「gpu」の検索結果

Rowan is a cloud-native molecular modeling and medicinal-chemistry workflow platform with a Python API. Use for pKa and macropKa prediction, conformer and tautomer ensembles, docking and analogue docking, protein-ligand cofolding, MSA generation, molecular dynamics, permeability, descriptor workflows, and related small-molecule or protein modeling tasks. Ideal for programmatic batch screening, multi-step chemistry pipelines, and workflows that would otherwise require maintaining local HPC/GPU infrastructure.

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Access a collection of open-source molecular design and structural biology tools on the Tamarind Bio platform, via its REST API or MCP server — no local GPUs required. Tamarind bundles popular open-source models for structure prediction (AlphaFold, Boltz, Chai, ESMFold), protein, binder, and de novo design (RFdiffusion, ProteinMPNN, BoltzGen), antibody and nanobody design and developability, protein-ligand docking (DiffDock, Autodock Vina), binding-affinity prediction, MSA generation, and molecular dynamics. Use when the user mentions Tamarind or tamarind.bio, wants to run any of these open-source tools in the cloud, references app.tamarind.bio/api or the x-api-key header, or needs to submit batches of sequences for structural or biophysical characterization.

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Use when debugging CUDA with cuda-gdb or Compute Sanitizer, reading GPU core dumps, using device printf, or triaging error codes 700, 701, 702, and 719. Not for performance: use cuda-profiling.

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Use when a rendering path needs stable frame-time, CPU, GPU, and memory evidence against fixed targets. Not for one-shot profiling or visual quality review.

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Compares two Prof datasets (GPU vs NPU / NPU vs NPU) by auto-installing and calling msprof-analyze compare, then parses the result xlsx into HTML report and Chinese xlsx. Invoke when user provides two prof dirs to compare, or has a compare result xlsx to analyze/translate.

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Build terminal UIs with OpenTUI. Covers core, components, audio, keymaps, React, Solid, plugins, testing, standalone executables, QR encoding, SSH, and Three.js WebGPU.

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Use when writing Swift code for Apple platforms - iOS, macOS, visionOS. Covers Swift 6 concurrency, actors, Sendable, async/await, SwiftUI, MVVM architecture, Metal GPU programming, RealityKit ECS, visionOS scenes, interpolation/animation, advanced collection types, property wrappers, Combine bridging, error handling, testing, and API design patterns.

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

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MATLAB R2026a code generation and deployment workflow for MATLAB Coder, Simulink Coder, Embedded Coder, GPU Coder, HDL Coder, fixed-point conversion, MEX validation, and embedded deployment readiness. Use whenever the user asks to generate C/C++/CUDA/HDL/code, deploy algorithms, or validate generated code.

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GPU-optimized OCR using Surya. Use when extracting text from images/screenshots, recovering image-only content in PDFs or slides, or inspecting multilingual document layouts. Preserve source locations and report recognition gaps separately from verified text.

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Use when setting up or troubleshooting Waydroid on Linux - installation and initialization, waydroid CLI, GPU and networking setup, GApps and Play certification, ADB integration, file sharing, or desktop environment integration

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React Native Skia GPU-accelerated 2D graphics - Canvas, declarative drawing, shaders, image filters, Paragraph text, Atlas batch rendering, Reanimated animations

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SQL discipline for querying Pulp Perfetto traces (.pftrace) with trace_processor — idempotent CREATE OR REPLACE PERFETTO views, GLOB not LIKE, dur = -1 incomplete-slice handling, EXTRACT_ARG for span args, joining on stable utid/upid, SPAN_JOIN PARTITIONED, and the draft→validate→execute loop. Ships Pulp's CPU/UI trace stdlib plus closed GPU startup, health, and probe views. TRIGGER when writing or debugging SQL over a .pftrace, when `pulp trace query` returns wrong/empty rows, or when the trace-analysis skill needs a query primitive.

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Build or iterate on Pulp's native Dawn-backed Three.js workflow using the real three.webgpu.js renderer, focused bridge tests, and native demo capture.

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Android platform development for Pulp — NDK cross-compilation, Oboe audio, Dawn/Skia GPU rendering, JNI bridge, touch interaction, emulator workflows, and end-to-end smoke validation. Covers build, deploy, debug, and the gotchas discovered during bringup.

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Update Pulp's pinned Skia, Dawn, and optional V8 prebuilts as one milestone-matched render-toolchain release. Use for requests such as "update Skia/Dawn", "move to chrome/mNNN", "find the matching V8", "update the GPU toolchain", or "use the Skia/Dawn/V8 tuple that goes together". Distinguishes milestone-matched V8 releases from v8-builder's newer weekly LKGR releases, verifies exact upstream provenance and asset hashes, updates every Pulp mirror, and runs the provider-identity/ODR gates.

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Capture faithful PNGs of Pulp view trees / imported UIs headlessly. Covers render_to_png backends (Skia vs CoreGraphics), the image-compositing gotcha, capture_png from a live GPU host, and the --screenshot-backend validate flag. Use whenever you render a UI to a PNG to eyeball or montage it.

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Unity 6 graphics and rendering guide. Use when working with render pipelines (URP, HDRP, Built-in), shaders, Shader Graph, materials, textures, cameras, post-processing, or rendering optimization. Covers Render Graph, batching, draw call optimization, and GPU instancing. Based on Unity 6.3 LTS documentation.

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用于构建或审查 Canvas 2D、Three.js/WebGL、React Three Fiber、GLSL shader、ShaderToy 到 WebGL 适配、2D/3D 可视化、游戏渲染、动画循环、GPU 资源清理或渲染性能。不要用于标准 DOM UI、已有图表库覆盖的图表或非图形类性能工作；中文触发词包括 Canvas、Three.js、WebGL、GLSL、Shader、3D、数据可视化、游戏。

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Use when building or reviewing Canvas 2D, Three.js/WebGL, React Three Fiber, GLSL shaders, ShaderToy-to-WebGL adaptation, 2D/3D visualization, game rendering, animation loops, GPU resource cleanup, or rendering performance. Do not use for standard DOM UI, charts already covered by a chart library, or non-graphical performance work; Chinese triggers include Canvas, Three.js, WebGL, GLSL, Shader, 3D, data visualization, games.

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Access ENCODE uniform analysis pipelines, generate user-specific Nextflow/WDL pipelines, manage compute resources, and integrate with cloud platforms. Use when the user wants to understand ENCODE pipelines, run pipelines on their own data, generate custom Nextflow workflows from ENCODE pipeline code, check compute requirements (CPU/GPU/memory), run pipelines in background, or integrate with Google Cloud, AWS, or other cloud platforms. Also use when the user asks about ENCODE pipeline outputs, processing standards, software versions, or wants to replicate ENCODE processing. Covers local execution, HPC, and cloud deployment with resource-aware scheduling. Use this skill for ANY pipeline execution, workflow generation, or compute resource management task involving ENCODE data.

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Use when working on SAM 3 video segmentation, vaila_sam.py, checkpoint handling, or GPU memory issues.

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Use when working on the SAM3 plus Sapiens2 pose estimation pipeline, batch GPU processing, or VRAM and throughput issues.

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Plans, executes, and validates Google Kubernetes Engine (GKE) cluster upgrades and maintenance operations for both Standard and Autopilot clusters. Produces upgrade plans, pre/post-upgrade checklists, maintenance runbooks with gcloud commands, release channel strategy, and troubleshooting guides. Handles node pool upgrade strategies (surge, blue-green), version compatibility, PDB management, and workload-specific concerns (stateful, GPU, operators). Use this skill whenever the user mentions GKE upgrades, Kubernetes version bumps, node pool maintenance, GKE patching, cluster version management, release channel selection, maintenance windows, surge upgrades, stuck upgrades, or any GKE lifecycle management task — even casual mentions like "we need to upgrade our clusters" or "plan our next GKE maintenance" or "our upgrade is stuck." Don't use for GKE cluster creation, application onboarding, general networking/routing setup, or security policy configurations (use gke-basics or relevant GKE skills instead).

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。