GPU
NVIDIA CUDA Optimizations: Practical Guide to Faster GPU Code
Learn how NVIDIA's CUDA toolbox boosts GPU performance by 300x, crucial for AI and HPC applications driving NVIDIA's $5.4T market cap.
NVIDIA CUDA Python 1.0 Launch Brings Stability to GPU Devs
NVIDIA CUDA Python 1.0 introduces stable APIs, unifying GPU programming for Python developers and simplifying access to CUDA's full power.
NVIDIA's GPU Tool Boosts Financial Instrument Clustering
NVIDIA introduces AdaptGrow, a GPU-powered tool for high-scale financial clustering, addressing risk and portfolio management challenges.
NVIDIA’s KAI Scheduler and vCluster Enable GPU Sharing in Kubernetes
NVIDIA introduces a solution for isolated Kubernetes clusters and efficient GPU sharing, reducing infrastructure costs for AI/ML teams.
Together AI Unveils Advanced Autoscaling for LLM Inference
Together AI introduces autoscaling features tailored for large language models, optimizing GPU use and managing latency during traffic spikes.
NVIDIA, Applied Materials Accelerate Semiconductor Innovation
NVIDIA and Applied Materials collaborate to advance semiconductor design with GPU-accelerated simulations and digital twins, addressing AI-driven demand.
NVIDIA CUDA Kernel Fusion Boosts GPU Efficiency in AI Workloads
NVIDIA's CUDA kernel fusion cuts memory traffic, kernel launch overhead, and speeds up AI and HPC tasks by up to 3x. Key for MoE and LLM training.
Nvidia NVSHMEM Boosts GROMACS GPU Scaling for Molecular Dynamics
Nvidia's NVSHMEM enables GPU-initiated communication, improving GROMACS scalability by eliminating CPU bottlenecks in molecular dynamics simulations.
NVIDIA (NVDA) Teams Up With AI Clouds to Scale Token Factories
NVIDIA partners with AI clouds to deploy large-scale AI factories, leveraging a new revenue-sharing model to meet soaring compute demand.
NVIDIA GQE Sets Benchmark for GPU-Accelerated Query Engines
NVIDIA's GPU Query Engine (GQE) leverages Grace Blackwell hardware to deliver 7.5x faster database performance compared to CPUs. Learn how.