Thirty Partitions in One Second: Validating the Memory Manager at Scale

The Message

In message 2367 of a multi-day coding session building a GPU proving engine for Filecoin, the assistant sends a single bash command to a remote machine and receives back a triumphant result:

Now let me wait ~30s and check concurrency:

>

``bash sleep 30 && ssh -p 40612 root@141.0.85.211 ' echo "=== SYNTH_START count (concurrent partitions) ===" grep "SYNTH_START" /tmp/cuzk-memtest.log | wc -l echo "" echo "=== SYNTH timeline ===" grep -E "SYNTH_START|SYNTH_END" /tmp/cuzk-memtest.log echo "" echo "=== RSS ===" cat /tmp/cuzk-memtest-rss.log echo "" echo "=== Budget lines ===" grep -E "budget_available|budget_used|SRS loaded|PCE cached|dispatching" /tmp/cuzk-memtest.log' ``

>

=== SYNTH_START count (concurrent partitions) === 30

>

=== SYNTH timeline === TIMELINE,22821,SYNTH_START,3add7926-421c-4051-be9a-5f6db913596a,partition=0 TIMELINE,22821,SYNTH_START,3add7926-421c-4051-be9a-5f6db913596a,partition=1 TIMELINE,22821,SYNTH_START,3add7926-421c-4051-be9a-5f6db913596a,partition=2 TIMELINE,22821,SYNTH_START,3add7926-421c-4051-be9a-5f6db913596a,partition=3 TIMELINE,22821,SYNTH_START,4d68d168-3286-4b74-b8b1-be1a856789fd,partition=0 TIMELINE,22822,SYNTH_START,3add7926-421c-40...

On its face, this is a simple diagnostic query. But the numbers it reveals — 30 partitions starting within the same second — represent the culmination of a long debugging arc. Just minutes earlier, the same system could only run one partition at a time. This message is the moment of validation, the proof that a complex memory management redesign actually works in production.

The Context: A Budget That Was Too Tight

To understand why this message exists, we need to step back into the minutes preceding it. The assistant had been implementing a "budget-based memory manager" for the cuzk GPU proving engine — a system that tracks memory reservations and gates concurrent work to prevent out-of-memory (OOM) crashes. The initial deployment used a tight 100 GiB budget on a machine with 755 GiB of RAM and an RTX 5090 GPU.

The results were disastrous for throughput. The user reported ([msg 2353]): "Seems there is only one synthesis running at a time, previously the machine was handling 10 or 8." The assistant investigated and found the root cause: with SRS (Structured Reference String) consuming 44 GiB and PCE (Pre-Compiled Constraint Evaluator) consuming 26 GiB, the baseline alone ate 70 GiB of the 100 GiB budget. That left only ~30 GiB for working sets, which meant at most 2 partitions could run concurrently. But a secondary problem — an SRS pre-acquisition race where three concurrent proofs each tried to reserve 44 GiB simultaneously — further inflated the budget usage to 88 GiB, starving everything else.

The assistant attempted to fix this by switching the config from total_budget = "100GiB" to total_budget = "auto" with safety_margin = "5GiB". But the first restart attempt failed: the old daemon process wasn't killed properly, the config file wasn't updated (the heredoc in the bash command didn't execute as expected), and a zombie process lingered. It took several rounds of nuclear process killing and a careful heredoc rewrite before the new configuration was finally in place ([msg 2364]).

With the daemon restarted under the new config, the log showed total_budget_gib=750 (auto-detected from 755 GiB minus the 5 GiB safety margin) and max_partitions_in_budget=53. The assistant launched a benchmark: 3 proofs, concurrency 3, using 32 GiB PoRep data.

What This Message Does

Message 2367 is a diagnostic check sent 30 seconds after the benchmark starts. It runs five queries on the remote machine:

  1. Count SYNTH_START entries — to measure how many partitions have begun synthesis
  2. Show the full SYNTH timeline — to see the exact timing of starts and ends
  3. Show RSS trace — to monitor actual memory consumption over time
  4. Show budget lines — to see how the memory budget is being allocated These are the vital signs of the proving engine under load. The assistant is looking for evidence that the budget system is no longer serializing work. The result is unambiguous: 30 SYNTH_START entries, all with timestamps 22821–22822 (within one second). Every partition across all three proofs started simultaneously. The timeline shows partition=0 through partition=9 for multiple proof IDs all launching at the same tick.

Why This Matters: The Architecture of the Fix

The jump from 1 partition to 30 partitions is not just a configuration tweak — it validates several architectural decisions made across the preceding segments:

The budget system works. The MemoryBudget struct, the acquire()/release() reservation protocol, and the two-phase memory release mechanism all function correctly at scale. When given enough headroom (750 GiB instead of 100 GiB), the budget gates work without artificially constraining throughput.

The evictor callback fix holds. Earlier in this segment ([msg 2355]), the assistant had to fix a runtime panic where the evictor callback used blocking_lock() on a tokio Mutex from within an async context. The fix — replacing blocking_lock() with try_lock() — is now proven stable under real load.

The SRS race is tolerable. The assistant identified that three concurrent proofs each pre-acquire 44 GiB for SRS before any has loaded it, temporarily reserving 132 GiB. With a 750 GiB budget, this race condition is harmless. It only became a problem under the tight 100 GiB budget.

The pipeline dispatch is correct. The synthesis_concurrency = 4 setting, combined with the budget-aware dispatch logic, correctly launches partitions in parallel. The old concern that synthesis_concurrency might be the bottleneck is disproven: with sufficient budget, all 30 partitions start immediately regardless of the concurrency setting, because the budget itself becomes the natural throttle.

The Thinking Process Visible

This message reveals a methodical, hypothesis-driven debugging approach. The assistant's reasoning in the preceding messages shows a clear chain:

  1. Observe the symptom: Only 1 partition runs at a time ([msg 2353])
  2. Form a hypothesis: The 100 GiB budget is too tight, and there's an SRS race
  3. Gather evidence: Check budget logs showing budget_used_gib=88 and only 12 GiB available
  4. Design a fix: Switch to auto-detected budget, fix the config, restart cleanly
  5. Validate: Wait 30 seconds, then check concurrency The 30-second delay is deliberate — long enough for all partitions to start (synthesis takes ~42 seconds per partition based on earlier logs), but short enough to catch the system in mid-flight. The assistant chooses to count SYNTH_START entries rather than wait for completions, because the goal is to measure concurrency, not throughput. The choice of diagnostic queries is also telling. Rather than checking a single metric, the assistant cross-references four data sources: the partition timeline (showing when things start), the RSS trace (showing how much memory is used), and the budget lines (showing why the budget is allocated). This triangulation is characteristic of debugging complex systems where no single log line tells the full story.

Input Knowledge Required

To fully understand this message, one needs:

Output Knowledge Created

This message produces several important pieces of knowledge:

  1. Validation of the budget system: The memory manager works correctly when given adequate headroom. All 30 partitions start concurrently, proving the budget gates don't artificially serialize work.
  2. Baseline performance data: RSS peaks around 100–114 GiB under the old config; the new config should show different behavior.
  3. Confirmation that the SRS race is benign at scale: With 750 GiB budget, the temporary double-reservation of SRS (44 GiB × 2 = 88 GiB) is absorbed without issue.
  4. Evidence that the evictor fix is stable: No panic occurs during the 30-second window, confirming the try_lock() change works.

What Happens Next

The reader of the full conversation knows that this success is short-lived. In the very next message ([msg 2368]), the assistant discovers that the daemon was OOM-killed shortly after this check. The RSS trace shows memory climbing toward 500 GiB as all 30 partitions synthesize simultaneously, and with Curio and other processes consuming the remaining memory, the system runs out of RAM.

The assistant's conclusion is nuanced: the budget system works correctly, but the safety margin was too small. With 5 GiB of margin on a machine where Curio and other daemons consume significant memory, the budget calculation didn't account for co-located processes. The fix is not to change the budget logic, but to set a larger safety margin (e.g., 250 GiB) or an explicit cap.

This makes message 2367 a bittersweet milestone. It proves the memory manager's core design is sound — the budget gating, the evictor, the dispatch logic all function correctly. But it also reveals a configuration blind spot: the budget system only manages cuzk's own memory, not the memory of other processes on the same machine. The lesson is that "auto" detection of total system memory is not enough; you must also account for the memory needs of co-located workloads.

Conclusion

Message 2367 is a diagnostic query that becomes a victory lap — and then, in retrospect, a cautionary tale. It shows 30 partitions starting in one second, a tenfold improvement over the previous test. It validates weeks of work on the memory manager, the evictor callback fix, and the budget-aware dispatch pipeline. But it also sets the stage for the next bug: the OOM kill that follows when too many partitions run at once.

The message is a perfect snapshot of the iterative, empirical nature of systems programming. You form a hypothesis, you test it, you measure the results, and you learn something new — even when the test "passes." The 30 concurrent partitions were real, and they were correct. The problem was just that the system needed a bigger safety margin to coexist with its neighbors.