Svoboda | Graniru | BBC Russia | Golosameriki | Facebook

To install click the Add extension button. That's it.

The source code for the WIKI 2 extension is being checked by specialists of the Mozilla Foundation, Google, and Apple. You could also do it yourself at any point in time.

4,5
Kelly Slayton
Congratulations on this excellent venture… what a great idea!
Alexander Grigorievskiy
I use WIKI 2 every day and almost forgot how the original Wikipedia looks like.
Live Statistics
English Articles
Improved in 24 Hours
Added in 24 Hours
Languages
Recent
Show all languages
What we do. Every page goes through several hundred of perfecting techniques; in live mode. Quite the same Wikipedia. Just better.
.
Leo
Newton
Brights
Milds

Nvidia CUDA Compiler

From Wikipedia, the free encyclopedia

Nvidia CUDA Compiler (NVCC) is a proprietary compiler by Nvidia intended for use with CUDA.

Compiler

CUDA code runs on both the CPU and GPU. NVCC separates these two parts and sends host code (the part of code which will be run on the CPU) to a C compiler like GCC or Intel C++ Compiler (ICC) or Microsoft Visual C++ Compiler, and sends the device code (the part which will run on the GPU) to the GPU. The device code is further compiled by NVCC. NVCC is based on LLVM.[1] According to Nvidia provided documentation, nvcc in version 7.0 supports many language constructs that are defined by the C++11 standard and a few C99 features as well. In version 9.0 several more constructs from the C++14 standard are supported.[2]

Any source file containing CUDA language extensions (.cu) must be compiled with nvcc. NVCC is a compiler driver which works by invoking all the necessary tools and compilers like cudacc, g++, cl, etc. NVCC can output either C code (CPU Code) that must then be compiled with the rest of the application using another tool or PTX or object code directly. An executable with CUDA code requires: the CUDA core library (cuda) and the CUDA runtime library (cudart).

Other widely used libraries:

  • CUBLAS: BLAS implementation
  • CUFFT: FFT implementation
  • CUDPP (Data Parallel Primitives): Reduction, Scan, Sort.
  • Thrust: Reduction, Scan, Sort.

See also

References

  1. ^ "CUDA LLVM Compiler". NVIDIA Developer. Retrieved Apr 6, 2016.
  2. ^ "CUDA C++ Programming Guide". NVIDIA Documentation Hub. Retrieved 2019-06-28.

General

  1. David B. Kirk, and Wen-mei W. Hwu. Programming massively parallel processors: a hands-on approach. Morgan Kaufmann, 2010.
  2. "NVIDIA CUDA Compiler Driver NVCC". NVIDIA Documentation Hub. Archived from the original on Oct 13, 2023.
  3. "CUDPP". GPGPU. Archived from the original on Nov 17, 2018.
This page was last edited on 22 March 2024, at 14:00
Basis of this page is in Wikipedia. Text is available under the CC BY-SA 3.0 Unported License. Non-text media are available under their specified licenses. Wikipedia® is a registered trademark of the Wikimedia Foundation, Inc. WIKI 2 is an independent company and has no affiliation with Wikimedia Foundation.