Imagine you need to add two arrays of 50,000 numbers together. On a CPU, you would write a loop that processes one element at a time. This sequential approach works, but it's slow when dealing with ...

This is a sixth tutorial (#Madhav_Gumma_Tutorials) in my tutorial series on pipelining inputs on a single thread using CUDA Streams. This technique, known as pipelining, uses "ping-pong" buffering to ...

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Convolutional Neural Networks (CNNs) have revolutionized computer vision. They power face recognition on your phone, object detection in self-driving cars, and medical image analysis. But CNNs are ...

After teaching CUDA and GPU programming for nine years, I left the university. Still, I think knowing CUDA can be an important and outstanding skill especially nowadays, so I've started writing a ...

NVIDIA’s CUDA is a general purpose parallel computing platform and programming model that accelerates deep learning and other compute-intensive apps by taking advantage of the parallel processing ...

Every few years or so, a development in computing results in a sea change and a need for specialized workers to take advantage of the new technology. Whether that’s COBOL in the 60s and 70s, HTML in ...

NVIDIA CUDA 13.3 introduces Tile C++ programming, Python updates, and CompileIQ, delivering up to 15% kernel speedups and enhancing GPU development. NVIDIA (NASDAQ: NVDA) has unveiled CUDA 13.3, the ...

NVIDIA's new CUDA Tile IR backend for OpenAI Triton enables Python developers to access Tensor Core performance without CUDA expertise. Requires Blackwell GPUs. NVIDIA has released Triton-to-TileIR, a ...