The 18 GiB That Didn't Matter: A Diagnostic Pivot in GPU Proving Optimization

In the high-stakes world of GPU-accelerated SNARK proving, memory is the invisible wall that stops progress. This article examines a single, deceptively brief message in an opencode coding session — message [msg 3073] — where an assistant, after implementing what seemed like a promising memory optimization, discovers that the fix barely moved the needle. The message is only a few lines: a bash command to extract peak RSS values from a monitoring log, and the resulting five numbers. But those numbers represent a critical inflection point in a multi-week optimization campaign for the CUZK SNARK proving engine, a system that generates Filecoin Proof-of-Replication (PoRep) proofs on a 755 GiB GPU server.

The Optimization Context

The session leading up to this message had been intensely focused on Phase 12 of the CUZK optimization roadmap. Phase 12 introduced a "split GPU proving API" — a refactoring of the C++ generate_groth16_proofs function into two asynchronous stages: prove_start (which runs the GPU kernel region and releases the GPU lock) and prove_finish (which completes the CPU-side b_g2_msm computation and epilogue). The goal was to decouple the GPU worker's critical path from the ~1.7 seconds of CPU post-processing, allowing the GPU to pick up the next synthesized partition immediately.

The Phase 12 implementation had been successfully committed at commit 99c31c2c, with benchmark results showing a 2.4% throughput improvement — from 38.0s to 37.1s per proof at the optimal configuration (gw=2, pw=10, gt=32). However, when the team tried to increase synthesis parallelism from pw=10 to pw=12, the system hit an Out-Of-Memory wall, with RSS peaking at approximately 668 GiB on the 755 GiB machine.

The Early Deallocation Hypothesis

The user's question at [msg 3055] — "the pending proof handle has nothing that can be freed early?" — prompted a detailed investigation. The assistant traced through the C++ prep_msm_thread code to determine which data structures the background finalization thread actually needed. The critical discovery was that the massive NTT evaluation vectors a, b, and c — each approximately 4 GiB per circuit, totaling ~12 GiB per partition — were only used by the GPU kernel region, which completed entirely within prove_start before the function returned. The prep_msm_thread only needed the input_assignment, aux_assignment, and density bitvectors, which were comparatively small.

The assistant implemented an early deallocation in prove_start: immediately after the C++ call returned, the a, b, and c vectors were dropped, freeing ~12 GiB per pending partition. The reasoning was sound: with two GPU workers, each potentially holding one pending handle during the ~1.7s b_g2_msm window, this would save approximately 24 GiB at steady state, plus more during burst conditions. The code was rebuilt and a new benchmark run was launched with pw=12.

The Moment of Failure

Then came the user's report at [msg 3072]: a single word — "ooming". The system was still being killed by the OOM killer. The assistant's response at [msg 3073] is the subject of this article:

Still OOM at pw=12. Let me check the RSS to understand where the memory is going: [bash] awk '{gsub(/RSS=/, ""); print $2}' /tmp/rss-pw12-v3.log | sort -n | tail -5 615.5 621.0 647.9 649.9 650.8

These five numbers — the five highest RSS readings from the monitoring log — tell a devastating story. The peak of 650.8 GiB is only ~18 GiB lower than the previous 668 GiB peak. The early deallocation of the a, b, c vectors had saved almost exactly the expected ~24 GiB, but it was nowhere near enough. The system was still consuming 86% of available memory and being terminated by the kernel.

What the Numbers Reveal

The assistant's thinking process is visible in the structure of the response. The opening line — "Still OOM at pw=12" — is not just a status update; it's a hypothesis refutation. The assistant had believed that the early deallocation would be sufficient to squeeze pw=12 into the 755 GiB budget. The evidence now disproves that belief.

The choice to extract the top five RSS values (rather than just the maximum) is itself diagnostic. By showing the sorted tail, the assistant reveals that the system spent significant time above 615 GiB, with multiple readings clustered in the 615-650 GiB range. This isn't a brief spike — it's sustained high memory pressure. The sort -n | tail -5 command is a classic systems debugging technique: look at the worst-case behavior to understand the failure mode.

The gap between 649.9 and 650.8 GiB (the top two values) is only 0.9 GiB, suggesting the system was hitting a hard ceiling. On a 755 GiB machine with typical kernel memory overhead and the OOM killer's threshold, 650.8 GiB of RSS likely represents the practical limit before processes are terminated.

The Deeper Problem

The assistant's next message ([msg 3074]) reveals the true diagnosis. By examining the full RSS timeline, the assistant realizes that the memory growth pattern doesn't match the "pending proof handle" theory. With pw=12, 12 concurrent syntheses each consuming ~13 GiB account for only ~156 GiB of synthesis memory — only 26 GiB more than the pw=10 configuration. Yet the peak jumped by approximately 300 GiB. The discrepancy points to a different root cause: glibc arena fragmentation.

The assistant's analysis identifies that each std::thread deallocation and the massive concurrent allocations from 12+ synthesis threads create severe memory fragmentation. The freed memory from completed syntheses is not returned to the operating system despite malloc_trim calls, because glibc's per-thread arenas fragment the heap. This is a fundamentally different problem from the one the early deallocation fix was designed to solve.

The Pivot

Message [msg 3073] is the pivot point where the assistant abandons the "pending proof handle memory" hypothesis and begins searching for the real bottleneck. The brevity of the message belies its significance: it represents the moment when a seemingly reasonable optimization is proven insufficient, forcing a deeper investigation into the system's memory architecture. The subsequent chunk (chunk 1 of segment 30) describes how the assistant built a global buffer tracker with atomic counters, discovered that the provers counter peaked at 28 (meaning 28 synthesized partitions were queued holding their full ~16 GiB datasets), and ultimately identified the partition semaphore release timing as the true culprit.

This message exemplifies a fundamental truth about systems optimization: the first hypothesis is often wrong, and the most valuable debugging tool is the willingness to measure, fail, and pivot. The 18 GiB saved by early deallocation was real, but it addressed the wrong problem. The real solution — holding the semaphore permit until the synthesized job was delivered to the GPU channel — would reduce peak RSS from 668 GiB to 294.7 GiB, a far more dramatic improvement. But that discovery required first confronting the failure documented in this brief, five-line message.