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SkillsMP has collected 34 skills from intel/skills. Open a skill to review its source and details.
Showing 34 of 34 collected skills.
Create a CUDA-to-XPU migration assessment for an existing AI repo. Identify CUDA-specific assumptions, route to the right XPU skills, produce a migration report. Use when the user has a CUDA repo, notebook, Dockerfile, launch script, HF / vLLM / SGLang…
Passing dpnp arrays to and from other Python libraries on Intel CPUs and GPUs. Use when dpnp numeric work has to feed pandas, scikit-learn, PyTorch, or TensorFlow, when one of those libraries raises a type error on a dpnp array, when a pipeline mixes device…
Reading and writing files from dpnp code on Intel CPUs and GPUs. Use when the user needs to load an array into dpnp or save a dpnp result — .npy, .npz, HDF5 via h5py, Zarr, CSV or plain text — when a file is larger than device memory and has to be read in…
Linear algebra and FFT with dpnp on Intel CPUs and GPUs, backed by oneMKL. Use when a matrix multiply, solve, decomposition, eigenvalue problem, or Fourier transform is the hot part of NumPy code, when the user asks whether dpnp covers a linalg or FFT call,…
Device memory management for dpnp arrays on Intel CPUs and GPUs. Use when a dpnp script grows in memory until it fails, when a dataset does not fit in device memory, when an array turns out to be on a different device than expected, or when a loop allocates a…
Porting an existing NumPy or CuPy program to dpnp on Intel CPUs and GPUs. Use when deciding whether a codebase can run on dpnp at all, when a call raises NotImplementedError or AttributeError after the import was swapped, when the user asks whether dpnp…
NumPy-compatible array operations optimized for Intel hardware. Use when the user wants to migrate or port NumPy code to dpnp, asks whether a NumPy hot path can run on an Intel CPU or GPU, needs to check dpnp installation or SYCL device selection with dpctl,…
Random number generation with dpnp on Intel CPUs and GPUs, backed by oneMKL. Use when NumPy random calls move to dpnp, when a seeded dpnp run does not reproduce a NumPy sequence, when a distribution turns out not to be implemented, when results have to be…
Diagnosing dpnp failures on Intel CPUs and GPUs. Use when dpnp raises NotImplementedError or an unexpected TypeError, when the import fails or a SYCL runtime library is missing, when no SYCL device is visible, when dpctl reports a device the user did not…
Profile and fix Linux performance problems using `perf`. Workflows: (A) hardware counters -- IPC, cache-miss, branch mispredictions; (B) hotspot profiling -- which functions and source lines consume CPU, with SIMD and accumulator detection; (C) cache-line…
Run a GGUF model on an Intel GPU using llama.cpp's SYCL backend (Level Zero) with the official intel.Dockerfile. Covers building the Docker image from source at a pinned tag, launching llama-server with an OpenAI-compatible API, device selection, multi-GPU…
Deciding whether Intel's MKL extension packages apply to NumPy or SciPy code on Intel CPUs. Use when a user asks whether mkl_fft, mkl_random, or mkl_umath help their code, or points at a snippet, function, file, or codebase using np.fft, scipy.fft, np.random,…
Estimate whether a Hugging Face decoder-only LLM, MoE, or VLM fits in Intel GPU VRAM for a quantization, context length, concurrency, runtime, and tensor-parallel setting. Use for memory-fit or max-model-len planning before launch. Reports weights, KV cache,…
Recommend a vLLM-XPU deployment config (quant, KV dtype, DP/TP, max concurrency, max context) for a Hugging Face decoder-only LLM on Intel Arc B-series GPUs using roofline math against published hardware specs. Experimental; predictions are physics-bounded…
Getting started with Intel oneTBB for C++ parallelism on Intel CPUs. Use when a C++ loop or reduction should run on multiple threads with oneTBB, when the user needs the headers, namespace, or CMake wiring for a first oneTBB program, when a parallel_for body…
Detect and fix x86/C/C++ performance patterns from source code or profiling output (perf, VTune, flamegraphs). Invoke when the user asks to optimize, review for performance, or write new SIMD/vectorized code — even without profiling data. Trigger on: serial…
Install, run, parse, and optimize benchmarks from the Phoronix Test Suite (PTS). Use this skill whenever the user mentions "phoronix", "pts/", or "phoronix-test-suite", or asks to run, measure, improve, or optimize a PTS test — e.g., "run pts/mt-dgemm",…
Benchmark a **running SGLang-XPU server** on an Intel GPU using `sglang.bench_serving`. Measures TTFT, TPOT, ITL, end-to-end latency, and throughput against the OpenAI-compatible endpoint. Use after sglang-xpu-run. Not for vLLM servers (use vllm-xpu-bench) or…
Serve a Hugging Face safetensors model on an Intel GPU using SGLang's XPU backend with the OpenAI-compatible API. Covers pulling the pre-built `intel/sglang-dev:latest` image, fixing the render-group and UMD/kernel compatibility issues that affect non-root…
Benchmark a Hugging Face model on an Intel GPU through pure PyTorch + Transformers, **single-process, no HTTP server**. Measures generate() throughput in tokens/sec, time-to-first-token, decode-step latency, and peak XPU memory. Also covers diffusion and…
Profile a Hugging Face model on Intel GPU at the **PyTorch level** with `torch.profiler` and Kineto. Captures CPU + XPU timeline, exports Chrome trace, identifies hottest kernels and async-overlap gaps. Use when the user asks why a model is slow, which op is…
Run an arbitrary Hugging Face safetensors model on an Intel GPU using **upstream PyTorch** (>= 2.8) with the built-in `torch.xpu` device. Covers loading from the Hub, picking the right dtype, autocast, multi-GPU with accelerate's `device_map`, and the CUDA ->…
Benchmark a **running vLLM-XPU OpenAI-compatible server** on an Intel GPU using `vllm bench`. Measures TTFT (time-to-first-token), TPOT (time-per-output-token), ITL (inter-token latency), end-to-end latency, and throughput under concurrency. Covers online…
Profile a running vLLM-XPU server with torch.profiler around a window of real requests, either via /start_profile and /stop_profile HTTP endpoints or via vllm bench --profile for offline runs. Use to find the dominant op under real concurrent traffic. Not for…
Serve a Hugging Face safetensors model on an Intel GPU with upstream vLLM-XPU's OpenAI-compatible API. Covers image choice, container launch, the right vllm serve flags (dtype, enforce-eager, model-impl fallback, attention backend, quant + KV-cache pairing),…
Launch a Docker container with Intel GPU access on Linux. Encodes the correct combination of `--device /dev/dri`, render-group access, `--ipc=host`, `ZE_AFFINITY_MASK` pinning, Hugging Face cache mount, and `--entrypoint /bin/bash` for interactive use. Use…
Plan an end-to-end Intel XPU model deployment by chaining existing skills. Calls xpu-runtime-preflight (readiness), model-can-it-fit (sizing), model-config-recommend (flags), and the selected runtime skill (vllm-xpu-run / sglang-xpu-run / torch-xpu-run), then…
Inventory Intel GPUs (Arc, Arc Pro, Data Center GPU Max) on a Linux host. Detect devices, check driver health, list processes using each XPU, run a quick diagnostic, and read live utilisation.
Before loading a Hugging Face model on Intel XPU, detect its actual type (text generation, text encoder, seq2seq, vision classification, vision-language, audio encoder, audio seq2seq, multimodal VL, diffusion, time-series, reward model, masked LM) so the…
Execute a single-target CUDA-to-XPU port of a PyTorch repo with libcst-based scan, mechanical rewrite, and CPU FP64 vs target-dtype correctness verify on one forward pass. Use when the request says "port" — "port my repo to XPU", "port my repo at <path> to…
Profile Intel-XPU workloads at the SYCL / Level Zero kernel level via Intel pti-gpu's unitrace. Captures per-API-call and per-kernel timing, memory transfers, oneCCL / MPI events, and hardware counters PyTorch-level profilers cannot see. Use when a hot op is…
Run a read-only go/no-go preflight before any Intel GPU/XPU skillpack work. Checks driver health, /dev/dri permissions, render/video groups, Docker, /dev/shm, disk, proxy, and optional container-level XPU visibility. Use when the user asks whether a machine…
First-time setup for Intel XPU/GPU hosts. Detects what's missing and installs xpu-smi, configures user groups (render), sets up Intel GPU PPA repository, installs Level Zero runtime, installs Docker, and runs a post-setup verification gate. Prompts before…
What this skill covers, and when an agent should load it. Write it in the words a user would type, not the canonical product name, and say what it is not for. Two or three sentences: the descriptions in this catalog run 450-600 characters, and 1024 is the…