Search Results: CUDA

Red Hat has committed to integrating NVIDIA's CUDA Toolkit directly into RHEL, OpenShift, and Red Hat AI platforms, following similar moves by Canonical and SUSE. This strategic collaboration aims to streamline AI development by simplifying deployment and ensuring compatibility with NVIDIA's hardware ecosystem. The initiative reinforces Red Hat's hybrid cloud vision while addressing concerns about proprietary lock-in through open ecosystem integration.

RightNow AI has developed a groundbreaking GPU emulator that accurately predicts CUDA kernel execution times across 50+ NVIDIA GPUs without actual hardware. By simulating performance using architectural models and real specs, it achieves 99% accuracy, saving developers thousands in cloud costs and catching bugs before deployment. This tool transforms GPU optimization workflows from a costly gamble into a precise, accessible process.

Discover how meticulous CUDA kernel optimization can push NVIDIA's Tensor Cores to their absolute limits. By evolving from naive implementations to sophisticated techniques like permuted shared memory and asynchronous pipelines, this journey achieves 93% of the RTX 4090's theoretical peak performance—matching cuBLAS efficiency.

China's Innosilicon unveils the Fenghua No. 3 GPU, boasting RISC-V architecture, alleged CUDA compatibility, and 112GB+ HBM memory for AI workloads like large language models. This 'all-function' GPU targets gaming, medical imaging, and scientific computing, signaling a bold step in China's semiconductor self-sufficiency drive—but technical validation remains critical.

Navigating NVIDIA's GPU architecture requires fluency in a complex lexicon of specialized terms. This comprehensive guide demystifies CUDA cores, warp schedulers, and memory hierarchies to help developers optimize high-performance computing workloads.

RightNow AI launches an invite-only early access program focused on solving one of AI deployment's toughest challenges: ensuring stability across all CUDA versions and NVIDIA GPU architectures. The strategic move targets developers struggling with hardware fragmentation ahead of a wider public release for Windows, macOS, and Linux systems.