Translating CUDA Tile Operations from Python to Rust Using Agentic AI
cuTile Rust (cutile-rs) is a tile-based system for safe, idiomatic GPU kernel authoring in the Rust programming language.
Infrastructure
Serving stacks, inference performance changes, deployment patterns, and platform reliability signals.
Dense vs. MoE Models: Active Parameters, Throughput, and When to Choose Each
How can a 30B-parameter model activate only 3B parameters per token, and still use the capacity of the larger model?
How NVIDIA Groq 3 LPX Deterministic Execution Drives Power-Efficient High-Interactivity Inference on NVIDIA Vera Rubin
Power is a defining constraint for AI factories.
When to Use Encode-Prefill-Decode Disaggregation to Accelerate Multimodal Model Serving
NVIDIA Generative AI Blog published a source-backed update on When to Use Encode-Prefill-Decode Disaggregation to Accelerate Multimodal Model Serving.
How to Size GPUs for AI Inference and TCO Without Overspending
The surge in AI adoption is transforming everything from chatbots to content generation.
Restore LLM Inference Capacity in Seconds with Shadow Engine Recovery in NVIDIA Dynamo
When an LLM engine process fails, the standard recovery path involves a cold restart.
How NVIDIA Groq 3 LPX Unlocks Ultrafast Interactivity at Long Context on NVIDIA Vera Rubin
NVIDIA Groq 3 LPX is the interactive AI inference accelerator for the NVIDIA Vera Rubin platform.
Scaling AI Inference Across Multiple GPUs Using NVIDIA TensorRT with Multi-Device Inference Support
Generative AI workloads are rapidly outgrowing the memory and compute budget of single GPUs.
Boost Inference Performance up to 15x on NVIDIA Blackwell Using DFlash Speculative Decoding
NVIDIA describes DFlash speculative decoding for Blackwell inference throughput. Treat the headline speedup as vendor-benchmark context until workload shape, quality tradeoffs, and deployment constraints are verified.