CUDA 11 Features Revealed | NVIDIA Technical Blog
The new NVIDIA A100 GPU based on the NVIDIA Ampere GPU architecture delivers the greatest generational leap in accelerated computing. The A100 GPU has revolutionary hardware capabilities and we’re excited to announce CUDA 11 in conjunction with A100. CUDA 11 enables you to leverage the new hardware capabilities to accelerate HPC, genomics, 5G, rendering, deep learning, data analytics, data science
High-Performance GPU Computing in the Julia Programming Language | NVIDIA Technical Blog
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 performance in mind, and combines careful language design with a sophisticated LLVM-based compiler [Bezanson et al. 2017]. Julia is already well regarded for programming multicor
Accelerated Ray Tracing in One Weekend in CUDA | NVIDIA Developer Blog
Recent announcements of NVIDIA’s new Turing GPUs, RTX technology, and Microsoft’s DirectX Ray Tracing have spurred a renewed interest in ray tracing. Using these technologies vastly simplifies the ability to write applications using ray tracing. But what if you’re curious about how ray tracing actually works? One way to learn is to code your own ray tracing engine. Would you like to build a ray t
Hybrid Frustum Traced Shadows
I recently delivered a presentation on “Advanced Geometrically Correct Shadows for Modern Game Engines” at GDC 2016. If you weren’t fortunate enough to attend GDC, then you can catch up with what I was talking about right here! The presentation itself can be found on our developer website: https://developer.nvidia.com/gameworks NVIDIA HFTS (Hybrid Frustum Traced Shadows) is an advanced hybrid shad
Mocha.jl: Deep Learning for Julia | NVIDIA Technical Blog
Deep learning is becoming extremely popular due to several breakthroughs in various well-known tasks in artificial intelligence. For example, at the ImageNet Large Scale Visual Recognition Challenge, the introduction of deep learning algorithms into the challenge reduced the top-5 error by 10% in 2012. Every year since then, deep learning models have dominated the challenges, significantly reducin
MapD: Massive Throughput Database Queries with LLVM on GPUs | NVIDIA Technical Blog
Note: this post was co-written by Alex Şuhan and Todd Mostak of MapD. At MapD our goal is to build the world’s fastest big data analytics and visualization platform that enables lag-free interactive exploration of multi-billion row datasets. MapD supports standard SQL queries as well as a visualization API that maps OpenGL primitives onto SQL result sets. Although MapD is fast running on x86-64 CP
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CUDA Development for Jetson with NVIDIA Nsight Eclipse Edition | NVIDIA Technical Blog