Results for “gpu-evaluation”

Detect and validate GPU availability for MATLAB GPU computing. Use when the user can't use their GPU, or is setting up or selecting a GPU. Triggers on: gpuDevice, GPU setup, check GPU, GPU not found, GPU not working, can't use GPU, GPU not available, unable to find a supported GPU device, compatible GPU, canUseGPU, validateGPU.

Diagnose frame-rate bottlenecks (CPU vs GPU bound FIRST), control Unreal Insights traces, sample live frame times, and annotate performance captures. Use when FPS is low/bad, the game is slow, or you need to find what is limiting the frame rate.

Build, optimize, backtest, rebalance, or analyze stock portfolios using NVIDIA-accelerated Mean-CVaR optimization with cuOpt GPU solver.

Diagnose and improve MSBuild project evaluation performance by analyzing phases, glob patterns, import chains, and property functions.

KINTSUGI NOTEBOOK processing principles: Never sacrifice quality for speed, always use GPU when available. Trigger: performance optimization, CPU/GPU choice, fast mode, quality vs speed in NOTEBOOKS (not SLURM).

Systematically profile Node.js, Python, and Go applications to identify CPU, memory, and I/O bottlenecks, generate flamegraphs, analyze bundle sizes, optimize database queries, and run load tests with k6 and Artillery.

Performance regression detection using the browse daemon. (gstack)

Web browser game development principles. Framework selection, WebGPU, optimization, PWA.

PC and console game development principles. Engine selection, platform features, optimization strategies.

GPU-accelerated correlation matrix computation with persistent SQLite caching to eliminate bottleneck at correlation calculation during symbol selection

Performance Profiler

Analyzes game balance by extracting stats from code and running mathematical simulations, including DPS tier lists, TTK matrices, EHP comparisons, economy stress tests, progression pacing, and Monte Carlo RNG simulations.

GPU-aware PPO training configuration for A100/H100. Trigger when training is slow or GPU utilization is low.

Performance regression detection using the browse daemon. Establishes baselines for page load times, Core Web Vitals, and resource sizes. Compares before/after on every PR. Tracks performance trends over time. Use when: "performance", "benchmark", "page speed", "lighthouse", "web vitals", "bundle size", "load time". (gstack) Voice triggers (speech-to-text aliases): "speed test", "check performance".

Analyzes game AI systems in a codebase, covering behavior trees, finite state machines, GOAP, utility AI, pathfinding, steering, perception, difficulty adaptation, NPC dialogue, and AI debugging tools for Unity, Unreal, and Godot projects.

Weekly engineering retrospective. (gstack)

Profile and optimize CPU, memory, GC, and rendering performance for mobile QuizVerse.

Profile a target (script, process, GPU, memory, interconnect) using external tools and code instrumentation. Produces structured performance reports with actionable recommendations. Use when user says "profile", "benchmark", "bottleneck", or wants performance analysis.

Design and execute performance benchmarks for models and systems. Use when measuring throughput, latency, or comparing system variants.

Guides engine selection and platform-specific principles for PC and console game development, covering Steam integration, controller support, and performance optimization.

Analyze auto-memory for promotion candidates, stale entries, consolidation opportunities, and health metrics. Use when the user runs /si:review or asks what has been learned and what should be promoted or pruned.