nvidia/omniperf · Archived

perf-tuning

Resolve common Kit/Isaac Sim/Isaac Lab performance issues using specific settings and configuration changes. Covers PresentFrame stalls, resolveSamplerFeedback, headless mode, multi-GPU tradeoffs, DLSS/DLSS-G, PhysX tuning, RTX presets (isaaclab_performance/balanced/quality), viewport gizmos, HydraEngine waitIdle, fsWatcher overhead, and CPU governor. Use when profiling data shows a specific bottleneck and you need the fix, when someone asks "why is it slow" and you have Tracy/nsys evidence, or…

First seen Jun 30, 2026

Installation

$ npx skills add nvidia/omniperf --skill perf-tuning

Summary

  • Resolve common Kit/Isaac Sim/Isaac Lab performance issues using specific settings and configuration changes.
  • Covers PresentFrame stalls, resolveSamplerFeedback, headless mode, multi-GPU tradeoffs, DLSS/DLSS-G, PhysX tuning, RTX presets (isaaclab_performance/balanced/quality), viewport gizmos, HydraEngine waitIdle, fsWatcher overhead, and CPU governor.
  • Use when profiling data shows a specific bottleneck and you need the fix, when someone asks "why is it slow" and you have Tracy/nsys evidence, or when tuning RTX settings for GPU-bound workloads.
  • NOT for: initial triage (use diagnose-perf), capturing profiles (use profiling), or analyzing traces (use nsys-analyze).

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More details

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Repository health

Stars 33
License LICENSE
Default branch main
Open issues 0
Status Archived

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 7,822 B
  • docs SUMMARY.md 689 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 9 installs

SKILL.md

Performance Tuning for Kit / Isaac Sim / Isaac Lab

Specific fixes for performance issues identified through profiling. Prerequisite: you should already know where the bottleneck is (from diagnose-perf, profiling, or nsys-analyze skills).

PresentFrame is Abnormally Slow

Two causes:

GPU Backpressure

GPU work exceeds frame budget → CPU waits for swapchain buffer.

Verify: Enable GPU zones in Tracy and check if GPU frametime > CPU frametime.

--/profiler/gpu/tracyInject/enabled=true --/profiler/gpu=true --/rtx/addTileGpuAnnotations=true

Fix: Reduce GPU workload — see [RTX Tuning](#rtx-tuning-when-gpu-bound) below.

VNC / Remote Desktop

Virtual framebuffer causes driver present timing issues.

Fix: Use a physical monitor or run in headless mode.

resolveSamplerFeedback is Abnormally Slow

Texture Streaming bug causes per-frame thread waits proportional to RenderProduct count.

Fix: Disable Texture Streaming:

--/rtx-transient/resourcemanager/enableTextureStreaming=false

Impact: ~6.72 ms saved per frame (measured). VRAM usage may increase — verify headroom.

Headless Mode (3–4 ms GPU savings)

For simulation-only workloads (RL training, SDG, automated benchmarks):

# Isaac Sim via SimulationApp
simulation_app = SimulationApp({"headless": True, "disable_viewport_updates": True})
# Kit args
--no-window --/app/window/hideUi=True

Also disable viewport updates in Python:

from omni.kit.viewport.utility import get_active_viewport
get_active_viewport().updates_enabled = False

Multi-Camera Render Count Verification

Always check Tracy GPU zones to verify only intended cameras are rendering:

  • Count extrt/rtx/rtaTexturesMC (camera textures) and tviewportViewportTexture (viewport textures)
  • Verify resolution in zone names matches intent (e.g., rtaTexturesMC3RP_1920x1080)
  • In headless mode, check that unnecessary viewport textures aren't rendering in background

Common Multi-Camera Fixes

  • Remove per-camera viewports; keep render products only.
  • Replace separate camera render products with TiledCameraSensor when the workflow supports it.
  • Destroy or disable the default viewport after sensor setup in headless benchmark/simulation runs.
from isaacsim.sensors.experimental.camera import TiledCameraSensor

sensor = TiledCameraSensor(
    camera_paths,          # List[str]
    resolution=(H, W),     # Height, Width
    annotators=["rgb"],
)
data, info = sensor.get_data("rgb")

PhysX Tuning

Expose Full PhysX Detail

Default profilerMask=1 hides internal PhysX zones. To diagnose PhysX bottlenecks, remove the mask arg (defaults to ALL).

Key Settings

Setting Effect
--/physics/suppressReadback=true Suppress GPU→CPU readback
--/physics/updateToUsd=false Skip physics→USD writeback (only if not reading state from USD)
--/physics/disableContactProcessing=true Skip contact event callbacks (if no subscriber needs them)

Async Physics (USD Schema)

from pxr import UsdPhysics, PhysxSchema

stage = omni.usd.get_context().get_stage()
for prim in stage.Traverse():
    if prim.IsA(UsdPhysics.Scene):
        api = PhysxSchema.PhysxSceneAPI.Apply(prim)
        api.CreateUpdateTypeAttr().Set(PhysxSchema.Tokens.asynchronous)

Applicable when previous-frame physics results are acceptable (RL training, SDG).

Solver Type

The default solver is PGS. The profiling guide calls out switching PhysxSceneAPI.solverType to TGS as a scenario-dependent tuning option; verify with a WARM benchmark before keeping it.

api = PhysxSchema.PhysxSceneAPI.Apply(physics_scene_prim)
api.CreateSolverTypeAttr().Set("TGS")

Extension Change Detection (fsWatcher)

~0.1 ms/frame overhead for hot-reload file monitoring. Disable for benchmarks:

--/app/extensions/fsWatcherEnabled=false

Viewport Gizmo Overhead

Gizmos (manipulators, grid, selection outlines) cause significant CPU overhead in scenes with many objects.

--/persistent/app/viewport/displayOptions=0
--/persistent/app/viewport/gizmo/enabled=false

DLSS-G (Frame Generation) — Know What You're Measuring

DLSS-G inserts AI sub-frames between real frames:

  • Viewport HUD FPS includes sub-frames → inflated by 2–4x
  • Tracy/benchmark frametime FPS = actual rendering FPS
GPU Gen Sub-frame Multiplier
Ada (RTX 40) 2x
Blackwell (RTX 50) 3–4x

Rule: DLSS-G is for viewport display only. Disable for simulation/benchmarks:

--/rtx-transient/dlssg/enabled=false  # default is off, but verify

HydraEngine waitIdle

When /app/hydraEngine/waitIdle=true (default), main thread blocks every frame until GPU finishes.

--/app/hydraEngine/waitIdle=false  # allow CPU-GPU pipelining

Safe for rendering-only workloads. Keep true if reading GPU results same-frame (physics readback, synchronous sensors).

Multi-GPU — Not Always Faster

Multi-GPU adds CPU overhead (job distribution, per-GPU setup, data gathering). Only effective when GPU is the clear bottleneck.

Scenario Recommendation
High-res (4K) × many cameras (4–8) Multi-GPU effective
Low-res (1080p) × few cameras (1–2) Single GPU faster
CPU-bottlenecked Adding GPUs = pointless

Always verify GPU-bound with Tracy/nsys before adding GPUs.

CPU Governor

# Check
cat /sys/devices/system/cpu/cpu*/cpufreq/scaling_governor | sort | uniq -c
# Fix
echo performance | sudo tee /sys/devices/system/cpu/cpu*/cpufreq/scaling_governor

Real impact: powersave → performance saved ~4 ms/frame in measured cases.

RTX Tuning When GPU-Bound

Recommended Approach

Start from an IsaacLab preset, then selectively re-enable features you need.

IsaacLab Presets (ChessRTX path-traced, RTX PRO 6000 Blackwell)

Preset FPS Δ vs default
(default) 51.85 —
isaaclab_quality 70.25 +35.5%
isaaclab_balanced 87.81 +69.4%
isaaclab_performance 111.90 +115.8%

DLSS execMode — Single Biggest Lever

execMode Mode FPS Δ vs default
0 Performance 106.24 +104.9%
1 Balanced 87.08 +68.0%
2 Quality 71.42 +37.7%
--/rtx/post/dlss/execMode=0  # always specify 0/1/2 — mode 3 (Auto) broken in headless

~91% of isaaclab_performance's gain comes from this single setting.

Full Preset Parameter Table

For detailed per-parameter comparison across all three presets, see references/rtx-presets.md.

Tuning Checklist

  1. Confirm GPU-bound with Tracy/nsys
  2. Verify DLSS-G off for simulation (--/rtx-transient/dlssg/enabled=false)
  3. Set --/rtx/post/dlss/execMode=0 (biggest single lever)
  4. Apply isaaclab_performance preset for maximum speed
  5. Selectively re-enable visual features as needed
  6. Scene-dependent — numbers will vary