Search: cuda
Search MCP servers and agent skills by name, description, category or topic — 155 results.
NVIDIA/CUDA-Q/cudaq-guide
CUDA-Q onboarding guide for installation, test programs, GPU simulation, QPU hardware, and quantum applications.
NVIDIA/Megatron-Bridge/perf-cuda-graphs
Validate and use CUDA graph capture in Megatron Bridge, including local full-iteration graphs and Transformer Engine scoped graphs for attention, MLP, and MoE modules.
NVIDIA/TensorRT-LLM/perf-torch-cuda-graphs
Apply CUDA Graphs to PyTorch workloads — API selection (torch.compile, PyTorch make_graphed_callables, TE make_graphed_callables, MCore CudaGraphManager, FullCudaGraphWrapper, m...
NVIDIA/DALI/dali-dynamic-mode
Use when writing DALI data loading or preprocessing code with `nvidia.dali.experimental.dynamic` (ndd), or when converting DALI pipeline-mode code to dynamic mode, or when the user...
NVIDIA/Megatron-Bridge/adding-model-support
Guide for adding support for new LLM or VLM models in Megatron-Bridge.
NVIDIA/Megatron-Bridge/build-and-dependency
Dev environment setup for Megatron Bridge — container-based development, uv package management, lockfile regeneration, adding dependencies, Slurm container usage, and common build...
NVIDIA/Megatron-Bridge/bump-dependency
Bump a pinned dependency (TransformerEngine, Megatron-LM, NRX, etc.), regenerate the lockfile, open a PR, and drive it to green by attaching a watchdog to the "CICD NeMo" workflow...
NVIDIA/Megatron-Bridge/cicd
CI/CD reference for Megatron Bridge — pipeline structure, commit and PR workflow, CI failure investigation, and common failure patterns.
NVIDIA/Megatron-Bridge/linting-and-formatting
Code style and quality rules for Megatron Bridge — ruff configuration, naming conventions, type hints, mypy rules, docstrings, copyright headers, logging, and the code review check...
NVIDIA/Megatron-Bridge/mlm-bridge-training
Run Megatron-LM (MLM) and Megatron Bridge training with mock or real data.
NVIDIA/Megatron-Bridge/multi-node-slurm
Convert single-node scripts to multi-node Slurm sbatch jobs and debug common multi-node failures.
NVIDIA/Megatron-Bridge/nemo-rl-e2e-testing
External NeMo-RL end-to-end validation workflow for Megatron-Bridge model/provider changes, including downstream compatibility checks, external RL lifecycle behavior, Megatron poli...
NVIDIA/Megatron-Bridge/parity-testing
Structured framework for verifying numerical parity of HFMCore weight conversions.
NVIDIA/Megatron-Bridge/perf-activation-recompute
Validate and use selective and full activation recompute in Megatron Bridge to reduce GPU memory usage at the cost of extra compute.
NVIDIA/Megatron-Bridge/perf-cpu-offloading
Validate and use CPU offloading in Megatron Bridge, including layer-level activation offloading and fractional optimizer state offloading with HybridDeviceOptimizer.
NVIDIA/Megatron-Bridge/perf-expert-parallel-overlap
Validate and use MoE expert-parallel communication overlap in Megatron-Bridge, including overlap_moe_expert_parallel_comm, delay_wgrad_compute, and flex dispatcher backends such as...
NVIDIA/Megatron-Bridge/perf-hierarchical-context-parallel
Operational guide for enabling hierarchical context parallelism in Megatron-Bridge, including config knobs, code anchors, pitfalls, and verification.
NVIDIA/Megatron-Bridge/perf-megatron-fsdp
Operational guide for enabling Megatron FSDP in Megatron-Bridge, including config knobs, code anchors, pitfalls, and verification.
NVIDIA/Megatron-Bridge/perf-memory-tuning
Techniques for reducing peak GPU memory in Megatron Bridge — expandable segments, parallelism resizing, activation recompute, CPU offloading constraints, and common OOM fixes.
NVIDIA/Megatron-Bridge/perf-moe-comm-overlap
MoE expert-parallel communication overlap in Megatron Bridge.
NVIDIA/Megatron-Bridge/perf-moe-dispatcher-selection
Choose the right MoE token dispatcher (`alltoall`, DeepEP, or HybridEP) for the hardware, EP degree, and optimization stage.
NVIDIA/Megatron-Bridge/perf-moe-hardware-configs
Representative MoE training playbooks by hardware platform and model family.
NVIDIA/Megatron-Bridge/perf-moe-long-context
Long-context MoE training guidance for Megatron Bridge.
NVIDIA/Megatron-Bridge/perf-moe-optimization-workflow
Systematic workflow for MoE training optimization in Megatron Bridge, based on the Megatron-Core MoE paper.
NVIDIA/Megatron-Bridge/perf-moe-vlm-training
Practical guidance for training MoE VLMs in Megatron Bridge.
NVIDIA/Megatron-Bridge/perf-parallelism-strategies
Operational guide for choosing and combining parallelism strategies in Megatron Bridge, including sizing rules, hardware topology mapping, and combined parallelism configuration.
NVIDIA/Megatron-Bridge/perf-sequence-packing
Validate and use packed sequences and long-context training in Megatron-Bridge, distinguishing offline packed SFT for LLMs from in-batch packing for VLMs, and applying the right CP...
NVIDIA/Megatron-Bridge/perf-tp-dp-comm-overlap
Operational guide for enabling TP, DP, and PP communication overlap in Megatron-Bridge, including config knobs, code anchors, pitfalls, and verification.
NVIDIA/Megatron-Bridge/recipe-recommender
Recommend and customize Megatron Bridge recipes for a user's model, GPU count, and training goal.
NVIDIA/Megatron-Bridge/resiliency
Resiliency features in Megatron Bridge including fault tolerance, straggler detection, in-process restart, preemption, and re-run state machine.
NVIDIA/Megatron-Bridge/testing
Testing reference for Megatron Bridge — unit and functional test layout, tier semantics (L0/L1/L2/flaky), script conventions, running tests locally, adding/moving/disabling tests,...
NVIDIA/Megatron-Bridge/verl-e2e-testing
External verl end-to-end validation workflow for Megatron-Bridge model/provider changes.
NVIDIA/Megatron-Core/build-and-dependency
Container-based dev environment setup and dependency management for Megatron-LM.
NVIDIA/Megatron-Core/bump-base-image
Bump the NVIDIA PyTorch base image (`nvcr.io/nvidia/pytorch:-py3`) used by Megatron-LM CI.
NVIDIA/Megatron-Core/create-issue
Investigate a failing GitHub Actions run or job and create a GitHub issue for the failure.
NVIDIA/Megatron-Core/linting-and-formatting
Linting and formatting for Megatron-LM.
NVIDIA/Megatron-Core/nightly-sync
Domain knowledge for the nightly main-to-dev sync workflow.
NVIDIA/Megatron-Core/onboard-gb200-1node-tests
Onboard 1-node GitHub MR functional tests for GB200 from existing mr-scoped 2-node tests.
NVIDIA/Megatron-Core/respond-to-issue
Research and draft a response to a GitHub issue or question from an external contributor.
NVIDIA/Megatron-Core/run-on-slurm
How to launch distributed Megatron-LM training jobs on a SLURM cluster.
NVIDIA/Megatron-Core/split-pr
Split a PR into multiple PRs to reduce the number of required CODEOWNERS reviewer groups.
NVIDIA/Megatron-Core/update-golden-values
Refresh golden values from a GitHub Actions workflow run (failing-only or all jobs), score the change with average normalized relative differences, and produce a PR-ready summary.
NVIDIA/Model-Optimizer/accessing-mlflow
Query and browse evaluation results stored in MLflow.
NVIDIA/Model-Optimizer/debug
Run commands inside a remote Docker container via the file-based command relay (tools/debugger).
NVIDIA/Model-Optimizer/deployment
Serve a quantized or unquantized LLM checkpoint as an OpenAI-compatible API endpoint using vLLM, SGLang, or TRT-LLM.
NVIDIA/Model-Optimizer/evaluation
Evaluates accuracy of quantized or unquantized LLMs using NeMo Evaluator Launcher (NEL).