The KV cache accelerates LLM inference on GPUs by storing prior token key/value projections instead of recomputing them, reducing per-step attention cost from quadratic to linear. Decode is memory-ban…
A developer detailed the architectural differences between NVIDIA's Ampere and Hopper GPU architectures, focusing on tensor core and memory bandwidth improvements. The Hopper architecture introduces T…
NVIDIA released a guide showing how to optimize transformer-based models for low-precision training using Hopper and Blackwell GPUs, focusing on FP8 and NVFP4 formats. The method translates model conf…
Enterprises are burning millions on cloud LLM tokens due to inefficient agentic systems, prompting a shift to open-weight models on dedicated infrastructure to eliminate marginal token costs and achie…
NVIDIA released CompileIQ, an AI-powered compiler auto-tuning framework that uses evolutionary and genetic algorithms to optimize GPU compilers for individual workloads. The tool, included in NVIDIA C…