--benchmark <path> reports cumulative CPU and wall time per node and
names the node pacing the run. The pacing node is located from sampled
channel occupancy, not from time-in-node: backpressure inflates
time-in-node for everything downstream of the real bottleneck, so the
obvious measure names the victim rather than the cause.
Sampling starts with the network and stops before it is destroyed.
Channel fill is instantaneous and everything has drained by shutdown, so
a single read at the end reports an idle pipeline however congested it
was.
kill -USR1 dumps the table from a running or wedged process. Channel
occupancy identifies a stalled node -- full input, empty output --
without a debug build or a debugger, which is the difference between
diagnosing the AR-004 hang in seconds and reproducing it under gdb.
Two knobs this exposes for measurement rather than sets: SAE_CV_THREADS,
because OpenCV's TBB arena and KPN's thread-per-node are two schedulers
unaware of each other on the same cores; and SAE_CUDA_BLOCKING_SYNC,
because the default spin-wait held the embedder thread at 99.7% user
time while nvidia-powerd cut the GPU's clock from 1005 to 210 MHz.
Neither default changes until a measurement says it should.
TRACES: VR-015 | PR-004
OpenCV: distros (Arch/CachyOS) now ship OpenCV 5 as default. The config
package rejects a 5.x install when find_package requests 4, so probe for 5
first and fall back to 4. All components used here (core, imgproc, imgcodecs,
videoio, dnn, objdetect, highgui) exist in both.
TensorRT: nvinfer1::Dims5 was removed in TRT 10 (Dims2..Dims4 remain in
NvInferLegacyDims.h). Build the TransNetV2 rank-5 input shape via the generic
nvinfer1::Dims, which is valid on both 8.x and 10.x.
Gallery format switches from JSON to HDF5 exclusively (JSON read-only kept for
back-compat): save_gallery always writes HDF5, and the fitted Platt-sigmoid
calibration (a, b, valid, hash) is now embedded directly in the gallery file
instead of a sidecar .calib_cache.json — identity_matcher reads it from the
loaded gallery and writes back only when the embeddings actually changed
(hash mismatch), skipping the O(n^2) refit otherwise.
Also includes: TensorRT inference backend support (ort_backend.cpp,
trt_backend.cpp), gemm_backend improvements, TransNetV2-based scene-boundary
detection wired through frame_source/face_tracker/main, and CMake build
target updates for the new sources.
Bumps the KPN submodule to feature/persistent-pipeline-reuse (push_blocking
backpressure, node_ptr/node_stats introspection, ObjectVariantNodeWrapper for
stateful functors) — needed by the optimizer's sae_kpn Python bindings.
dtourolle