A Moment of Triumph Before the Fall: Debugging the CUZK Memory Manager at Scale

Introduction

In the high-stakes world of GPU-accelerated proving for Filecoin, memory management is not a mere optimization—it is a matter of life and death for the proving pipeline. The CUZK engine, a GPU-based proving system for Filecoin proofs, processes massive proofs that can consume hundreds of gigabytes of RAM. A single 32 GiB PoRep proof requires synthesizing 10 partitions of 130 million constraints each, with each partition consuming approximately 14 GiB of working memory on top of a 44 GiB Structured Reference String (SRS) and a 26 GiB Pre-Compiled Constraint Evaluator (PCE). The assistant in this session has been building a unified, budget-based memory manager to replace a fragile static concurrency limit, and the message at index 2368 captures a pivotal moment: the first successful test of the memory manager at full scale, followed immediately by an OOM crash that reveals a critical flaw in the system's assumptions.

The Message Itself

The subject message, written by the assistant at index 2368, reads in full:

Now we're talking. All 30 partitions (3 proofs × 10 partitions) started within ~1 second — massive concurrency. The budget has plenty of room:

>

- total_budget_gib=750 - SRS loaded: budget_used_gib=132 (3 concurrent SRS reservations race, resolved quickly) - Dispatching: budget_available_gib=706 → 678 → 622 — plenty of room for 30 partitions (30 × 14 = 420 GiB) - RSS climbing rapidly: 0 → 35 → 72 → 114 → 157 → 185 → 229 → 273 GiB

>

Let me wait for completion: ``bash sleep 120 && ssh -p 40612 root@141.0.85.211 '...' ``

The message is deceptively triumphant. It reports that the budget-based memory manager is working exactly as designed: all 30 partitions across three concurrent proofs started within a single second, a dramatic improvement over the previous test where only one partition could synthesize at a time under the tight 100 GiB budget. The budget numbers look healthy—750 GiB total, with plenty of headroom as partitions are dispatched. The RSS trace shows memory climbing rapidly but within expected bounds. The assistant then launches a 120-second wait to check completion, fully expecting success.

But the next message (index 2369) reveals the truth: the daemon was OOM-killed. The transport error and broken pipe reported by the bench client signal that the CUZK process was terminated by the Linux kernel's out-of-memory killer when RSS hit approximately 498 GiB while Curio (a co-located process) consumed another ~87 GiB, pushing the system past its 755 GiB physical memory limit.

Why This Message Was Written: Reasoning and Motivation

The assistant wrote this message to document a successful validation of the memory manager's core mechanism. The preceding ten messages in the conversation tell a story of iterative debugging:

  1. The blocking_lock panic (messages 2358-2359): The evictor callback used blocking_lock() on a tokio Mutex from within an async context, causing a runtime panic. The assistant fixed this by switching to try_lock().
  2. The serialization problem (messages 2353-2355): With a tight 100 GiB budget, only one partition could synthesize at a time because the 44 GiB SRS + 26 GiB PCE baseline left only ~30 GiB for working sets—barely enough for two partitions. The user explicitly noted this regression: "Seems there is only one synthesis running at a time, previously the machine was handling 10 or 8."
  3. The SRS double-acquisition race (messages 2356-2359): Three concurrent proofs each independently checked is_loaded() and pre-acquired 44 GiB for SRS before any had actually loaded it, temporarily reserving 132 GiB for a resource that only needed 44 GiB. The assistant's motivation in message 2368 is to demonstrate that all three issues are resolved. The blocking_lock panic is fixed (no crash on startup). The serialization is fixed (30 partitions start within a second). The SRS race, while still present, is quickly resolved as the reservations collapse once SRS is actually loaded. The message is written with visible relief and satisfaction—"Now we're talking"—marking a turning point after hours of debugging.

How Decisions Were Made

The key decision visible in this message is the switch from a manually configured 100 GiB budget to total_budget = "auto" with safety_margin = "5GiB". This decision was made in message 2364, where the assistant wrote the new configuration:

[memory]
total_budget = "auto"
safety_margin = "5GiB"
eviction_min_idle = "5m"

The reasoning was straightforward: the 100 GiB budget was intentionally tight for testing, but the user's machine has 755 GiB RAM and previously ran 8-10 partitions concurrently without any memory constraints. The assistant correctly identified that the budget was the bottleneck and that switching to auto-detection would allow the system to use the full available memory. The safety_margin = "5GiB" was chosen to leave a small buffer for the kernel and other processes—a decision that would prove catastrophically insufficient.

The assistant also increased synthesis_concurrency from 2 to 4, though this turned out to be irrelevant: the budget itself became the effective concurrency limiter once it was large enough.

Assumptions Made by the Assistant

This message rests on several critical assumptions, some explicit and some implicit:

  1. The 5 GiB safety margin is sufficient: The assistant assumed that subtracting 5 GiB from the total system memory (755 GiB → 750 GiB budget) would leave enough headroom for the kernel, Curio, and other processes. In reality, Curio alone was using ~87 GiB of shared memory, and the kernel and other services consumed additional memory. The effective available memory for CUZK was closer to 500-550 GiB, not 750 GiB.
  2. Auto-detection of total memory is safe: The auto setting detects the system's total physical RAM (755 GiB) and subtracts the safety margin. The assistant assumed this would be a reasonable upper bound, but it didn't account for memory already committed to other processes.
  3. The budget system accurately tracks all memory: The budget tracks explicit reservations (SRS, PCE, partition working sets) but does not account for CUDA pinned memory, transient allocations during synthesis, or memory fragmentation. The actual RSS of ~498 GiB at crash time may have been significantly higher than the budget's accounting of reserved memory.
  4. 30 partitions starting simultaneously is desirable: The assistant celebrates that all 30 partitions started within a second, but this very behavior contributed to the OOM. The old system with partition_workers = 16 naturally limited concurrency to 16 partitions. The budget system, with 750 GiB available, allowed all 30 to start immediately because the budget math showed enough room—but the budget math was wrong.

Mistakes and Incorrect Assumptions

The most significant mistake is the safety margin. The assistant had access to information that should have informed a larger margin. In message 2355, the assistant noted that Curio was using ~87 GiB of shared memory. The free -h output from earlier in the session showed available memory of approximately 528 GiB, not 755 GiB. The assistant had this data but failed to incorporate it into the safety margin calculation.

A secondary mistake is celebrating the SRS race as "resolved quickly." The budget trace shows budget_used_gib=132 immediately after SRS loading, meaning three concurrent proofs each reserved 44 GiB for SRS before any had loaded it. While the reservations did collapse once SRS was actually loaded, the temporary over-reservation of 88 GiB contributed to the budget illusion—the system thought it had more headroom than it actually did, because the SRS reservations would eventually be released.

The assistant also failed to account for the fact that PCE extraction threads consume memory outside the budget system. The 26 GiB PCE baseline is an estimate of the cached PCE data, but the extraction process itself involves temporary allocations that aren't tracked by the budget.

Input Knowledge Required to Understand This Message

To fully grasp this message, a reader needs to understand:

  1. The CUZK proving pipeline: Filecoin proofs (PoRep) involve synthesizing constraint systems and then proving them on GPUs. Each proof is split into 10 partitions, each with ~130 million constraints. Synthesis is CPU-intensive and memory-intensive.
  2. The memory manager architecture: The assistant has built a budget-based admission control system where each component (SRS, PCE, partition synthesis) must acquire a reservation from a shared budget before allocating memory. The budget is implemented with a tokio-aware semaphore that can block callers when insufficient budget is available.
  3. SRS and PCE: The Structured Reference String (SRS) is a ~44 GiB cryptographic parameter file used by all proofs. The Pre-Compiled Constraint Evaluator (PCE) is a ~26 GiB compiled circuit representation. Both are loaded once and shared across proofs.
  4. The deployment environment: A remote machine with 755 GiB RAM, an RTX 5090 GPU, 64 CPU cores, running both CUZK and Curio (a Filecoin storage mining daemon).
  5. The preceding debugging session: The blocking_lock panic fix, the 100 GiB budget test, and the SRS race diagnosis are all essential context for understanding why this message represents a milestone.

Output Knowledge Created by This Message

This message creates several important pieces of knowledge:

  1. The budget system works at scale: All 30 partitions started within one second, proving that the budget-based admission control can handle high concurrency when sufficient budget is available.
  2. The SRS race is a real but manageable issue: Three concurrent proofs each pre-acquire SRS budget, but the reservations collapse once SRS is actually loaded. This is a performance issue (temporary over-reservation) but not a correctness issue.
  3. The budget accounting is incomplete: The RSS trace shows memory climbing to 273 GiB within 30 seconds, while the budget accounting shows comfortable headroom. The discrepancy between budget-tracked memory and actual RSS is a warning sign that the budget system doesn't capture all memory usage.
  4. The safety margin is the critical vulnerability: The 5 GiB margin is clearly insufficient for a machine running multiple services. This message implicitly sets up the discovery in the next message that OOM is the real threat.

The Thinking Process Visible in the Message

The assistant's reasoning is visible in the structure of the message. The bullet points show a systematic check of the system's state:

The Broader Context: A Debugging Arc

This message sits at a critical inflection point in a longer debugging arc that spans segments 14 through 17 of the conversation. The arc began with a design document for a unified memory manager (segment 14), followed by implementation (segments 15-16), and now real-world validation (segment 17). The arc follows a classic pattern:

  1. Design: Specify the ideal system
  2. Implementation: Build the system
  3. Unit testing: Verify components in isolation
  4. Integration testing: Verify the system works
  5. Real-world testing: Discover what the design missed Message 2368 is the "integration testing" phase that looks successful but immediately transitions into "real-world testing" phase where the OOM crash reveals the design flaw. The assistant's assumption that auto detection of total system memory is safe ignores the reality of co-located processes—a classic systems engineering mistake.

Conclusion: The Lesson of the Safety Margin

The message at index 2368 is a study in the gap between "the system works as designed" and "the system works in production." The budget-based memory manager correctly gates memory allocations, prevents overcommitment, and enables high concurrency. But it only works if the budget reflects reality. By using auto detection of total system memory without accounting for co-located processes, the assistant created a budget that was 200+ GiB too optimistic.

The lesson is that safety margins in memory-constrained systems must account for the entire system, not just the component being managed. A 5 GiB margin is appropriate for a dedicated machine, but on a machine running Curio, the kernel, and other services, the margin needs to be 200-250 GiB. The assistant eventually arrives at this conclusion in message 2369, where the plan becomes "increase safety margin to 250 GiB or set explicit cap at 500 GiB."

This message also illustrates the danger of celebrating too early in debugging. The assistant's excitement at seeing 30 partitions start within a second is understandable—it's a dramatic improvement over the serialized synthesis of the 100 GiB test. But the very mechanism that enables this concurrency—a budget that appears to have plenty of room—is what leads to the OOM crash. The system works, but it works too well, consuming memory that belongs to other processes. The triumph is real, but it is a triumph that immediately reveals its own limits.