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GPUs have immensely contributed to various applications: in graphics, AI, scientific computing, you name it. But their ...

GPU programming is a mess. It relies on frameworks that are tied to specific devices, incompatible shading languages, and ...

What is the Bend programming language for parallel computing? Let's take a first look at Bend and how it uses a Python-like ...

Check out IBM Cloud for GPUs → https://ibm.biz/BdPSfV In the latest in our series of lightboarding explainer videos, Alex Hudak is ...

In this video, we talk about how why GPU's are better suited for parallelized tasks. We go into how a GPU is better than a CPU at ...

In this video, presenter Noel Chalmers introduces GPU programing concepts specific to ROCm. CTA: https://www.amd.com/rocm ...

Support this channel at: https://buymeacoffee.com/simonoz Code for animations and examples: ...

Support this channel at: https://buymeacoffee.com/simonoz Code for animations and examples: ...

Matrix multiplication on a GPU using CUDA C/C++. Code Repository: https://github.com/tgautam03/xGeMM Video Notes: ...

This video provides a high-level explanation of graphics programming, as well as the essential knowledge to get started writing ...

What is CUDA and why do we need it? An Nvidia invention, its used in many aspects of parallel computing. We spoke to Stephen ...

Introduction to NVIDIA's CUDA parallel architecture and programming model. Learn more by following @gpucomputing on twitter.

This is a solution to the classic CPU vs GPU technical interview question. Preparing for a technical interview? Checkout ...

In my previous video, I talked about why CPUs cannot have thousands of cores. While this is true, due to thermal, electrical, and ...

What's the difference between a CPU and GPU? And what the heck is a TPU, DPU, or QPU? Learn the how computers actually ...

Support this channel at: https://buymeacoffee.com/simonoz Code for animations and examples: ...

Tiled (general) Matrix Multiplication from scratch in CUDA C. Code Repo: ...

I explain the ending of exponential computing power growth and the rise of application-specific hardware like GPUs and TPUs.

If you can parallelize your code by harnessing the power of the GPU, I bow to you. GPU code is usually abstracted away by by the ...

Enroll to gain access to the full course: https://deeplizard.com/course/ptcpailzrd Artificial intelligence with PyTorch and CUDA.