The 38.5-Second Proof: Validating Memory Backpressure Under Realistic Load

In the middle of a marathon optimization session targeting the SUPRASEAL_C2 Groth16 proof generation pipeline for Filecoin PoRep, the assistant produced a message that at first glance appears to be little more than a status update. Message [msg 3203] reads:

38.5s/proof with 20 proofs. Let me check RSS: [bash] cat /tmp/rss-nodebug-pw10.log | awk -F'RSS: ' '{print $2}' | sort -t. -k1 -n | tail -3 317.2 GiB 317.6 GiB 321.3 GiB

Three lines of output from a log file, a single throughput number, and a brief bash command. Yet this message represents the culmination of an intense debugging and optimization effort spanning dozens of iterations, and it carries the weight of a critical validation: the memory backpressure mechanism for Phase 12's split GPU proving API actually works under sustained production-like load.

The Crisis That Preceded This Message

To understand why this message matters, one must understand the problem it was solving. The Phase 12 split API had decoupled CPU-side synthesis from GPU-side proving, allowing synthesis to run ahead and queue partitions for the GPU workers. This architectural change was essential for throughput — it prevented the GPU from idling while waiting for the next partition to be synthesized. But it introduced a dangerous memory dynamic: if synthesis outpaced GPU consumption, synthesized partitions would pile up in memory, each holding approximately 12 GiB of evaluation vectors (the a/b/c polynomials). With a partition_workers (pw) setting of 12, the system could theoretically accumulate over 144 GiB of in-flight partition data before the GPU caught up. In practice, this caused out-of-memory (OOM) conditions at pw=12, with peak RSS reaching 668 GiB before the process was killed by the kernel.

The assistant had spent the preceding messages implementing a three-pronged memory backpressure strategy: (1) early deallocation of a/b/c evaluation vectors immediately after prove_start returned, freeing ~12 GiB per partition; (2) auto-scaling the synthesis-to-GPU channel capacity to max(synthesis_lookahead, partition_workers) instead of the hardcoded value of 1; and (3) holding the partition semaphore permit through the channel send operation, ensuring that the total number of in-flight outputs was bounded by partition_workers. These changes were committed as 98a52b33, and initial testing at pw=10 showed peak RSS dropping from 390 GiB to 314.7 GiB — a 19% reduction — with throughput holding steady at 38.9s/proof.

Why the 20-Proof Benchmark

The immediate context for message [msg 3203] is a lingering concern about throughput regression. The Phase 12 baseline — the very first benchmark run with the split API — had achieved 37.1s/proof. The current code, with all the memory backpressure fixes in place, was consistently delivering 38.8–38.9s/proof at pw=10. That ~1.7s difference (approximately 4.6% regression) nagged at the assistant. Was it caused by the overhead of the buffer counters and eprintln! debug logging? Was it memory fragmentation from repeated large allocations? Or was the 37.1s baseline simply a statistical outlier — a "lucky first run" on a pristine memory heap?

The assistant had already ruled out the debug logging hypothesis by converting eprintln! calls to tracing::debug! and re-benchmarking, finding no improvement (38.8s/proof either way). The next hypothesis was sample size: the Phase 12 baseline had run 20 proofs, while the recent benchmarks had run only 15. With GPU times showing high variance — individual partition times ranged from 6.0s to 13.3s — a small sample could easily produce a misleading average.

Message [msg 3203] reports the result of running the 20-proof benchmark to match the baseline sample size. The assistant had launched this benchmark in the previous message ([msg 3202]), and now the results were in: 38.5s/proof with 20 proofs. This was essentially the same 38.5–38.9s range seen in the 15-proof runs, confirming that sample size was not the cause of the discrepancy. The 37.1s baseline was indeed a statistical outlier — or perhaps a reflection of a pristine memory state before any fragmentation had accumulated.

The RSS Numbers Tell the Real Story

While the throughput number (38.5s) is what the assistant explicitly reports, the RSS numbers are arguably the more significant data in this message. Peak RSS of 321.3 GiB with 20 proofs running concurrently is a dramatic improvement over the 668 GiB that caused OOM at pw=12 before the fix. The system has 755 GiB of total memory, so 321 GiB leaves a comfortable margin of over 400 GiB. The memory backpressure mechanism is working exactly as designed.

The three RSS readings — 317.2, 317.6, and 321.3 GiB — also reveal something about the system's memory dynamics. The fact that the peak increased by only ~4 GiB when going from 15 proofs (314.7 GiB peak in an earlier run) to 20 proofs (321.3 GiB peak) suggests that the memory footprint is not scaling linearly with the number of concurrent proofs. This is consistent with the backpressure design: the bottleneck is the GPU consumption rate, not the number of proofs in flight. Once the pipeline is saturated, additional proofs in the queue don't significantly increase peak memory because the synthesis-to-GPU channel is bounded by partition_workers.

The Thinking Process Visible Behind the Message

Although message [msg 3203] itself is terse, the reasoning that produced it is visible in the surrounding conversation. The assistant had been systematically working through a decision tree:

  1. Hypothesis: Debug logging causes regression. Test: convert eprintln! to tracing::debug!. Result: no change (38.8s/proof). → Hypothesis rejected.
  2. Hypothesis: Sample size causes variance. Test: run 20 proofs instead of 15. Result: 38.5s/proof. → Hypothesis rejected; the 37.1s baseline was the outlier.
  3. Implicit hypothesis: The split API has inherent overhead. This is the remaining explanation. The split API adds a channel send/receive pair and a spawn_blocking task boundary between synthesis completion and GPU submission. Even with zero-copy semantics, this introduces scheduling latency and cache effects. The assistant's next move, visible in the following message ([msg 3204]), is to try pw=12 — increasing partition parallelism to see if more synthesis workers can compensate for the overhead. This is a logical next step: if the split API adds fixed latency per partition, running more partitions in parallel might hide that latency through pipelining.

Assumptions and Their Validity

Several assumptions underpin this message and the work that led to it:

Assumption 1: Memory pressure is the primary risk. This assumption proved correct. Without the backpressure fixes, pw=12 OOM'd at 668 GiB. With them, pw=12 runs at 383.8 GiB peak. The assumption that memory, not compute, was the limiting factor for higher pw values was validated.

Assumption 2: The channel capacity should equal partition_workers. The assistant assumed that setting channel capacity to partition_workers would prevent send blocking without allowing unbounded memory growth. This was validated by the RSS numbers: peak provers in flight dropped from 19 to 14 at pw=10, and from unbounded (OOM) to 18 at pw=12.

Assumption 3: Early a/b/c free is safe. The assistant assumed that the GPU had finished reading the evaluation vectors by the time prove_start returned. This is correct for the split API design — the GPU copies are initiated during prove_start, and the host-side vectors are no longer needed after that call completes. However, this assumption deserves scrutiny: if any error path or deferred operation references these vectors after they're freed, a use-after-free bug could occur. The assistant had already fixed one such bug in an earlier iteration ([msg 3191] mentions a use-after-free fix in groth16_cuda.cu).

Assumption 4: The 37.1s baseline was reproducible. This was the assumption being tested in this message, and it was disproven. The consistent result across multiple runs is 38.5–38.9s/proof. The 37.1s outlier was likely a first-run artifact — cold cache effects, favorable memory layout, or simply statistical variation in GPU scheduling.

Input Knowledge Required

To fully understand this message, one needs knowledge of:

Output Knowledge Created

This message creates several pieces of actionable knowledge:

  1. Throughput baseline confirmed: The consistent throughput for the Phase 12 split API with memory backpressure is ~38.5s/proof at pw=10. This is the number to beat in future optimization phases.
  2. Memory backpressure validated: Peak RSS of 321 GiB with 20 concurrent proofs confirms that the three-pronged fix (early a/b/c free, channel capacity auto-scaling, permit-held-through-send) is effective at bounding memory growth.
  3. Sample size adequacy established: The 20-proof result matches the 15-proof results, confirming that 15-proof benchmarks are sufficient for throughput measurement.
  4. First-run effect documented: The 37.1s baseline is now understood to be a non-reproducible artifact, preventing future confusion when comparing against it.

Conclusion

Message [msg 3203] appears mundane — a throughput number and some RSS readings — but it represents a critical validation point in a complex optimization effort. It confirms that the memory backpressure mechanism works under realistic load, establishes a reliable throughput baseline of 38.5s/proof, and closes the loop on the investigation into the ~1.7s regression from the Phase 12 baseline. The assistant's systematic approach — formulating hypotheses, testing them, and letting the data guide the next move — is on full display in the surrounding conversation. This message is the calm center of that storm: the moment when the numbers come in and the next direction becomes clear.