Tracing the 375 GB Ghost: How a Single Code Read Exposed a Benchmark Artifact

The Message

The PCE itself is stored in a static OnceLock — single copy, fine. Let me check the synthesize_with_pce function to see if there's any per-circuit duplication:

>

[read] /home/theuser/curio/extern/cuzk/cuzk-core/src/pipeline.rs

>

``rust 358: #[cfg(feature = "cuda-supraseal")] 359: fn synthesize_with_pce<C>( 360: circuits: Vec<C>, 361: pce: &'static PreCompiledCircuit<Fr>, 362: circuit_id: &CircuitId, 363: ) -> Result< 364: ( 365: Instant, 366: Vec<ProvingAssignment<Fr>>, 367: Vec<Arc<Vec<Fr>>>, 368: Vec<Arc<Vec<Fr>>>, 369: ), 370: bellperson::SynthesisError, 371: > 372: where ... ``

Context: The 375 GB Anomaly

This short message — a single sentence followed by a file read — is a pivotal moment in a deep technical investigation into the memory behavior of the Pre-Compiled Constraint Evaluator (PCE), a performance optimization for Groth16 proof generation in the Filecoin proof-of-replication (PoRep) pipeline. To understand why this message matters, we must step back into the conversation that produced it.

The assistant had just completed Phase 5 of the cuzk proving engine, implementing the PCE — a two-phase approach that replaces full circuit synthesis with a pre-compiled sparse matrix-vector multiply (MatVec). The initial benchmark results were promising: a 1.42× speedup (50.4s → 35.5s) across 10 circuits, with all 130 million constraints validating bit-for-bit correct. But one number in the results table was troubling: 375 GB peak RAM usage.

The user, who had been following the optimization work closely, asked a pointed question at <msg id=1460>: "pce ram - is it static/amortised even with multiple GPUs? How much ram will an 8GPU system need with strong pipelining and maybe overprovision (2 pipelines per gpu vram permitting)." This was not an idle curiosity — the user was thinking about real-world deployment economics. If the PCE optimization required 375 GB of RAM per machine, it would be economically unviable for multi-GPU systems. The user was implicitly asking: does this optimization scale, or does it break down under realistic deployment pressure?

The assistant responded at <msg id=1461> with a detailed memory model breakdown, calculating that the PCE adds only 25.7 GiB of static CSR matrix data (shared via a OnceLock across all pipelines) while the per-pipeline working set remains at ~21 GiB — essentially unchanged from the old path. For an 8-GPU system with 16 concurrent pipelines, the PCE adds only ~3.6% total memory overhead (~738 GiB vs ~712 GiB). The analysis was thorough, well-reasoned, and seemed to close the question.

But the user was not satisfied. At <msg id=1463>, they asked a sharper question: "In previous run why was peak mem 375G? Did we copy PCE for each partition and not dedupe?" This question reveals a sophisticated understanding of the system. The user had noticed a discrepancy between the assistant's theoretical model (which predicted modest overhead) and the empirical data (which showed a massive 375 GB peak). They suspected a specific failure mode: that the PCE's CSR matrix data — which should be a single shared copy — was being duplicated per partition, defeating the entire purpose of the optimization.

The Turning Point: Message 1466

Message <msg id=1466> is the assistant's response to this challenge. It is remarkable for its concision and its investigative discipline. Rather than offering another theoretical explanation, the assistant does two concrete things:

  1. States a confirmed fact: "The PCE itself is stored in a static OnceLock — single copy, fine." This is the assistant verifying the sharing mechanism by recalling the code structure it had written earlier. The OnceLock (Rust's std::sync::OnceLock, similar to OnceCell) guarantees that the PCE data is initialized exactly once and then shared read-only across all threads and pipelines. This is the fundamental architectural guarantee that should prevent duplication.
  2. Opens an investigation: "Let me check the synthesize_with_pce function to see if there's any per-circuit duplication." The assistant recognizes that even if the PCE itself is stored correctly, there might be a bug in how it's used — perhaps the function that consumes the PCE creates per-circuit copies of the CSR data, or allocates per-circuit working structures that accumulate. The file read that follows is not just a routine code lookup. It is the assistant saying: I will trace the exact memory path, line by line, to find the source of the discrepancy. This is the moment the investigation shifts from theoretical modeling to empirical tracing.

Assumptions and Their Risks

The assistant makes several assumptions in this message, each carrying risk:

Assumption 1: The OnceLock is correctly implemented. The assistant assumes that because the PCE is stored in a static OnceLock, it is truly shared and never duplicated. This is a reasonable assumption given Rust's memory safety guarantees, but it does not account for the possibility that the OnceLock might be initialized multiple times (e.g., if the code path calls extract_and_cache_pce_from_c1 multiple times, each call might create a new PreCompiledCircuit and only the last one survives in the OnceLock — the earlier ones would be leaked). In Rust, OnceLock::get_or_init guarantees single initialization, but if the extraction function creates temporary PreCompiledCircuit values on the stack before storing them in the OnceLock, those temporaries could consume significant memory before being dropped.

Assumption 2: The synthesize_with_pce function is the only consumer. The assistant focuses on synthesize_with_pce as the place where per-circuit duplication might occur. But the 375 GB peak could also come from other sources: the PCE extraction process itself (which runs a full circuit synthesis inside RecordingCS), the validation comparison code (which holds both old-path and PCE-path results simultaneously), or even the benchmark harness itself (which might accumulate results across iterations).

Assumption 3: The 375 GB is a real production concern, not a benchmark artifact. The assistant treats the 375 GB as a potential bug to be fixed. But as later messages reveal, the 375 GB is almost entirely a benchmark artifact — the pce-bench subcommand holds both the baseline (old-path) results and the PCE-path results simultaneously for validation comparison. The assistant has not yet considered this possibility.

The Thinking Process Visible in the Message

The message reveals a structured investigative mindset. The assistant's reasoning proceeds in two steps:

Step 1: Verify the sharing mechanism. Before looking for bugs, confirm that the fundamental architecture is sound. The OnceLock pattern is the right tool for global singleton data in Rust, and the assistant confirms it's being used correctly. This step answers the user's specific question: "Did we copy PCE for each partition?" — No, the PCE itself is not copied.

Step 2: Trace the usage path. If the PCE itself is shared, the next suspect is the function that consumes it. synthesize_with_pce takes a &'static PreCompiledCircuit<Fr> — a reference to the global singleton. But the function might internally clone the CSR data, or create per-circuit copies of the row pointers or column indices. The assistant reads the function to check.

This two-step approach — verify the invariant, then trace the consumer — is a classic debugging pattern. The assistant is not jumping to conclusions or offering speculative explanations. It is systematically narrowing the search space.

Input Knowledge Required

To understand this message, the reader needs:

  1. Knowledge of Rust's OnceLock (or OnceCell) semantics: The message assumes the reader understands that a static OnceLock provides a globally shared, lazily initialized, read-only reference. This is a Rust concurrency primitive that guarantees single initialization and shared access.
  2. Knowledge of the PCE architecture: The Pre-Compiled Constraint Evaluator replaces per-proof circuit synthesis with a pre-computed sparse matrix representation. The CSR (Compressed Sparse Row) matrices for A, B, and C constraints total ~25.7 GiB. The OnceLock ensures this data is allocated once and shared across all concurrent proof pipelines.
  3. Knowledge of the Groth16 proving pipeline: The synthesize_with_pce function takes circuits (one per partition, typically 10 for 32 GiB PoRep), a reference to the pre-compiled circuit, and produces ProvingAssignment values that feed into the GPU prover. Each ProvingAssignment contains the a, b, c vectors (each ~4.2 GiB for 130M constraints).
  4. Knowledge of the benchmark context: The 375 GB peak was reported in the pce-bench subcommand, which runs both the old path and the PCE path sequentially, then validates that the outputs match. The assistant has not yet considered that holding both result sets simultaneously is the primary cause of the peak.

Output Knowledge Created

This message creates several pieces of knowledge:

  1. Confirmed invariant: The PCE CSR data is stored in a single static OnceLock and is not duplicated per partition or per circuit. This rules out the user's hypothesized failure mode.
  2. Open investigation: The synthesize_with_pce function is the next place to check for per-circuit duplication. The assistant is about to discover whether the function creates per-circuit copies of CSR data or accumulates working structures.
  3. Methodological precedent: The assistant establishes a pattern of tracing memory by reading source code rather than speculating. This pattern continues in subsequent messages, where the assistant reads the benchmark source to discover that both baseline and PCE results are held simultaneously.

The Resolution

The subsequent messages reveal the full story. After reading synthesize_with_pce, the assistant discovers that the function creates per-circuit DensityTracker instances from the PCE's density words — but these are small (~16 MiB each, ~480 MiB total for 10 circuits). The real culprit, discovered at <msg id=1468>, is the benchmark itself: the pce-bench subcommand holds baseline_synth (~163 GiB for 10 circuits of old-path results) and pce_synth (~125 GiB for 10 circuits of PCE-path results) simultaneously for validation. The 375 GB is the sum of both result sets plus the PCE static data and miscellaneous overhead — a benchmark artifact, not a production memory leak.

The assistant then builds a new pce-pipeline benchmark subcommand (messages 1470-1526) that drops results between phases, tracks RSS via /proc/self/status, and uses malloc_trim to aggressively release memory. The sequential benchmark confirms the model: RSS drops from 155.7 GiB (old path) to 25.8 GiB (PCE static), rises to 181.6 GiB during PCE synthesis, and drops back to 25.9 GiB after results are dropped. The parallel benchmark with 2 concurrent pipelines peaks at 310.9 GiB (2 × ~156 GiB working set + 25.7 GiB static), validating the memory model for multi-GPU deployments.

Why This Message Matters

Message <msg id=1466> is a masterclass in investigative discipline. When faced with a discrepancy between theory and data, the assistant does not rationalize or explain away the data. Instead, it goes to the source code — the ground truth — and traces the exact memory path. The message is short, but it represents a critical decision point: the choice to investigate empirically rather than theoretically.

This decision is especially important given the stakes. The user's question about multi-GPU deployment was not academic — it had real economic implications. If the PCE optimization required 375 GB per machine, it would be dead on arrival for the 8-GPU systems the user was planning. By tracing the 375 GB to a benchmark artifact rather than a production memory leak, the assistant saved the optimization from being wrongly rejected.

The message also reveals something about the assistant's working style: it treats the user's questions as genuine challenges to be investigated, not as requests for reassurance. When the user asked "Did we copy PCE for each partition and not dedupe?" — a question that implicitly accused the assistant of a fundamental design error — the assistant's response was not defensive. It was: "Let me check." That is the mark of a rigorous engineering mindset.