Accelerating Long-Context Model Training in JAX and XLA | NVIDIA Technical Blog
… Context parallelism and ring attention Context parallelism CP is a parallelization strategy designed specifically for handling long sequences in transformer models. …
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24/7 Simulation Loops: How Agentic AI Keeps Subsurface Engineering Moving | NVIDIA Technical Blog
… The agent handles tedious keyword editing and baseline comparisons, while its self-healing logic proactively fixes convergence issues and input errors, with an optional human-in-the-loop, to keep simulations running 24/7. …
Achieving Single-Digit Microsecond Latency Inference for Capital Markets | NVIDIA Technical Blog
… By standardizing key metrics—such as latency, throughput, and efficiency for LSTM and other time series models—STAC-ML enables banks, hedge funds, and market makers to conduct objective, apples-to-apples comparisons of competing hardware and software solutions prior to deployment. …
How Justt Scaled Chargeback Extraction with Nemotron Parse
… Before and after comparisons 25% fewer manual corrections : Customers spend significantly less time correcting extracted data during the upload process, enabling faster case preparation and reduced operational overhead. …
Unlock Exascale Performance on NVIDIA GB200 NVL72 with Slurm Topology-Aware Job Scheduling | NVIDIA Technical Blog
… As shown in Figure 2, this simulator provides accurate and repeatable results by: Running the Slurm code Replaying production workloads or generating synthetic workloads Simulating real-world conditions, including node failures and recoveries Integrating with the metrics system for direct compariso… …
Scaling the AI-Ready Data Center with NVIDIA RTX PRO 4500 Blackwell Server Edition and NVIDIA vGPU 20 | NVIDIA Technical Blog
… It covers setting up MIG with vGPU, sizing for enterprise workloads, performance comparison, and supplementary features. …
Speeding Up Variable-Length Training with Dynamic Context Parallelism and NVIDIA Megatron Core | NVIDIA Technical Blog
… The solver uses the cost model output as input and applies a heuristic algorithm to determine a near-optimal packing strategy for each sample. …
Maximizing Memory Efficiency to Run Bigger Models on NVIDIA Jetson | NVIDIA Technical Blog
… The desktop compared to headless comparison is a straight BSP configuration swap: a full GNOME desktop session gnome-shell + Xorg + gnome-software + associated background services compared to a headless boot target multi-user.target , with no other changes to the stack. …
Pruning and Distilling LLMs Using NVIDIA TensorRT Model Optimizer | NVIDIA Technical Blog
… For Throughput comparison, all models are quantized to FP8 precision using Model Optimizer and run with TensorRT-LLM. …
Build AI-Ready Knowledge Systems Using 5 Essential Multimodal RAG Capabilities | NVIDIA Technical Blog
… Benefits of reasoning For any use case involving mathematical operations or complex data comparison, a typical simple similarity or hybrid search will not suffice. …