-bit and Windows XP 32/64-bit operating systems
  • Direct driver and assembly level access through CUDA for research and language development

Support

GeForce Tesla Quadro
8800 Ultra C870 FX 5600
8800 GTX D870 FX 4600
8800 GTS S870 FX 3700
8800 GT   FX 1700
8800 GS   FX 570
8600 GTS   FX 370
8600 GT   NVS 290
8500 GT   FX 1600M
8400 GS   FX 570M
8700M GT   FX 360M
8600M GT   Quadro Plex 1000 Model IV
8600M GS   Quadro Plex 1000 Model S4
8400M GT   NVS 320M
8400M GS   NVS 140M
8400M G   NVS 135M
    NVS 130M



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