All Agent Skills
41,263 results
- Nemo Mbridge Perf Cuda GraphsNVIDIAOfficialValidate and use CUDA graph capture in Megatron Bridge, including local full-iteration graphs and Transformer Engine scoped graphs for attention, MLP, and MoE modules.
- Nemo Mbridge Perf Expert Parallel OverlapNVIDIAOfficialValidate 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 DeepEP and HybridEP.
- Nemo Mbridge Perf Hierarchical Context ParallelNVIDIAOfficialOperational guide for enabling hierarchical context parallelism in Megatron-Bridge, including config knobs, code anchors, pitfalls, and verification.
- Nemo Mbridge Perf Megatron FsdpNVIDIAOfficialOperational guide for enabling Megatron FSDP in Megatron-Bridge, including config knobs, code anchors, pitfalls, and verification.
- Nemo Mbridge Perf Memory TuningNVIDIAOfficialTechniques for reducing peak GPU memory in Megatron Bridge — expandable segments, PEFT + SP input re-gather, parallelism resizing, activation recompute, CPU offloading constraints, and common OOM fixes.
- Nemo Mbridge Perf Moe Comm OverlapNVIDIAOfficialMoE expert-parallel communication overlap in Megatron Bridge. Covers dispatch/combine overlap, flex dispatcher backends, and expert wgrad scheduling.
- Nemo Mbridge Perf Moe Dispatcher SelectionNVIDIAOfficialChoose the right MoE token dispatcher (`alltoall`, DeepEP, or HybridEP) for the hardware, EP degree, and optimization stage. Summarizes patterns from DSV3, Qwen3, Qwen3-Next, and VLM bring-up work.
- Nemo Mbridge Perf Moe Hardware ConfigsNVIDIAOfficialRepresentative, point-in-time MoE training playbooks by hardware and model family. Use them as candidate seeds, then revalidate the exact runtime, semantics, topology, and steady-state throughput.
- Nemo Mbridge Perf Moe Long ContextNVIDIAOfficialLong-context MoE training guidance for Megatron Bridge. Covers CP sizing, selective recompute, dispatcher choices, and practical patterns from DSV3, Qwen3, and Qwen3-Next long-context experiments.
- Nemo Mbridge Perf Moe Optimization WorkflowNVIDIAOfficialEvidence-gated workflow for MoE performance optimization in Megatron Bridge. Covers measurement contracts, the Three Walls framework, parallel folding, profiling, matched A/B tuning, and final validation.
- Nemo Mbridge Perf Moe Vlm TrainingNVIDIAOfficialPractical guidance for training MoE VLMs in Megatron Bridge. Compares FSDP and 3D-parallel approaches, using rounded lessons from Qwen3-VL, Qwen3-Next, and other multimodal experiments.
- Nemo Mbridge Perf Parallelism StrategiesNVIDIAOfficialOperational guide for choosing and combining parallelism strategies in Megatron Bridge, including sizing rules, hardware topology mapping, and combined parallelism configuration.
- Nemo Mbridge Perf Sequence PackingNVIDIAOfficialValidate and use packed sequences and long-context training in Megatron-Bridge, including offline LLM packing, collate-time VLM packing, Energon online packing, and CP constraints.
- Nemo Mbridge Perf Tp Dp Comm OverlapNVIDIAOfficialOperational guide for enabling TP, DP, and PP communication overlap in Megatron-Bridge, including config knobs, code anchors, pitfalls, and verification.
- Nemo Mbridge Recipe RecommenderNVIDIAOfficialRecommend and customize Megatron Bridge library and benchmark recipes for a user's model, GPU count, hardware, sequence length, and pretrain/SFT/PEFT goal. Use when selecting a starting recipe, comparing library and benchmark configs, resizing parallelism for a GPU allocation, or distinguishing convergence changes, semantics-preserving execution tuning, and benchmark-only shortcuts.
- Nemo Mbridge ResiliencyNVIDIAOfficialResiliency features in Megatron Bridge including fault tolerance, straggler detection, in-process restart, preemption, and re-run state machine.
- Nemo Relay Debug Runtime IntegrationNVIDIAOfficialUse this skill when NeMo Relay is installed or imported but application-side runtime behavior is missing or incorrect, including load failures, inactive scopes, missing events, and plugin or adaptive wiring problems.
- Nemo Relay Get StartedNVIDIAOfficialUse this skill when first-time NeMo Relay users want to try Relay, choose the least-complex supported quick start, or verify initial value through the CLI, a maintained integration, or direct Python, Node.js, or Rust instrumentation before production setup.
- Nemo Relay InstallNVIDIAOfficialUse this skill when choosing or running NeMo Relay installation for the CLI, Python, Node.js, Rust, OpenClaw, Hermes, or maintained framework integrations before runtime configuration or quick-start setup.
- Nemo Relay Instrument CallsNVIDIAOfficialUse this skill when an application owns tool or LLM/provider call sites and needs to wrap them with NeMo Relay scopes and managed execution APIs for lifecycle events, middleware, or guardrails.
- Nemo Relay Instrument Context IsolationNVIDIAOfficialUse this skill when concurrent requests, async tasks, threads, workers, goroutines, or agents need independent NeMo Relay scope stacks and correct ancestry propagation.
- Nemo Relay Instrument Typed WrappersNVIDIAOfficialUse this skill when adding NeMo Relay typed wrappers, domain types, or provider codecs while preserving JSON middleware semantics and caller-visible behavior.
- Nemo Relay Migrate From FlowNVIDIAOfficialUse this skill when migrating applications, examples, integrations, documentation, manifests, or repository code from NeMo Flow to NeMo Relay across Python, Rust, Node.js, Go, C FFI, CLI, configuration, and observability surfaces.
- Nemo Relay Plugin Adaptive TuningNVIDIAOfficialUse this skill when baseline NeMo Relay instrumentation exists and the user wants to configure or evaluate adaptive plugin behavior, including telemetry, state, adaptive_hints, tool_parallelism, ACG, hint consumption, or measured rollout.