APIC MVP #1349

Description

Unified graph capture infrastructure that records Warp operations (kernel
launches, memory copies, memsets, allocations) during wp.ScopedCapture and
supports two consumers:

1. APIC serialization — Serialize the captured graph to a portable .wrp
   binary format and replay it from Python or standalone C++ without the
   original Python program.
2. CPU graph replay — Replay captured operations from the APIC byte stream,
   eliminating Python per-kernel dispatch overhead.

Both share a single C++ recording layer (the APIC byte stream in
APICStateInternal) and the same public API (capture_begin / capture_end /
capture_launch / capture_save / capture_load).

Implemented

• Record wp.launch, wp.copy, array.zero_(), and allocations during graph
  capture on both CPU and CUDA devices
• APIC: serialize to .wrp + _modules/ (compiled kernels as .cubin/.ptx
  for CUDA, .o for CPU)
• APIC: load and replay in Python via capture_load() and in standalone C++
  via the wp_apic_* C API
• APIC: named input/output bindings for supplying new data without graph rebuild
  (set_param / get_param)
• APIC: wp.Mesh serialization with handle pointer remapping (wp.handle type)
• CPU: replay via byte-stream interpretation (wp_apic_cpu_replay_state /
  wp_apic_cpu_replay_graph) with no Python involvement per operation
• Backward-compatible with existing wp.capture_* APIs
• Standalone C++ examples: CUDA OpenGL visualization
  (02_apic_visualization), CPU-only OpenGL visualization
  (03_apic_visualization_cpu)

Not yet supported

• array.fill_() during CPU capture (wp_memtile_host not recorded)
• wp.Volume / wp.BVH serialization
• wp.capture_if / wp.capture_while (conditional and loop graph nodes)
• Stream event nodes (record_event, wait_event)
• Texture array copies
• Multi-GPU support
• Compilation recording (deferred graph construction)
• wp.Tape backward pass during capture (access violation on CPU — forward
  arrays are not executed during deferred capture)

Coverage

Operations supported during graph capture:

Tests: 55 total (28 CPU+CUDA graph tests, 16 APIC round-trip tests, 6 mesh
serialization tests, 5 additional tests enabled on CPU).

Design docs

• Analysis — per-example catalog of captured operations and coverage matrix
• v1 Design — Python recording approach (superseded)
• v2 Design — C++ byte stream recording, architecture, implementation notes

Usage

import warp as wp

# CPU graph capture (already worked on CUDA)
with wp.ScopedCapture(device="cpu") as capture:
    wp.launch(my_kernel, dim=n, inputs=[a, b], device="cpu")
wp.capture_launch(capture.graph)

# APIC serialization
with wp.ScopedCapture(device="cuda:0", apic=True) as capture:
    wp.launch(my_kernel, dim=n, inputs=[a, b], device="cuda:0")
wp.capture_save(capture.graph, "my_graph",
                inputs={"a": a}, outputs={"b": b})

# Load and replay (Python, also available as standalone C API)
loaded = wp.capture_load("my_graph", device="cuda:0")
wp.capture_launch(loaded)