564 件 ・ 関連度順
概要と使いどころ
A distinctive GPU shader background rendered in dependency-free WebGL — a marketing-grade hero backdrop. One per view; scrim behind text. Renders a static frame under prefers-reduced-motion.
日本語の概要は準備中です。原文の説明を表示しています。
A distinctive GPU shader background rendered in dependency-free WebGL — a marketing-grade hero backdrop. One per view; scrim behind text. Renders a static frame under prefers-reduced-motion.
日本語の概要は準備中です。原文の説明を表示しています。
A distinctive GPU shader background rendered in dependency-free WebGL — a marketing-grade hero backdrop. One per view; scrim behind text. Renders a static frame under prefers-reduced-motion.
日本語の概要は準備中です。原文の説明を表示しています。
A living GPU shader background rendered in dependency-free WebGL — a distinctive, marketing-grade hero backdrop. One per view; put a scrim behind text. Renders a static frame under prefers-reduced-motion.
日本語の概要は準備中です。原文の説明を表示しています。
A distinctive GPU shader background rendered in dependency-free WebGL — a marketing-grade hero backdrop. One per view; scrim behind text. Renders a static frame under prefers-reduced-motion.
日本語の概要は準備中です。原文の説明を表示しています。
A distinctive GPU shader background rendered in dependency-free WebGL — a marketing-grade hero backdrop. One per view; scrim behind text. Renders a static frame under prefers-reduced-motion.
日本語の概要は準備中です。原文の説明を表示しています。
A distinctive GPU shader background rendered in dependency-free WebGL — a marketing-grade hero backdrop. One per view; scrim behind text. Renders a static frame under prefers-reduced-motion.
日本語の概要は準備中です。原文の説明を表示しています。
A distinctive GPU shader background rendered in dependency-free WebGL — a marketing-grade hero backdrop. One per view; scrim behind text. Renders a static frame under prefers-reduced-motion.
日本語の概要は準備中です。原文の説明を表示しています。
A distinctive GPU shader background rendered in dependency-free WebGL — a marketing-grade hero backdrop. One per view; scrim behind text. Renders a static frame under prefers-reduced-motion.
日本語の概要は準備中です。原文の説明を表示しています。
A retro Bayer-dithered noise wave — pixelated, quantized, faithful GPU shader. A marketing-grade hero backdrop. One per view; scrim behind text. Renders a static frame under prefers-reduced-motion.
日本語の概要は準備中です。原文の説明を表示しています。
A distinctive GPU shader background rendered in dependency-free WebGL — a marketing-grade hero backdrop. One per view; scrim behind text. Renders a static frame under prefers-reduced-motion.
日本語の概要は準備中です。原文の説明を表示しています。
A living GPU shader background rendered in dependency-free WebGL — a distinctive, marketing-grade hero backdrop. One per view; put a scrim behind text. Renders a static frame under prefers-reduced-motion.
日本語の概要は準備中です。原文の説明を表示しています。
A distinctive GPU shader background rendered in dependency-free WebGL — a marketing-grade hero backdrop. One per view; scrim behind text. Renders a static frame under prefers-reduced-motion.
日本語の概要は準備中です。原文の説明を表示しています。
Expert blueprint for HTML5/web export on Compatibility (WebGL 2.0): JavaScriptBridge, localStorage wrapper, custom loading shells, COOP/COEP hosts, relative paths, beforeunload, visibility pause, and size optimization. WebGPU is out of scope. Keywords: web, HTML5, WebGL, Compatibility, JavaScriptBridge, localStorage, COOP, COEP, canvas, browser API.
日本語の概要は準備中です。原文の説明を表示しています。
Expert patterns for porting desktop games to mobile including touch control schemes (virtual joystick, gesture detection), UI scaling for small screens, performance optimization for mobile GPUs, battery life management, and platform-specific features. Use when creating mobile ports or cross-platform mobile builds. Trigger keywords: TouchScreenButton, virtual_joystick, gesture_detector, InputEventScreenTouch, InputEventScreenDrag, mobile_optimization, battery_saving, adaptive_performance, MOBILE_ENABLED.
日本語の概要は準備中です。原文の説明を表示しています。
Bevy ECS skill for web and Wasm. Keywords: Bevy, wasm, web, webgl2, webgpu, browser.
日本語の概要は準備中です。原文の説明を表示しています。
Use when implementing particle effects — GPUParticles2D/3D, ParticleProcessMaterial, emission shapes, subemitters, trails, attractors, collision, and common VFX recipes
日本語の概要は準備中です。原文の説明を表示しています。
Expert knowledge for Azure Stack Edge development including troubleshooting, best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when deploying IoT Edge modules, GPU/Kubernetes apps, DeepStream workloads, Arc GitOps, or local ARM integrations, and other Azure Stack Edge related development tasks. Not for Azure IoT Edge (use azure-iot-edge), Azure Kubernetes Service (AKS) (use azure-kubernetes-service), Azure Kubernetes Service Edge Essentials (use azure-aks-edge-essentials), Azure Virtual Machines (use azure-virtual-machines).
日本語の概要は準備中です。原文の説明を表示しています。
Expert knowledge for Azure Virtual Machines development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when choosing VM/VMSS sizes, configuring disks/GPU/InfiniBand, using ADE/CMK, Trusted Launch, or Oracle/HPC workloads, and other Azure Virtual Machines related development tasks. Not for Azure Data Science Virtual Machines (use azure-data-science-vm), SQL Server on Azure Virtual Machines (use azure-sql-virtual-machines), Azure Virtual Machine Scale Sets (use azure-vm-scalesets), Azure Virtual Desktop (use azure-virtual-desktop).
日本語の概要は準備中です。原文の説明を表示しています。
Expert knowledge for Azure Kubernetes Service (AKS) development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when securing AKS with Entra/RBAC, configuring Fleet, GPUs or Wasm, AI/ML workloads, or Istio/KEDA autoscaling, and other Azure Kubernetes Service (AKS) related development tasks. Not for Azure Container Apps (use azure-container-apps), Azure Container Instances (use azure-container-instances), Azure Container Registry (use azure-container-registry), Azure Red Hat OpenShift (use azure-redhat-openshift).
日本語の概要は準備中です。原文の説明を表示しています。
Expert knowledge for Azure Lab Services development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring lab plans, VM templates/schedules, VNet-integrated labs, GPU/nested virtualization, or Canvas/Teams integration, and other Azure Lab Services related development tasks. Not for Azure DevTest Labs (use azure-devtest-labs), Azure Virtual Machines (use azure-virtual-machines), Azure Virtual Desktop (use azure-virtual-desktop).
日本語の概要は準備中です。原文の説明を表示しています。
Expert knowledge for Azure Data Science Virtual Machines development including troubleshooting, decision making, architecture & design patterns, security, configuration, integrations & coding patterns, and deployment. Use when managing DSVM images/tools, IaC deployment (Bicep/ARM), Key Vault secrets, MLflow, or GPU/Jupyter issues, and other Azure Data Science Virtual Machines related development tasks. Not for Azure Virtual Machines (use azure-virtual-machines), Azure Machine Learning (use azure-machine-learning), Azure Databricks (use azure-databricks), Azure HDInsight (use azure-hdinsight).
日本語の概要は準備中です。原文の説明を表示しています。
Expert knowledge for Azure Container Instances development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, and deployment. Use when configuring ACI standby pools, static IP networking, GPU containers, secure ACR pulls, or GitHub Actions deploys, and other Azure Container Instances related development tasks. Not for Azure Container Apps (use azure-container-apps), Azure Kubernetes Service (AKS) (use azure-kubernetes-service), Azure App Service (use azure-app-service), Azure Virtual Machines (use azure-virtual-machines).
日本語の概要は準備中です。原文の説明を表示しています。
Provides guidance for writing, optimizing, and benchmarking Triton kernels for Intel XPU GPUs (Battlemage/Arc Pro B50) using the Xe-Forge optimization framework. Includes an LLM-driven trial-loop workflow (analyze, validate, benchmark, profile, finalize), XPU-specific patterns (tensor descriptors, GRF mode, tile swizzling), KernelBench fused kernels, and Flash Attention.
日本語の概要は準備中です。原文の説明を表示しています。