XPUSYS-Monitor-NG/CHANGELOG.md

Changelog — XPUSYS-Monitor-NG

All notable changes for the Windows-native AMD ROCm port are documented here.

This fork is based on ComfyUI-XPUSYS-Monitor v1.0.3 by allanmeng. The version below tracks deviations from that baseline.

---

v0.1.0 — 2026-06-08

Intent

The upstream AMD provider (providers/amd.py) relied on rocm_smi_lib — a Linux-only Python package that wraps librocm_smi64.so. On Windows with AMD ROCm, pip install rocm_smi_lib fails because the native .so library does not exist. This port replaces every rocm_smi call with a Windows-native alternative.

Detection: providers/__init__.py

Problem: The upstream detection function _is_amd_rocme() accessed torch.version.roc directly. On Windows AMD ROCm builds (tested with PyTorch 2.9.1+rocm7.2.1), the roc attribute does not exist on the torch.version module — raising AttributeError. The outer try/except caught it and returned False, causing the auto-detector to load NvidiaProvider instead of AMDProvider. The GPU name fallback code after the roc check was unreachable.

Fix: Replaced bare attribute access with getattr(torch.version, 'roc', None). Added a secondary signal getattr(torch.version, 'hip', None) for HIP-based detection. Added a tertiary fallback scanning the GPU device name (via torch.cuda.get_device_name(0)) for the markers "amd", "radeon", or "advanced micro devices".

VRAM: providers/amd.py → _read_vram()

Problem: The upstream AMD provider used rocm_smi.getMemFreeVdev(0), rocm_smi.getMemSizeVdev(0), and rocm_smi.getMemUsedVdev(0) for driver-level VRAM reads. Without rocm_smi_lib, the fallback returned only total VRAM from torch.cuda.get_device_properties(0).total_memory, leaving free and driver_used as 0.0 — making the PRED predictor and VRAM capsule unusable.

Fix: Replaced all three rocm_smi VRAM calls with torch.cuda.mem_get_info(device_index), which returns (free_bytes, total_bytes) from the AMD driver on ROCm 6+ for Windows. Moved the call inside a try/except with a fallback to get_device_properties().total_memory if mem_get_info is unavailable. Added torch.cuda.synchronize() before reads to force CUDA/HIP context creation (some ROCm builds defer context init until the first GPU operation, returning zeros otherwise).

GPU Load: providers/amd.py → _read_gpu_load()

Problem: The upstream used rocm_smi.getGpuBusyVdev(0). No standard Python-accessible equivalent exists on Windows AMD.

Solution attempted — PDH (ctypes): Added _PdhQuery to providers/_utils.py using ctypes wrappers around pdh.dll to query \GPU Engine(*)\Utilization Percentage. The wildcard counter path does not aggregate correctly with PdhGetFormattedCounterValue (returns only the first matching instance). This approach was disabled for AMD in favour of typeperf.

Solution adopted — typeperf: Added _TypeperfGpuQuery to providers/_utils.py. Uses Windows built-in typeperf.exe (available since Vista) with the same counter path \GPU Engine(*)\Utilization Percentage. Output is CSV; we parse columns after the timestamp and take max() across all engine instances. Averaging would dilute the signal (hundreds of engine columns including idle video/copy/timer). max() correctly reflects the busiest engine (typically 3D or Compute during a ComfyUI workflow). At idle all engines report ~0%, so the capsule drops cleanly.

Attempted — amdsmi: Added _AmdSmiGpuQuery to providers/_utils.py using the official AMD SMI Python library (pip install amdsmi). On Windows the library searches for libamd_smi.so (a Linux shared object) at D:\opt\rocm\lib\, which does not exist on the tested configuration. The class logs a single info line and gracefully skips if amdsmi is not installed or fails to load.

GPU Frequency / Temperature / Power: providers/amd.py

Problem: The upstream used rocm_smi.getSingleClockSpeed(0), rocm_smi.getTempVdev(0), rocm_smi.getPowerVdev(0), and rocm_smi.getPowerCapVdev(0) for clock speed, temperature, and power draw. The AMD Windows WDDM driver on the RX 9070 XT does not register these performance counters through any standard Python-accessible interface.

Resolution: All three return sentinel values matching the GPUSnapshot contract defaults — 0.0 for frequency, -1.0 for temperature, (-1.0, 0.0, False) for power. The frontend displays these as unavailable (-- / greyed out), identical behaviour to when the Intel provider cannot open Level Zero handles or the NVIDIA provider cannot reach pynvml.

Shared Utilities: providers/_utils.py (new file)

Problem: The upstream AMD provider imported system-level CPU and RAM utility functions (_get_cpu_info, _read_cpu_ram_stats, _read_commit_charge) from providers/intel.py. This created a spurious dependency on the Intel Level Zero provider code for non-Intel users.

Fix: Extracted these three functions plus _is_admin() into a new shared module providers/_utils.py. Also relocated _PdhQuery, _TypeperfGpuQuery, and _AmdSmiGpuQuery into the same module. Both amd.py and nvidia.py now import from _utils.py instead of intel.py. The intel.py module is no longer needed unless the Intel provider is loaded (auto-detection fallback path).

NVIDIA Provider: providers/nvidia.py

Change: Updated import path from from .intel import ... to from ._utils import .... No functional change — identical utility functions.

Frontend: web/xpu_monitor.js

Problem: The __init__.py declares WEB_DIRECTORY = "./web" which tells ComfyUI to serve the JavaScript toolbar extension from a web/ subdirectory. This directory was not included in the initial workspace, causing the toolbar capsules to not render.

Fix: Added web/xpu_monitor.js (56 KB, identical to upstream v1.0.3). The file is the full JavaScript frontend that renders the seven-capsule status bar, handles WebSocket updates from the backend, and provides the VRAM predictor UI. No modifications were made.

Dependencies: requirements.txt

Change: rocm_smi_lib commented out with an explanatory note. No replacement dependency added — VRAM reads use torch.cuda (bundled with the ROCm PyTorch installation), GPU load reads use typeperf (Windows built-in), and CPU/RAM reads use psutil (already required by the upstream).

Project Metadata: pyproject.toml

Changes:

• Repository URL updated to https://github.com/forkless/XPUSYS-Monitor-NG
• Display name set to XPUSYS-Monitor-NG
• Description updated to reflect the POC nature
• Publisher ID set to forkless

Documentation

• README.md — rewritten for the fork with POC context, status table, relationship to upstream, tested hardware, support disclaimer, MIT license
• AMD.md — detailed technical summary of every change, intent, and end result table
• LICENSE.md — MIT license (matches upstream)