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Author SHA1 Message Date
3b76b6dcb9 [0.1.26] gpu-bench: a memory trace per step, -ocr-workers and -ort-log
Each result now has the GPU's memory over the baseline after loading, the
first image, each warm-up pass and each timed pass (with the pass's peak), in
the output and as trace= in the results file, so growth across passes (a leak)
shows apart from a working set. -ocr-workers sets OCR's GPU worker threads, and
-ort-log info prints onnxruntime's arena extensions: what found the cause of
0.1.24's memory fix.
2026-10-17 21:13:30 -04:00
0bf505f0dd [0.1.25] GPU benchmark (gpu-bench branch, not for master)
bin/gpu-bench times every GPU model (OCR mobile and server, the label
image encoder, segmentation; optionally the CPU and the label text
encoder) over a fixed 30-image corpus in tools/gpu_bench/corpus. Every
corpus file is checked against corpus.txt's SHA-256 before anything
runs; each model's files and models.config entry are fingerprinted;
the GPU, driver, power limit, CUDA runtime, cuDNN and onnxruntime are
recorded, and NVML samples memory, load, power and clocks during the
timed passes. Results go to bin/gpu-bench-results as text files.

The GPU Bench button opens a window that runs gpu-bench in its own
process (no console) and lays results files from several machines side
by side against a baseline, marking a different corpus or model.
2026-10-17 21:13:01 -04:00
9 changed files with 6 additions and 214 deletions

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@ -107,12 +107,9 @@ grid (in its order, so through a search's matches).
from CUDA, and OCR's inputs change size every run, so each larger image or wider batch of lines left
another block behind. OCR now runs the largest images and widest batches first, has the detector's
and recognizer's arenas give back what they hold after each stage of a call, and keeps its 4 worker
threads for the engine's life. Since 0.1.25 the runs on the GPU at once are as many as fit in its
memory: each engine measures what its runs need when it starts, and each run waits while the runs in
flight and the GPU's free memory leave too little for it (`modules/OCR/budget.jai`). On an RTX 5080
laptop (16 GB), gpu-bench, 2026-10-17: the mobile model peaks at 5.7 GB and drops to 2 GB between
calls, at 140 ms a capture against 126 before; the server model peaks at 13.1 GB, at 335 ms a
capture against 10.9 s.
threads for the engine's life. The mobile model now peaks at 5.7 GB and drops to 2 GB between
calls, at 142 ms a capture against 126 before (gpu-bench, 2026-10-17). The server model has not been
measured again yet.
- **Running on:** the GPU or the CPU, and if the CPU, what to install for the GPU.
- **Scan the library** reads every capture the model has not read yet and, with **Labels too**,
labels every capture not yet labelled with the current list. While a search is active the button

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@ -47,7 +47,7 @@ APP_NAME :: "mcap";
APP_FOLDER_NAME :: "mcap";
GIT_BRANCH :: "check";
GIT_HASH :: "-";
VERSION :: "0.1.28";
VERSION :: "0.1.26";
BUILD_DATE :: "-";
DEBUG :: true;
COMPILE_TESTS :: true;

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@ -8,7 +8,7 @@ APP_NAME :: "mcap";
APP_FOLDER_NAME :: "mcap";
APP_BUNDLE_IDENTIFIER :: "com.example.mcap";
VERSION :: "0.1.28";
VERSION :: "0.1.26";
// Where everything goes: bin/, or bin-headless/ for builds made with no_crash_dialog, so automated
// builds never write over the ones you run by hand.
build_directory := "bin";

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@ -1,137 +0,0 @@
// On the GPU, how many detector and recognizer runs share it at once: as many as fit in its memory.
// Each run reserves what it is expected to need before it starts, and waits while the runs in flight
// leave too little; one run always goes. A run's need grows with its input, and the engine measures
// how fast when it is made, so it holds for any model and GPU: from the arena's peak (onnxruntime's
// MaxInUse) over runs on two input sizes. The limit is a share of the GPU's free memory, read again at
// the start of every ocr_process call, as other engines and programs come and go. A run must also fit
// in what the GPU has free when it starts: the arenas keep finished runs' blocks until the stage ends
// (ocr_shrink_arena), a run of another size can need a new block beside them, and cuDNN and cuBLAS
// take memory of their own, so the reservations alone let the server model reach 15.4 GB of 16.
//
// Without it, gpu_workers runs went at once whatever the images: the server model, four large images
// at a time, took 15 GB of a 16 GB GPU, and on a smaller GPU Windows pages the excess into shared
// system memory, running it many times slower.
Ocr_Budget :: struct {
enabled: bool; // on CUDA, when the engine could measure its runs
limit: s64; // bytes the runs in flight may reserve together
in_use: s64; // reserved by the runs in flight; under mutex
headroom: s64; // bytes left free on the GPU, beside the limit and when a run starts
recent: [8] Ocr_Budget_Grant; // the last runs let go, under mutex: what the GPU's free memory may not show yet
mutex: Mutex;
det_fixed, det_per_pixel: float64; // a detector run's need: det_fixed + det_per_pixel * height * width
rec_fixed, rec_per_column: float64; // a recognizer run's: rec_fixed + rec_per_column * lines * width
}
// A run let go, which may not have taken its memory yet.
Ocr_Budget_Grant :: struct { at: Apollo_Time; bytes: s64; }
OCR_BUDGET_GRANT_MS :: 50; // how long a run let go may take to take its memory
OCR_BUDGET_MARGIN :: 1.2; // estimates are raised by this much: other shapes, other kernels
OCR_BUDGET_HEADROOM :: 0.1; // of the free memory, left for everything else on the GPU
OCR_BUDGET_MIN_HEADROOM :: 512 * 1024 * 1024;
// Measures what the detector's and recognizer's runs need, from runs on two sizes each. Called at
// creation, under ort_gpu_lock, after ocr_warm_up; on failure the budget is off and every worker runs.
ocr_budget_calibrate :: (engine: *Ocr_Engine) {
b := *engine.budget;
// What one run needs, from the arena's peak, run after run of growing size so each sets a new peak.
need :: (engine: *Ocr_Engine, session: *Ocr_Session, shape: [4] s64) -> s64, ok: bool {
before, _, ok := ort_gpu_arena_stats(session);
if !ok return 0, false;
count := shape[0] * shape[1] * shape[2] * shape[3];
input := NewArray(count, float, initialized = true,, context.default_allocator);
defer array_free(input,, context.default_allocator);
out, run_ok := ocr_run(session, engine.memory_info, input, shape);
if !run_ok return 0, false;
ocr_release_output(*out);
_, peak, stats_ok := ort_gpu_arena_stats(session);
if !stats_ok || peak <= before return 0, false;
return peak - before, true;
}
fit :: (x0: float64, y0: s64, x1: float64, y1: s64) -> fixed: float64, slope: float64 {
slope := max(cast(float64) (y1 - y0) / (x1 - x0), 0);
return max(y0 - slope * x0, 0), slope;
}
// The detector at 512 and 1024 px square; the recognizer on a full batch 256 and 1024 px wide.
d0, ok0 := need(engine, *engine.det, .[1, 3, 512, 512]);
d1, ok1 := need(engine, *engine.det, .[1, 3, 1024, 1024]);
lines := cast(s64) max(engine.model.rec_batch_gpu, 1);
height := cast(s64) engine.model.rec_height;
r0, ok2 := need(engine, *engine.rec, .[lines, 3, height, 256]);
r1, ok3 := need(engine, *engine.rec, .[lines, 3, height, 1024]);
ocr_shrink_arena(engine, *engine.det);
ocr_shrink_arena(engine, *engine.rec);
if !ok0 || !ok1 || !ok2 || !ok3 return;
b.det_fixed, b.det_per_pixel = fit(512.0 * 512, d0, 1024.0 * 1024, d1);
b.rec_fixed, b.rec_per_column = fit(cast(float64) lines * 256, r0, cast(float64) lines * 1024, r1);
init(*b.mutex);
b.enabled = true;
}
// The share of the GPU's free memory the runs of this call may take; at the start of ocr_process.
ocr_budget_update :: (engine: *Ocr_Engine) {
b := *engine.budget;
if !b.enabled return;
free, _, ok := ort_cuda_memory();
if !ok return; // the last limit stands
headroom := max(cast(s64) (free * OCR_BUDGET_HEADROOM), OCR_BUDGET_MIN_HEADROOM);
lock(*b.mutex);
b.headroom = headroom;
b.limit = max(free - headroom, 0);
unlock(*b.mutex);
}
ocr_budget_detector :: (engine: *Ocr_Engine, height: s64, width: s64) -> s64 {
b := *engine.budget;
return cast(s64) ((b.det_fixed + b.det_per_pixel * height * width) * OCR_BUDGET_MARGIN);
}
ocr_budget_recognizer :: (engine: *Ocr_Engine, lines: s64, width: s64) -> s64 {
b := *engine.budget;
return cast(s64) ((b.rec_fixed + b.rec_per_column * lines * width) * OCR_BUDGET_MARGIN);
}
// Waits until bytes fit beside the runs in flight and in the GPU's free memory (at once when no run
// is in flight), and reserves them.
ocr_budget_reserve :: (engine: *Ocr_Engine, bytes: s64) {
b := *engine.budget;
if !b.enabled return;
waited := false;
while true {
free, _, free_ok := ort_cuda_memory();
lock(*b.mutex);
fits := b.in_use == 0;
if !fits && b.in_use + bytes <= b.limit {
// Runs let go in the last moments may not show in free yet.
now := current_time_monotonic();
pending: s64;
for b.recent if it.bytes && to_milliseconds(now - it.at) < OCR_BUDGET_GRANT_MS pending += it.bytes;
fits = !free_ok || bytes + pending <= free - b.headroom;
}
if fits {
b.in_use += bytes;
oldest := 0;
for b.recent if it.at < b.recent[oldest].at oldest = it_index;
b.recent[oldest] = .{current_time_monotonic(), bytes};
}
unlock(*b.mutex);
if fits break;
if !waited { waited = true; atomic_add(*engine.stats.budget_waits, 1); }
sleep_milliseconds(1);
}
}
ocr_budget_release :: (engine: *Ocr_Engine, bytes: s64) {
b := *engine.budget;
if !b.enabled return;
lock(*b.mutex);
b.in_use -= bytes;
unlock(*b.mutex);
}
ocr_budget_destroy :: (engine: *Ocr_Engine) {
if engine.budget.enabled destroy(*engine.budget.mutex);
engine.budget = .{};
}

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@ -83,10 +83,7 @@ ocr_detect_tile :: (engine: *Ocr_Engine, image: Ocr_Image, scale: float, scaled_
}
shape := s64.[1, 3, h, w];
reserved := ocr_budget_detector(engine, h, w);
ocr_budget_reserve(engine, reserved); // budget.jai: waits while the GPU's memory is taken
out, ok, error := ocr_run(*engine.det, engine.memory_info, input, shape);
ocr_budget_release(engine, reserved);
if !ok return false, error;
defer ocr_release_output(*out);
if out.dim_count != 4 || out.dims[2] != h || out.dims[3] != w {

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@ -48,7 +48,6 @@ Ocr_Engine :: struct {
options: Ocr_Options;
stats: Ocr_Stats; // since creation, or the last ocr_reset_stats
pool: Ocr_Pool; // the worker threads, for the engine's life (run_on_workers)
budget: Ocr_Budget; // on CUDA: how many runs fit in GPU memory at once (budget.jai)
// When set, and true, ocr_process stops starting work: the batch of lines or image each worker is
// on is finished, and then every image fails as "cancelled" (none is part read). Set by the caller.
@ -69,7 +68,6 @@ Ocr_Stats :: struct {
recognize_us: s64; // cropping lines, the recognizer, and decoding the text
orientation_us: s64; // cropping lines and the orientation classifier
turned: s64; // lines that read better the other way up, or level as found
budget_waits: s64; // detector and recognizer runs that waited for GPU memory (budget.jai)
}
ocr_stats :: (engine: *Ocr_Engine) -> Ocr_Stats { return engine.stats; }
@ -134,10 +132,6 @@ ocr_create :: (models_folder: string, model_name: string, prefer_gpu := true, op
sessions_ok, sessions_error := ocr_create_sessions(engine, models_folder, true, 2);
if sessions_ok sessions_ok, sessions_error = ocr_warm_up(engine);
if !sessions_ok ocr_release_sessions(engine);
if sessions_ok {
engine.provider = .CUDA; // before calibrating: ocr_shrink_arena only works on CUDA
ocr_budget_calibrate(engine);
}
ort_gpu_unlock();
if sessions_ok {
engine.provider = .CUDA;
@ -172,7 +166,6 @@ ocr_gpu_status :: (engine: *Ocr_Engine) -> in_use: bool, explanation: string {
ocr_destroy :: (engine: *Ocr_Engine) {
if !engine return;
ocr_pool_stop(engine);
ocr_budget_destroy(engine);
if engine.provider == .CUDA ort_gpu_lock();
ocr_release_sessions(engine);
if engine.provider == .CUDA ort_gpu_unlock();
@ -187,7 +180,6 @@ ocr_destroy :: (engine: *Ocr_Engine) {
ocr_process :: (engine: *Ocr_Engine, images: [] Ocr_Image, allocator := context.allocator) -> [] Ocr_Result {
results := NewArray(images.count, Ocr_Result,, allocator);
if !images.count return results;
ocr_budget_update(engine); // budget.jai: the GPU memory this call's runs may share
// Detection: images shared out among the workers.
per_image := NewArray(images.count, Image_Work,, context.default_allocator);
@ -454,7 +446,6 @@ run_on_workers :: (engine: *Ocr_Engine, count: s64, proc: Work_Proc, data: *void
#load "models.jai";
#load "detect.jai";
#load "recognize.jai";
#load "budget.jai";
#import "Basic";
#import "String";

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@ -38,10 +38,7 @@ ocr_recognize_batch :: (engine: *Ocr_Engine, jobs: [] *Line_Job) -> ok: bool, er
}
shape := s64.[jobs.count, 3, height, width];
reserved := ocr_budget_recognizer(engine, jobs.count, width);
ocr_budget_reserve(engine, reserved); // budget.jai: waits while the GPU's memory is taken
out, ok, error := ocr_run(*engine.rec, engine.memory_info, input, shape);
ocr_budget_release(engine, reserved);
if !ok return false, error;
defer ocr_release_output(*out);
if out.dim_count != 3 || out.dims[0] != jobs.count return false, tprint("The recognizer gave an output of shape %.", array_view(out.dims, 0, out.dim_count));

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@ -123,50 +123,6 @@ ort_release_session :: (s: *Ort_Session) {
s.* = .{};
}
// The GPU's free and total memory in bytes, from the CUDA runtime onnxruntime's CUDA provider loads;
// ok false before a CUDA session has been made, or without CUDA.
ort_cuda_memory :: () -> free: s64, total: s64, ok: bool {
Get_Info :: #type (free: *u64, total: *u64) -> s32 #c_call;
get: Get_Info;
#if OS == .WINDOWS {
module := GetModuleHandleA("cudart64_13.dll");
if module get = cast(Get_Info) GetProcAddress(module, "cudaMemGetInfo");
} else #if OS == .LINUX {
handle := dlopen("libcudart.so.13", RTLD_LAZY);
if handle get = cast(Get_Info) dlsym(handle, "cudaMemGetInfo");
}
if !get return 0, 0, false;
free, total: u64;
if get(*free, *total) != 0 return 0, 0, false;
return cast(s64) free, cast(s64) total, true;
}
// A CUDA session's GPU arena: the bytes its blocks hand out now, and the most they ever have (onnxruntime
// keeps the peak since the session was made). ok false when onnxruntime does not say.
ort_gpu_arena_stats :: (s: *Ort_Session) -> in_use: s64, max_in_use: s64, ok: bool {
api := ort.api;
info: *OrtMemoryInfo;
if !ort_check(api.CreateMemoryInfo("Cuda", .OrtArenaAllocator, 0, .OrtMemTypeDefault, *info)) return 0, 0, false;
defer api.ReleaseMemoryInfo(info);
allocator: *OrtAllocator;
if !ort_check(api.CreateAllocator(s.session, info, *allocator)) return 0, 0, false;
defer api.ReleaseAllocator(allocator);
stats: *OrtKeyValuePairs;
if !ort_check(api.AllocatorGetStats(allocator, *stats)) return 0, 0, false;
defer api.ReleaseKeyValuePairs(stats);
keys, values: **u8;
count: u64;
api.GetKeyValuePairs(stats, *keys, *values, *count);
in_use, max_in_use := -1, -1;
for 0..cast(s64) count - 1 {
key := to_string(keys[it]);
if key == "InUse" in_use = string_to_int(to_string(values[it]));
if key == "MaxInUse" max_in_use = string_to_int(to_string(values[it]));
}
if in_use < 0 || max_in_use < 0 return 0, 0, false;
return in_use, max_in_use, true;
}
// A run's output: its values stay valid until ort_release_output.
Ort_Output :: struct {
value: *OrtValue;

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@ -151,7 +151,6 @@ Run :: struct {
stages: string; // where the time went, per item
batch: s64;
gpu: Gpu_Stats;
budget: string; // OCR on the GPU: what its memory budget measured (modules/OCR/budget.jai), or ""
trace: [..] string; // the GPU's memory above the baseline, MB, after each step: load:812 first:1020 warm1:... pass1:.../peak...
explanation: string; // why a GPU run is on the CPU
}
@ -323,10 +322,6 @@ run_task :: (task: *Task, prefer_gpu: bool, corpus: *Corpus) -> Run {
if prefer_gpu && !ocr_gpu run.explanation = copy_string(ocr_why);
run.provider = sprint("%", ocr_provider(engine.ocr));
run.batch = engine.ocr.rec_batch;
b := engine.ocr.budget;
if b.enabled run.budget = sprint("detector %+% MB/MP, recognizer %+% MB per 1000 line-px", FF(b.det_fixed / MEGABYTE, 0), FF(b.det_per_pixel * 1_000_000 / MEGABYTE, 0),
FF(b.rec_fixed / MEGABYTE, 0), FF(b.rec_per_column * 1000 / MEGABYTE, 1));
else if engine.ocr.provider == .CUDA run.budget = "off (the arena could not be measured)";
}
case .LABELS; #through;
case .LABELS_TEXT;
@ -462,8 +457,7 @@ run_task :: (task: *Task, prefer_gpu: bool, corpus: *Corpus) -> Run {
per := cast(float64) max(run.items * options.repeats, 1) * 1000;
if task.kind == .OCR {
s := ocr_stats(engine.ocr);
run.stages = sprint("detect:%,orient:%,recognize:%,budget_waits:%", FF(s.detect_us / per, 2), FF(s.orientation_us / per, 2), FF(s.recognize_us / per, 2), s.budget_waits);
if engine.ocr.budget.enabled run.budget = sprint("%; limit % MB at the end", run.budget, FF(engine.ocr.budget.limit / MEGABYTE, 0));
run.stages = sprint("detect:%,orient:%,recognize:%", FF(s.detect_us / per, 2), FF(s.orientation_us / per, 2), FF(s.recognize_us / per, 2));
} else if task.kind == .SEGMENT {
s := engine.segment.stats;
run.stages = sprint("prepare:%,model:%,post:%", FF(s.prepare_us / per, 2), FF(s.model_us / per, 2), FF(s.post_us / per, 2));
@ -507,7 +501,6 @@ print_run :: (task: *Task, run: Run) {
if run.megapixels print(", % megapixels/s", FF(run.megapixels / m.median, 1));
print("\n");
if run.stages print(" per %, summed over threads (ms): %\n", run.unit, run.stages);
if run.budget print(" GPU memory budget: %\n", run.budget);
if run.gpu.samples print(" GPU: % MB more memory at the peak, % percent busy, % W, % MHz, up to % C\n",
FF(run.gpu.peak_mb - run.gpu.baseline_mb, 0), FF(run.gpu.util_sum / run.gpu.samples, 0),
FF(run.gpu.power_sum / run.gpu.samples, 0), FF(run.gpu.clock_sum / run.gpu.samples, 0), FF(run.gpu.temperature_max, 0));
@ -678,8 +671,6 @@ hash_file_cached :: (path: string) -> string {
return hash;
}
MEGABYTE :: 1024.0 * 1024;
seconds_since :: (start: Apollo_Time) -> float64 {
return to_float64_seconds(current_time_monotonic() - start);
}