Docs v0.81.0 — Accelerator Bridge (Intel NPU + vendor plugin model)

v0.81.0 — Accelerator Bridge (Intel NPU + vendor plugin model)

v0.84+: Lucy lives in lucy_bloom_rivers (was loom/lucy/). Log and harness paths below are relative to the Lucy repo root.

Release: 0.80.0 "Native Ship" → 0.81.0 "Accelerator Bridge"
Checklist: 112 / 146 (76.7%) on adjustments — Intel forward dispatch advances Accelerators & Distributed (experimental)

First public vendor accelerator path: Loom forwards individual layers through poly/accel into chaosglue-built plugins, starting with Intel OpenVINO CPU + NPU on Linux.

What shipped

poly/accel — vendor-neutral plugin loader

Item Detail
Package poly/accel/ — Discover, Registry, Plugin, CompiledLayer
C ABI loom_accel.h in chaosglue (Loom does not vendor OpenVINO)
Linux dlopen via CGO (CGO_ENABLED=1)
Intel plugin libloom_accel_intel.so — built from loom/accel/intel/ (single .so, no versioned soname)

Dispatch integration

Item Detail
accel_intel.go DiscoverAccel, SyncToAccel, DispatchAccelForward, LayerWeightBytesForAccel (FP32/FP16/INT8)
forward.go DispatchLayer calls accel when layer.ExecTarget.UseAccel()
VolumetricLayer ExecTarget, AccelBinding fields
Init-once SyncToAccel(sizeLabel) compiles + uploads dtype-aware weights; steady infer reuses handle

Lucy [9] — Intel NPU bridge suite

Item Detail
Menu [9] → [4] medium or [5] full matrix
Tables Timing (Loom / Intel CPU / Intel NPU, speedup) + seven-style drift spectrum
Log lucy_testing_output/nine_layer.txt
Proof 90 cells: Intel infer 💎 EXACT repeat-forward; Conv2D large ~22× NPU vs Loom

Welvet C-ABI (489/489 parity)

Non-Go bindings can drive the same accel and entity-file paths without reimplementing poly/:

Export family Purpose
LoomDiscoverAccel / LoomNetworkAttachAccel / LoomSyncToAccel Plugin load, attach to VolumetricNetwork, compile + weight bake
LoomDispatchAccelForward / LoomLayerWeightBytesForAccel Per-layer Intel forward + weight byte introspection
LoomOpenEntityFile / LoomLoadEntityTransformerFromFile Random-access .entity without slurping full file
LoomLoadNetworkLayerWeights Hydrate selected layer indices from an open EntityFile

Parity check: cd welvet/cabi/internal/check && go run . → 489/489.

Linux build: cd welvet/cabi/internal/build && ./build_linux.sh (or ./build_unix.sh linux amd64). Output: dist/linux_<arch>/welvet.so + welvet.h.

Documentation

File Contents
accelerators.md User/developer guide — Intel now, Qualcomm + Google planned
chaosglue npu/docs/2025-06-26-loom-dispatch-integration-assessment.md Full benchmark evidence

What this release is (and is not)

You now have:

  • A real dispatch hook — not a standalone bench binary
  • Intel CPU + NPU on Linux with documented env + Lucy validation
  • A plugin model ready for Qualcomm NPU and Google TPU (same ABI, new .so)
  • Experimental label — appropriate for first wild release

You do not yet claim:

  • End-user “turn on NPU” without code (ExecTarget is manual)
  • JSON network field for exec: intel-npu
  • Training or backward on vendor path
  • Bit-perfect Loom ↔ Intel parity on all layers
  • Windows or macOS Intel plugin builds
  • Qualcomm or Google plugins (roadmap only)

Quick start (developers)

# 1. Build Intel CABI
cd accel/intel && ./install_openvino.sh && source ./setup_env.sh && ./build.sh

# 2. Optional explicit plugin path
export LOOM_ACCEL_INTEL_SO="$PWD/accel/intel/build/libloom_accel_intel.so"

# 3. Run Lucy validation
cd lucy_bloom_rivers
CGO_ENABLED=1 go run .
# → 9 → 4

Or: ./run_npu_bridge.sh from Lucy repo .

Monolithic MLP demo: cd accel/intel/example && CGO_ENABLED=1 go run .

Future vendors (planned)

Vendor Plugin (planned) SDK / hardware
Intel libloom_accel_intel.so ✅ OpenVINO, Core Ultra NPU
Qualcomm libloom_accel_qcom.so QNN / Hexagon, Snapdragon X
Google libloom_accel_google.so TPU / PJRT (cloud + edge TBD)

Loom code path is identical: DiscoverAccel → ExecTarget → SyncToAccel → ForwardPolymorphic.

Next targets (v0.82+)

  • AccelPlanner — auto-select CPU vs Intel CPU vs Intel NPU from shape + layer type
  • JSON exec field — "intel-npu" per layer in network JSON
  • Parity — MatMul bias/layout, norm weight upload, shared INT8 quant
  • Qualcomm CABI stub in chaosglue npu/qualcomm/
  • ASM rollout (continues from v0.80 roadmap) — Dense backward, SwiGLU, MHA

Key source files

Area Files
Accel package poly/accel/*.go
Intel dispatch poly/accel_intel.go, poly/forward.go
Types poly/poly.go (ExecTarget, AccelBinding, net.Accel)
Lucy suite Lucy examples/nine_layer/
Intel plugin C++ accel/intel/include/loom_accel.h, accel/intel/src/
Welvet C-ABI welvet/cabi/accel_ext.go, entity_ext.go, transformer_ext.go

See also