Programming Languages / Compilers

Decorative image of green transparent cube with tiered white lights inside.

Oct 22, 2023

Differentiable Slang: Example Applications

Differentiable Slang easily integrates with existing codebases—from Python, PyTorch, and CUDA to HLSL—to aid multiple computer graphics tasks and enable...

6 MIN READ

Oct 22, 2023

Differentiable Slang: A Shading Language for Renderers That Learn

NVIDIA just released a SIGGRAPH Asia 2023 research paper, SLANG.D: Fast, Modular and Differentiable Shader Programming. The paper shows how a single language...

12 MIN READ

Jul 25, 2023

Ask Me Anything: NVIDIA CUDA Toolkit 12

On July 26, connect with NVIDIA CUDA product team experts on the latest CUDA Toolkit 12.

1 MIN READ

Jul 06, 2023

CUDA Toolkit 12.2 Unleashes Powerful Features for Boosting Applications

The latest release of CUDA Toolkit 12.2 introduces a range of essential new features, modifications to the programming model, and enhanced support for hardware...

8 MIN READ

Jan 17, 2023

CUDA 12.0 Compiler Support for Runtime LTO Using nvJitLink Library

CUDA Toolkit 12.0 introduces a new nvJitLink library for Just-in-Time Link Time Optimization (JIT LTO) support. In the early days of CUDA, to get maximum...

14 MIN READ

Apr 28, 2022

Updating the CUDA Linux GPG Repository Key

To best ensure the security and reliability of our RPM and Debian package repositories, NVIDIA is updating and rotating the signing keys used by the apt,...

5 MIN READ

Apr 06, 2021

N Ways to SAXPY: Demonstrating the Breadth of GPU Programming Options

Back in 2012, NVIDIAN Mark Harris wrote Six Ways to Saxpy, demonstrating how to perform the SAXPY operation on a GPU in multiple ways, using different languages...

9 MIN READ

Nov 16, 2020

Accelerating Fortran DO CONCURRENT with GPUs and the NVIDIA HPC SDK

Fortran developers have long been able to accelerate their programs using CUDA Fortran or OpenACC. For more up-to-date information, please read Using Fortran...

13 MIN READ

Aug 04, 2020

Accelerating Standard C++ with GPUs Using stdpar

Historically, accelerating your C++ code with GPUs has not been possible in Standard C++ without using language extensions or additional libraries: CUDA C++...

19 MIN READ

Oct 25, 2017

High-Performance GPU Computing in the Julia Programming Language

Julia is a high-level programming language for mathematical computing that is as easy to use as Python, but as fast as C. The language has been created with...

10 MIN READ

Nov 11, 2014

12 Things You Should Know about the Tesla Accelerated Computing Platform

You may already know NVIDIA Tesla as a line of GPU accelerator boards optimized for high-performance, general-purpose computing. They are used for parallel...

14 MIN READ

Oct 23, 2013

CUDA Pro Tip: nvprof is Your Handy Universal GPU Profiler

CUDA 5 added a powerful new tool to the CUDA Toolkit: nvprof. nvprof is a command-line profiler available for Linux, Windows, and OS X. At first glance, nvprof...

6 MIN READ

Jul 02, 2012

Six Ways to SAXPY

For even more ways to SAXPY using the latest NVIDIA HPC SDK with standard language parallelism, see N Ways to SAXPY: Demonstrating the Breadth of GPU...

8 MIN READ

May 14, 2012

In the Trenches at GTC: Languages, APIs and Development Tools for GPU Computing

By Michael Wang, The University Of Melbourne, Australia (GTC '12 Guest Blogger) It’s 9 am, the first morning session of the pre-conference Tutorial Day. The...

3 MIN READ