The Moment of Truth: Watching the First Real Proof Through the cuzk Daemon

Introduction

In the long arc of building a production-grade SNARK proving engine, there comes a moment when the scaffolding falls away and the system must actually prove something real. For the cuzk project — a pipelined Groth16 proving daemon designed for Filecoin's Proof-of-Replication (PoRep) — that moment arrives in message <msg id=227>. The assistant, having spent hours designing the architecture, implementing Phase 0, fixing build issues, and validating the gRPC pipeline, now watches the daemon consume 142 CPU cores and 203 GiB of RAM as it generates its first real proof. But the message contains a quiet dramatic irony: while the assistant waits for the GPU phase to begin, the proof has already finished.

The Message in Full

The assistant writes:

The daemon is using: - 14253% CPU (~142 cores!) — circuit synthesis is running massively parallel - 203 GiB RSS — the SRS params (45 GiB) + circuit witness + synthesis working memory - 298 GiB VSZ — virtual address space

>

This machine has plenty of cores. Synthesis is running at full tilt. Let me wait for the GPU phase — I'll check every minute: [bash] sleep 60 && echo "=== $(date) ===" && nvidia-smi --query-gpu=utilization.gpu,memory.used,power.draw --format=csv && echo "---" && tail -5 /tmp/cuzk-daemon.log && echo "---" && ps -p 3033808 -o %cpu,rss,etime --no-headers === Tue Feb 17 04:34:42 PM CET 2026 === utilization.gpu [%], memory.used [MiB], power.draw [W] 4 %, 3822 MiB, 46.02 W --- [log output showing verify_seal:finish]

The message is deceptively simple — a status update with a monitoring command — but it carries the weight of the entire session's work. This is the first time the cuzk daemon has been asked to produce a real Groth16 proof for a 32 GiB Filecoin sector, and the numbers are staggering.

Why This Message Was Written

The assistant's motivation is twofold. First, there is the engineering imperative to validate that the system works end-to-end. The previous messages in the conversation show the assistant methodically working through a checklist: build the workspace, enable CUDA features, start the daemon, submit a C1 output, monitor progress. Message <msg id=227> is the monitoring step — the assistant needs to confirm that the proof pipeline is progressing through its phases correctly.

Second, there is a characterization goal. The assistant is not just checking "did it crash?" but rather "what does the resource profile look like?" The numbers — 14253% CPU, 203 GiB RSS, 298 GiB VSZ — are not incidental observations. They are data points that will inform the optimization proposals already drafted in earlier segments. The assistant is gathering empirical evidence to validate or challenge the theoretical models built during the deep-dive investigation of the SUPRASEAL_C2 pipeline.

The broader context is crucial. In <msg id=223>, the assistant had celebrated "phenomenal progress" as the daemon loaded the 45 GiB SRS parameters in ~15 seconds and confirmed that "Bellperson 0.26.0 with SupraSeal is being used!" In <msg id=226>, they observed the daemon at 14253% CPU and 203 GiB RSS, correctly identifying that circuit synthesis was running. Message <msg id=227> is the natural continuation — the assistant expects the GPU phase to begin next and wants to catch it.

The Resource Profile: A Window into Groth16 at Scale

The three resource metrics reported are each significant independently, but together they paint a complete picture of what a 32 GiB PoRep proof generation looks like at the system level.

14253% CPU — This is not a typo or artifact. On a machine with ~160+ logical cores, the daemon is using effectively all of them. The assistant correctly interprets this as "circuit synthesis is running massively parallel." Groth16 proof generation for Filecoin's PoRep involves building a Rank-1 Constraint System (R1CS) with approximately 130 million constraints. Each constraint must be synthesized from the circuit description, which involves hashing operations (SHA-256, Poseidon), Merkle tree traversals, and field arithmetic. The bellperson library, which cuzk delegates to via filecoin-proofs-api, parallelizes this synthesis across available CPU cores. Seeing 14253% means the synthesis is fully utilizing the machine's parallel capacity — a good sign that the CPU-bound phase is not bottlenecked by serial sections.

203 GiB RSS — This is the most startling number. The resident set size of 203 GiB means the daemon is holding over 200 GiB of physical RAM. The assistant breaks this down: the SRS parameters (the Structured Reference String, a large collection of elliptic curve points used in the Groth16 protocol) account for roughly 45 GiB. The remainder — approximately 158 GiB — is the circuit witness and synthesis working memory. This confirms the ~200 GiB peak memory footprint identified in the earlier deep-dive analysis (Segment 0). The witness for a 32 GiB PoRep circuit is enormous because it must store the entire Merkle tree structure, all intermediate hash values, and the constraint system itself. This memory profile is the primary motivation behind the Sequential Partition Synthesis proposal (Proposal 1) from earlier segments, which would stream partitions sequentially rather than holding the entire witness in memory.

298 GiB VSZ — The virtual address space is even larger than RSS, indicating that the process has mapped memory regions it hasn't yet touched. This is typical for a process that allocates large arenas for future use, but it also hints at the memory-mapped file approach used for the SRS parameters. The gap between VSZ and RSS (roughly 95 GiB) represents allocations that exist in the virtual address space but haven't been backed by physical pages yet.

The Dramatic Irony: A Proof Already Complete

The most fascinating aspect of this message is what the assistant doesn't realize. The commentary frames the situation as "Synthesis is running at full tilt. Let me wait for the GPU phase." But the log output included in the command results tells a different story:

found params in memory cache for STACKED[34359738368]-verifying-key
verify_seal:finish: SectorId(1)

The proof has already completed and been internally verified. The GPU phase — the NTT (Number Theoretic Transform) and MSM (Multi-Scalar Multiplication) computations that are the GPU-bound portion of Groth16 — happened silently between the assistant's checks. By the time the assistant runs the monitoring command at 16:34:42, the GPU is already idle at 4% utilization because its work is done.

This is a beautiful moment of dramatic irony for the reader. The assistant, expecting a long wait for the GPU phase, is still mentally in "monitoring for the GPU phase to start" mode, but the system has already moved past it. The 3822 MiB of GPU memory in use (up from 1690 MiB in <msg id=225>) is the residual footprint of the completed GPU computation — the GPU allocated memory for the MSM and NTT operations, ran them, and the memory hasn't been freed yet.

The assistant's assumption — that the GPU phase would be clearly visible as a distinct, lengthy period of high GPU utilization — turns out to be incorrect for this particular workload. On an RTX 5070 Ti (Blackwell architecture, CUDA 13.1), the GPU computation for a 32 GiB PoRep proof completes quickly enough that the assistant misses it entirely when polling at 60-second intervals. This is itself a valuable data point: the GPU is not the bottleneck for single-proof generation. The bottleneck is CPU synthesis, which takes the vast majority of the wall-clock time.

Input Knowledge Required

To fully appreciate this message, the reader needs several layers of context:

  1. Groth16 proof generation pipeline: Understanding that C2 (commit phase 2) proof generation has two major phases — CPU-bound circuit synthesis (building the R1CS constraint system and witness) and GPU-bound computation (NTT and MSM for the elliptic curve operations that produce the final proof).
  2. Filecoin PoRep specifics: The 32 GiB sector size means the circuit has ~130 million constraints, making it one of the largest practical Groth16 circuits in production use. The SRS parameters are ~45 GiB and must be loaded from disk into memory before proving can begin.
  3. The cuzk architecture: The daemon is a gRPC server that wraps filecoin-proofs-api calls, with a priority scheduler and SRS memory management. Phase 0 is the minimal viable implementation — single-threaded proof execution with no pipelining.
  4. System monitoring tools: Understanding ps output format (%cpu as percentage of a single core, RSS in KB), nvidia-smi metrics, and how to interpret them in context.
  5. The project's optimization goals: The earlier segments had identified nine structural bottlenecks and proposed five optimization proposals. The resource numbers in this message validate the memory bottleneck analysis and the need for Sequential Partition Synthesis.

Output Knowledge Created

This message produces several important pieces of knowledge:

  1. Empirical validation of the memory model: The ~200 GiB peak memory footprint, previously estimated from code analysis, is confirmed by actual runtime measurements. The 203 GiB RSS directly validates the analysis from Segment 0.
  2. CPU synthesis is the dominant phase: The assistant's inability to catch the GPU phase in action demonstrates that CPU synthesis dominates the wall-clock time for single-proof generation. This has implications for optimization priorities — improving synthesis throughput (via better parallelization, constraint precomputation, or circuit optimization) would yield larger gains than further GPU optimization.
  3. SRS memory caching works: The log line "found params in memory cache" confirms that the GROTH_PARAM_MEMORY_CACHE mechanism (set by the engine before calling into filecoin-proofs-api) successfully cached the SRS parameters after the initial load. This is the foundation for the SRS residency benefit measured later in the session.
  4. The daemon is production-functional: A 1920-byte Groth16 proof was produced and internally verified. The gRPC pipeline, parameter loading, CUDA backend integration, and proof verification all worked correctly on the first real attempt.

The Thinking Process Visible in the Message

The assistant's reasoning is visible in several dimensions. First, there is the choice of what to monitor: CPU percentage, RSS, VSZ, GPU utilization, GPU memory, and daemon logs. This selection reveals the assistant's mental model of the proof pipeline — they expect to see CPU-heavy synthesis followed by GPU-heavy computation, and they want to correlate system metrics with pipeline phases.

Second, there is the interpretation of the numbers: The assistant immediately converts 14253% CPU into "~142 cores" and correctly attributes it to circuit synthesis. They break down the 203 GiB RSS into SRS params (45 GiB) plus working memory, showing a clear understanding of where memory is consumed.

Third, there is the temporal framing: "Let me wait for the GPU phase — I'll check every minute" reveals the assistant's expectation that the GPU phase will be a distinct, observable period. The choice of a 60-second polling interval is reasonable but, as it turns out, too coarse to catch the GPU computation.

Fourth, there is the implicit validation: The assistant doesn't explicitly state "the proof completed successfully" but includes the log output that proves it. This understated presentation suggests the assistant is focused on the resource characterization rather than the binary success/failure question — the proof working is already expected; the interesting question is how it works.

Conclusion

Message <msg id=227> captures a pivotal moment in the cuzk project: the first real proof generation, observed through the lens of system resource metrics. The numbers — 14253% CPU, 203 GiB RSS, 298 GiB VSZ — are not just impressive statistics; they are empirical validation of the memory and compute models built during the earlier deep-dive investigation. The message also contains a quiet dramatic irony, as the assistant waits for a GPU phase that has already completed, revealing that CPU synthesis is the true bottleneck for single-proof throughput.

This message exemplifies the engineering mindset that characterizes the entire session: build the thing, run the thing, measure the thing, and let the measurements guide the next iteration. The proof worked. The numbers are known. The optimization work can now proceed with empirical grounding.