| """Where a native render's time goes: top CUDA kernels and host-side syncs.""" |
| import torch |
| from torch.profiler import profile, ProfilerActivity |
| from engine_client import Engine |
| from native_render import NativeRenderer |
|
|
| engine = Engine() |
| renderer = NativeRenderer(engine.scene, engine.scene_arrays) |
| frames = [] |
| for i in range(200): |
| events = [{'action': 'enter', 'phase': 'down'}, {'action': 'enter', 'phase': 'up'}] if i == 5 else [] |
| header, frame = engine.advance(round((i + 1) * 60 / 24), events, capture=i % 4 == 0, state=False) |
| if i % 4 == 0: |
| frames.append({k: v.copy() for k, v in frame.items()}) |
| engine.close() |
| for f in frames[:20]: |
| renderer.render(f) |
| torch.cuda.synchronize() |
| with profile(activities=[ProfilerActivity.CPU, ProfilerActivity.CUDA]) as prof: |
| for f in frames[20:40]: |
| renderer.render(f) |
| torch.cuda.synchronize() |
| print(prof.key_averages().table(sort_by='cuda_time_total', row_limit=14, max_name_column_width=60)) |
| syncs = [e for e in prof.key_averages() if any(k in e.key for k in ('Synchronize', 'cudaMemcpy', 'item', 'nonzero', 'local_scalar'))] |
| for e in syncs: |
| print('HOST', e.key, e.count, round(e.cpu_time_total / 20 / 1000, 3), 'ms/frame') |
|
|
