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SiliconScope

Release Downloads License: MIT Platform

A sudoless Apple Silicon system monitor with a native SwiftUI GUI — and first-class ANE (Neural Engine), Media Engine, and memory-bandwidth tracking that terminal monitors and Activity Monitor don't surface.

Born from wanting to see exactly how on-device AI and media workloads drive the Apple Silicon accelerators — hence the focus on ANE / Media / bandwidth.

SiliconScope catching a GPU thermal throttle under a local-LLM load

A sustained on-device LLM (MLX-Swift) pinning the GPU — SiliconScope catches the thermal throttle (banner + the menu-bar glyph blinks red), shows the per-engine trends, and attributes it honestly as in-app / unmanaged (no managed runtime serving a model).

SiliconScope dashboard and menu-bar cockpit

The full dashboard plus the menu-bar cockpit: a live 6-bar glyph (CPU / GPU / ANE / Media / memory / bandwidth) and six color-matched per-engine trend graphs — each on a fixed axis so a small signal reads small.

Install

⬇ Download the latest DMG, then:

  1. Open the downloaded SiliconScope-*.dmg
  2. Drag SiliconScope into Applications
  3. Launch it

Signed with a Developer ID and notarized by Apple — it opens with no Gatekeeper prompt. Requires macOS 14+ on Apple Silicon.

Prefer to build it yourself? See Build & run.

Highlights

  • AI Workload view — a bottleneck classifier (bandwidth-bound / compute-bound / thermal-throttled / memory-pressured) with a per-chip "% of ceiling" bandwidth gauge — answers "what's limiting my local LLM right now?"
  • E-core / P-core split — per-cluster utilization + real DVFS frequency
  • GPU — utilization, power, frequency
  • ANE & Media Engine — Neural-Engine power and media-codec bandwidth (the differentiators)
  • Memory bandwidth — CPU / GPU / Media / total GB/s (the local-LLM bottleneck signal)
  • Memory — Wired / Active / Compressed / Free stacked bar + macOS memory-pressure alerts
  • Network ↑/↓ and Disk read/write + free space, with live graphs
  • Temperatures — grouped CPU / GPU / Memory / Battery (SMC), fan RPM, thermal pressure, and GPU throttle detection (clock held below its rolling peak under pressure)
  • Power — per-domain CPU / GPU / ANE / DRAM / SoC, plus battery %
  • Processes — sort, filter, kill (in-card scroll)
  • No sudo required. Full dashboard and menu-bar mode (with a compact GPU readout).

Build & run

Requires macOS on Apple Silicon and the Xcode toolchain.

xcrun swift run SiliconScope        # SwiftUI GUI (dashboard + menu bar)
xcrun swift run -q sscope-cli       # data-layer verification CLI
xcrun swift build                   # build everything
scripts/build-app.sh                # create dist/SiliconScope.app locally
open dist/SiliconScope.app          # launch the local app bundle

Use xcrun. A non-Xcode swift (e.g. swiftly) may not match the macOS SDK and will fail with Failed to build module 'Foundation'.

How it works (all sudoless)

Data Source
Power (CPU/GPU/ANE/DRAM), residency, memory bandwidth private IOReport framework (symbols resolved at runtime via dyld)
CPU usage host_processor_info ticks (matches Activity Monitor)
CPU/GPU frequency IOReport CPU Stats / GPU Stats × IORegistry DVFS table
Memory / swap / pressure host_statistics64, sysctl
Temperatures, fans SMC via IOKit
Network / Disk / Battery getifaddrs, IOBlockStorageDriver, IOPowerSources
Processes libproc

Verified IOReport channel map: docs/ioreport-channels.md. Display spec: docs/display-spec.md.

Not on the Mac App Store

SiliconScope uses private (un-entitled) APIs (IOReport, SMC, HID), so it cannot be sandboxed/notarized for the App Store. Distribute directly. This is the same trade-off as NeoAsitop, macmon, mactop, and Stats.

Acknowledgements

  • IOReport / SMC / sensor knowledge referenced from NeoAsitop (MIT) and SocPowerBuddy; sensor naming informed by Stats. The data layer here is written from scratch — declarations/facts referenced, no code copied.
  • Design language inspired by btop.

License

MIT © 2026 Kennt Kim — see LICENSE.

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Sudoless Apple Silicon system monitor (native SwiftUI GUI) with ANE / Media Engine / memory-bandwidth tracking

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