Developers can now use NVIDIA CUDA Tile programming within large existing C++ GPU codebases to develop highly optimized GPU kernels using tile-based...
NVIDIA CUDA 13.3 brings new capabilities and performance optimizations to developers across the CUDA ecosystem. The launch of NVIDIA CUDA Tile programming in...NVIDIA CUDA 13.3 brings new capabilities and performance optimizations to developers across the CUDA ecosystem. The launch of NVIDIA CUDA Tile programming in C++, enables high-level, tile-based kernel development that automatically manages complex low-level GPU details for optimal performance and portability. Additionally, CUDA Tile programming is now supported on Compute Capability 9.0…
NVIDIA CompileIQ tackles one of the hardest problems in performance engineering: finding the compiler options that unlock the best performance for a specific...NVIDIA CompileIQ tackles one of the hardest problems in performance engineering: finding the compiler options that unlock the best performance for a specific workload. Consider a team that has spent weeks optimizing an LLM inference pipeline on GPUs, tuning batch sizes, quantizing to FP8, adopting flash attention, fusing every kernel they can. The profiler says there’s nothing left to squeeze.
Precision medicine depends on two fundamental capabilities: understanding disease at the genomic level and identifying treatments at the molecular level. ...Precision medicine depends on two fundamental capabilities: understanding disease at the genomic level and identifying treatments at the molecular level. NVIDIA’s contributions to precision medicine extend far beyond accelerated computing, delivering a full-stack platform that translates hardware and software advancements directly into healthcare outcomes. Sequencing the human genome…
High‑quality 3D medical imaging data is the foundation of modern radiology AI, but access to it is often constrained by data scarcity, privacy restrictions,...High‑quality 3D medical imaging data is the foundation of modern radiology AI, but access to it is often constrained by data scarcity, privacy restrictions, and the high cost of expert annotation. As a result, training reliable 3D medical imaging models is frequently bottlenecked by small, narrow, and hard‑to‑share datasets, limiting model robustness and generalization. To help teams overcome…
Maximizing the value of AI infrastructure demands deep visibility into GPU utilization. Yet many platform teams running AI workloads on Kubernetes operate with...Maximizing the value of AI infrastructure demands deep visibility into GPU utilization. Yet many platform teams running AI workloads on Kubernetes operate with limited visibility into how their GPUs are used. Most don’t know who’s consuming them, how much memory is in use, and whether Kubernetes pods are pending or silently idle. Without a signal, GPU fleets are routinely underutilized and slow to…
Telcos around the world are building sovereign AI factories based on the NVIDIA Cloud Partner (NCP) reference architecture, giving governments, enterprises, and...Telcos around the world are building sovereign AI factories based on the NVIDIA Cloud Partner (NCP) reference architecture, giving governments, enterprises, and startups access to in‑country AI infrastructure with the right controls, trust, and performance. But infrastructure alone doesn’t get you to high-margin, production-ready enterprise AI services. Model sizes and reasoning workloads…
Autonomous AI agents are becoming more capable. Open models, Model Context Protocol (MCP)-connected tools, and portable skills are also making agents easier to...Autonomous AI agents are becoming more capable. Open models, Model Context Protocol (MCP)-connected tools, and portable skills are also making agents easier to extend.But scaling agent use with structural transparency and operational integrity requires more than runtime guardrails. Organizations and teams need to understand and trust the skills, or instructions, an agent is using.
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