This project demonstrates how to implement and benchmark high-performance batched matrix multiplication on GPU using both PyTorch’s official GPU API and a custom CUDA batched matmul kernel (via CuPy ...

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We propose to introduce a new distributed CUDA Unified Memory backend that supports Tensor allocation in CUDA Unified Memory in order to enable significantly larger network sizes (e.g. 80GB on a ...

House of Zen promises 3.5x improvement in inference and 3x uplift in training perf over last-gen software AMD closed the ...

NVIDIA introduces cuda.cccl, bridging the gap for Python developers by providing essential building blocks for CUDA kernel fusion, enhancing performance across GPU architectures. NVIDIA has unveiled a ...

NVIDIA announced  the CUDA software stack is being deployed across various operating systems and package managers. The company said it - Read more from Inside HPC & AI News.

“wsl --update”: Microsoft provides a command (when run in an elevated PowerShell or Command Prompt) that can fetch newer ...

Designed to work locally with large AI models, and scale to larger workloads connecting two Acer Veriton GN100 systems with ...

AI developers use popular frameworks like TensorFlow, PyTorch, and JAX to work on their projects. All these frameworks, in turn, rely on Nvidia's CUDA AI toolkit and libraries for high-performance AI ...

This post will show how to install PyTorch on your Windows 11 device. PyTorch is an open-source machine learning library used for a wide range of tasks in the field of artificial intelligence and ...