torch-xpu-profile SKILL.md skillA
torch-xpu-profile from intel/skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add intel/skills/torch-xpu-profile@git:20260903.b1ad034Pins git:20260903.b1ad034 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- intel/skills
- Path
skills/torch-xpu-profile/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260903.b1ad034, committed Sep 3, 2026
- Size
- 5,327 bytes
- Repository stars
- 29
- License
- Apache-2.0
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 the bottleneck, or where the GPU is idle. Not for profiling inside a running vLLM server (use vllm-xpu-profile) or for SYCL-kernel-level signal beneath the PyTorch op layer (use xpu-profile-unitrace).
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# torch-xpu-profile
`torch.profiler` with `ProfilerActivity.XPU` captures CPU + XPU op
timeline on Kineto. Use for "which `aten::*` op is slow?", "is
the GPU idle?", "is decode kernel-bound?". For server-side
profiling use **vllm-xpu-profile**; for SYCL kernel level use
**xpu-profile-unitrace**.
## CUDA -> XPU translation
| CUDA | XPU |
|---|---|
| `ProfilerActivity.CPU, ProfilerActivity.CUDA` | `ProfilerActivity.CPU, ProfilerActivity.XPU` |
| `prof.export_chrome_trace("trace.json")` | identical |
| `record_shapes=True, with_stack=True` | identical |
| `prof.key_averages().table(sort_by="cuda_time_total")` | `sort_by="xpu_time_total"` |
## Quickstart
```python
import torch
from torch.profiler import profile, ProfilerActivity, schedule
from transformers import AutoModelForCausalLM, AutoTokenizer
mid = "Qwen/Qwen2.5-1.5B-Instruct"
tok = AutoTokenizer.from_pretrained(mid)
model = AutoModelForCausalLM.from_pretrained(
mid, dtype=torch.bfloat16, device_map="xpu"
).eval()
inp = tok("Tell me a joke.", return_tensors="pt").to("xpu")
# Warmup so first-run kernel compile doesn't pollute the trace
with torch.no_grad():
model.generate(**inp, max_new_tokens=8, do_sample=False,
…Read the whole file at its exact version.
How to install
mdr add intel/skills/torch-xpu-profile@sha256:3f9229b37ec34943The line at the top of this page pins the label git:20260903.b1ad034, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_f6tjumck6ngxwmde)
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Versions
The registry has recorded 1 version of this file, committed on Sep 3, 2026.
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (5327 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
intel/skills · 29 stars · license Apache-2.0 · pushed 2026-11-06 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_f6tjumck6ngxwmde GET https://markdownregistry.com/api/v1/resolve?ref=intel/skills/torch-xpu-profile GET https://markdownregistry.com/api/v1/blob/3f9229b37ec34943dc8f749153e2fe63f22a029583ca19ca252f2fba4d70e7b6
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.