The Ten-Second Ghost: Instrumenting a CUDA Destructor Chain

In the high-stakes world of Filecoin proof generation, every second counts. When the assistant wrapped up Phase 4 synthesis optimizations for the cuzk proving engine — having already shaved 3.5 seconds off circuit synthesis via Boolean::add_to_lc — a full end-to-end benchmark should have been a moment of triumph. Instead, it revealed a puzzle. The CUDA kernels were running at exactly the same speed as the baseline (~25.7 seconds), but the Rust-side timer around the GPU proving function had mysteriously grown from 34.0 seconds to 36.0 seconds. Somewhere, ten seconds had gone missing.

Message <msg id=1238> is the turning point in solving that mystery. It is deceptively simple on the surface — a single edit to a CUDA source file — but it represents the moment a hypothesis was put to the test with surgical precision. This article examines that message in depth: the reasoning that led to it, the assumptions it encoded, the knowledge it required, and the critical insight it would ultimately produce.

The Setup: A Timing Discrepancy That Shouldn't Exist

The assistant had just completed a full E2E proof with the Boolean::add_to_lc optimization and logged the results at <msg id=1222>:

timings: total=87459 ms (queue=264 ms, srs=0 ms, synth=51234 ms, gpu=35961 ms)

The synthesis improvement was real — 51.2 seconds versus a 54.7-second baseline. But the GPU number was alarming. The previous baseline had shown 34.0 seconds for the GPU phase, and the CUDA internal timing markers (CUZK_TIMING) showed that the actual GPU compute was unchanged at ~25.7 seconds. The assistant compiled a comparison table at <msg id=1224> that made the problem stark: CUDA internal time was stable, but the bellperson wrapper was reporting 36.0 seconds instead of 34.0. A ten-second gap had opened up between the end of the CUDA kernel execution and the moment the Rust pipeline logged "GPU prove complete."

This was not a performance regression in the normal sense — the CUDA code was running identically. Something else was consuming those ten seconds, and it was happening after the GPU work finished but before control returned to the pipeline.

The Investigation: Tracing the Gap

The assistant began methodically tracing the timeline. At <msg id=1226>, it reconstructed the sequence of events from log timestamps:

01:09:13.35 - bellperson GPU prove done (25.8s)
01:09:23.53 - pipeline GPU complete (36.0s total)
Gap: 10.2s between bellperson prove and pipeline complete

The gap was entirely between the Rust-side prove_from_assignments() function returning and the pipeline's outer timer stopping. The assistant read the pipeline code at <msg id=1228> and the bellperson prover at <msg id=1231>, confirming that the Rust Instant::now() wrapper around prove_from_assignments() was the source of the 36-second measurement, while the function's internal timer (at line 354 of supraseal.rs) showed only 25.8 seconds.

At <msg id=1234>, the assistant dispatched a subagent task to perform a deep analysis of the full call chain from Rust through the C++ FFI boundary into the CUDA kernels. The task result mapped every allocation, every thread join, and every destructor call in the generate_groth16_proofs_c function. The critical finding was that the C++ function allocated enormous temporary vectors — split_vectors for each circuit's a/b/c segments and tail_msm_*_bases for the tail MSM computation — totaling approximately 37 GB of heap memory. These allocations were freed in the implicit destructor chain when the function's local variables went out of scope at the closing brace.

The hypothesis crystallized at <msg id=1235>: the ten-second gap was almost certainly heap deallocation of ~37 GB in implicit destructors at function exit. But a hypothesis is not a fact. It needed measurement.

The Edit: Instrumenting the Return Path

Message <msg id=1238> is the application of that measurement. The assistant edited /home/theuser/curio/extern/supraseal-c2/cuda/groth16_cuda.cu to add timing instrumentation at strategic points. The edit added markers for:

  1. Pre-prep overhead — time from function entry to when the prep MSM thread actually starts
  2. Split vector allocation — the time spent constructing the large temporary vectors
  3. Epilogue — time for proof assembly after GPU compute finishes
  4. Pre-destructor marker — a timestamp recorded just before the return ret statement, capturing everything up to that point The key insight was the placement of the pre-destructor marker. By comparing the Rust-side timer (which includes destructor time) with the pre-destructor timestamp (which excludes it), the assistant could directly measure the destructor overhead. If the hypothesis was correct, the pre-destructor time would match the bellperson internal measurement (~26 seconds), and the Rust-side timer would show the full ~36 seconds, with the difference being exactly the destructor chain.

Assumptions and Risks

The edit made several assumptions. First, that the timing discrepancy was not caused by something in the Rust FFI layer — the extern "C" function boundary, the RustError return type, or the marshaling of results back to Rust. Second, that the gettimeofday calls would have sufficient precision to distinguish sub-second differences in a 10-second gap. Third, that the act of adding instrumentation would not itself materially change the timing behavior (the Heisenberg problem).

There was also a subtle assumption about the destructor model: that the C++ vectors' destructors were the dominant cost, rather than Rust-side drops of the ProvingAssignment vectors (a/b/c assignments) which were also ~130 GB of data. The assistant would later discover that both sides contributed — the C++ destructors freed ~37 GB of split vectors and tail MSM bases, while the Rust side freed the even larger ProvingAssignment Vecs — and both would need to be addressed with async deallocation.

The Knowledge Required

To understand this message, one needs knowledge of several layers:

The Knowledge Created

The edit at <msg id=1238> was the decisive diagnostic step. When the assistant rebuilt and ran the E2E test at <msg id=1248> and <msg id=1249>, the instrumentation produced the critical data point:

CUZK_TIMING: epilogue_ms=10 pre_destructor_ms=26138

The pre-destructor time was 26.1 seconds — matching the bellperson internal measurement of ~25.8 seconds almost exactly. The epilogue (proof assembly) was a mere 10 milliseconds. The remaining ~10 seconds between pre_destructor_ms and the Rust-side timer of 36.2 seconds could only be destructor overhead.

The assistant confirmed this at <msg id=1250>: "So: pre_destructor_ms = 26.1s, but Rust side measures 36.2s. That means 10.0 seconds is in destructors — the time between return ret and when the Rust caller gets control back."

Broader Significance

This moment exemplifies a pattern that recurs throughout performance engineering: the most costly operations are often invisible because they happen between the measured intervals. The CUDA kernels were fast, the proof assembly was fast, but the cleanup — the act of freeing memory that was no longer needed — was consuming ten seconds that no one was timing. The instrumentation at <msg id=1238> exposed this hidden cost.

The fix that followed (async deallocation via detached threads on both the C++ and Rust sides) would drop the GPU wrapper time from 36.0 seconds to 26.2 seconds, matching the CUDA internal time exactly. Combined with the synthesis improvements, the total E2E time fell from 88.9 seconds to 77.2 seconds — a 13.2% improvement. But none of that would have been possible without first knowing where those ten seconds were hiding.

In the end, the ten-second ghost was not a ghost at all. It was the sound of 37 gigabytes of vectors being freed, one destructor call at a time — and a single well-placed gettimeofday was all it took to hear it.