The First Breath of Phase 7: Validating Per-Partition Dispatch in the cuzk SNARK Proving Engine

On February 18, 2026, at 23:36 UTC, a single command echoed across a terminal session that marked the culmination of weeks of architectural design and implementation work. The assistant typed:

cd /home/theuser/curio/extern/cuzk && ./target/release/cuzk-bench batch --type porep --c1 /data/32gbench/c1.json -c 1 -j 1 2>&1

And the machine answered:

=== Batch Benchmark ===
proof type:  porep
count:       1
concurrency: 1

  [1/1] COMPLETED — 72.8s (prove=38849 ms, queue=251 ms)

=== Batch Summary ===
total time:    72.8s
completed:     1
failed:        0
wall time:     avg=72.8s min=72.8s max=72.8s
prove time:    avg=38.8s min=38.8s max=38.8s
throughput:    0.824 proofs/min (72.8s/proof)

This message — message 2106 in the conversation — is the first benchmark of Phase 7 of the cuzk SNARK proving engine, a fundamental architectural shift that treats each of the 10 PoRep partitions as an independent work unit flowing through the engine pipeline. It is a deceptively simple output: a single number, 72.8 seconds, representing the cold-start latency of one Groth16 proof for Filecoin's Proof-of-Replication (PoRep) circuit. But behind that number lies an intricate story of design decisions, performance engineering, and the iterative pursuit of GPU saturation.

The Context: Why This Message Exists

To understand why this message was written, one must understand the journey that led to it. The cuzk project is an open-source GPU-accelerated proving engine for Filecoin storage proofs. The core challenge is generating Groth16 proofs for the PoRep circuit, which involves 10 partitions of computation that must be synthesized and then proved on a GPU. The original architecture suffered from a "thundering-herd" pattern: all 10 partitions were synthesized simultaneously, then all 10 were fed to the GPU in a single monolithic call with num_circuits=10. This caused massive GPU idle gaps, memory spikes of ~200 GiB, and poor utilization.

Phase 7, designed in the document c2-optimization-proposal-7.md and implemented across 578 lines of changes in 4 files, fundamentally rearchitected this flow. Instead of treating a proof as a single monolithic unit, each partition became an independent work item. The engine's process_batch() function was refactored to dispatch partitions through a semaphore-gated pool of 20 spawn_blocking workers, each synthesizing one partition and then sending it to a GPU worker that proved partitions one at a time with num_circuits=1. The predicted benefit was dramatic: instead of a 25-second b_g2_msm for 10 circuits, each partition would enjoy a ~0.4s b_g2_msm, and the GPU would stay continuously busy as partitions streamed through.

The code was committed as f5bfb669 on the feat/cuzk branch. But a commit is just text on disk. The real question was: does it work? And how fast is it?

This message is the answer to that question. It is the first empirical validation of the Phase 7 architecture, the moment when theory meets reality.

What the Message Reveals: Reading the Numbers

The output contains several critical data points. The total wall time of 72.8 seconds includes everything: loading the C1 output from disk, parsing it, synthesizing all 10 partitions (the cold-start synthesis phase), proving each partition on the GPU, assembling the final proof, and returning the result. The "prove" time of 38.8 seconds represents the GPU portion — the time spent in generate_groth16_proofs_c across all 10 partitions. The queue time of 251ms is negligible, indicating the request was handled promptly.

The 38.8-second prove time is particularly revealing. With 10 partitions, this averages to approximately 3.9 seconds per partition. This aligns closely with the theoretical prediction from the Phase 7 design: each partition, with num_circuits=1, should complete its GPU work in roughly 3.5–4.0 seconds, dominated by the multi-scalar multiplication (MSM) and number-theoretic transform (NTT) operations. The old architecture, with num_circuits=10, had a b_g2_msm of ~25 seconds; Phase 7 reduces this to ~0.4 seconds per partition, a 60x improvement in that specific operation.

The 72.8-second total also reveals the synthesis overhead. Subtracting the 38.8-second prove time from the 72.8-second total gives approximately 34 seconds for synthesis, C1 parsing, SRS loading, and other overhead. This is the cold-start penalty — on a warm daemon with preloaded SRS, subsequent proofs would skip the SRS loading and potentially reuse synthesized data.

The Deeper Significance: A Working Architecture

Beyond the raw numbers, this message is significant because it proves that the Phase 7 architecture works correctly. The benchmark completed successfully with zero failures. The proof was assembled from 10 individual partition proofs into the final 1920-byte Groth16 proof. Every component of the new architecture — the PartitionedJobState tracker, the ProofAssembler that collects partition proofs, the partition_semaphore that gates concurrent synthesis, the partition-aware GPU worker routing, the malloc_trim(0) call after each partition to release memory — all of it functioned as designed.

This is not trivial. The Phase 7 implementation touched the most critical path in the entire proving engine: the process_batch() dispatch function, the GPU worker loop, and the job tracking infrastructure. A single bug could have caused deadlocks, dropped proofs, memory corruption, or incorrect proof assembly. The fact that the benchmark produced a valid proof on the first attempt is a testament to the careful design and the systematic testing approach.

The Thinking Process: A Methodical Validation

The assistant's reasoning, visible in the surrounding messages, reveals a methodical, measurement-driven engineering approach. Before running this benchmark, the assistant:

  1. Verified the build: Ran cargo check and cargo build across all crates (cuzk-core, cuzk-daemon, cuzk-bench) to ensure the code compiled cleanly with no warnings.
  2. Reviewed the diff: Examined the full 578-line diff to verify correctness before committing.
  3. Created a dedicated config: Wrote /tmp/cuzk-phase7.toml with partition_workers = 20 and appropriate settings for the test.
  4. Cleaned up the environment: Killed any existing daemon processes to avoid port conflicts and stale state.
  5. Started the daemon: Launched the daemon with nohup and waited for SRS preloading to complete, confirmed by log messages showing "SRS preload complete".
  6. Planned the test sequence: Created a todo list with clear steps: single-proof latency, then multi-proof throughput at various concurrency levels. The single-proof test with -c 1 -j 1 (count=1, concurrency=1) was deliberately chosen as the first test. It is the simplest possible benchmark: one proof, one concurrent request. This minimizes variables and produces a clean baseline. If anything were wrong with the Phase 7 implementation, this test would reveal it immediately with the clearest signal.

Assumptions and Their Validity

The assistant made several assumptions in this message. First, that the daemon was properly configured and running with the Phase 7 settings. The daemon logs confirmed partition_workers=20 was active, validating this assumption.

Second, that the benchmark tool (cuzk-bench) was correctly built against the Phase 7 code. The assistant had rebuilt the bench binary after the Phase 7 commit, ensuring it linked against the new engine code.

Third, that the C1 test data at /data/32gbench/c1.json was valid and representative. This 51 MB JSON file contains the pre-computed C1 output for a 32 GiB sector, which is the standard test vector used throughout the project.

Fourth, that a single-proof latency of 72.8 seconds was reasonable for a cold start. This assumption was validated by the subsequent analysis in message 2107, where the assistant examined the daemon logs and confirmed that all 10 partitions were synthesized and GPU-proved individually, with each GPU call taking 3.3–3.9 seconds.

What This Message Does Not Say

The 72.8-second number is just the beginning. This message does not reveal the multi-proof throughput, which is where Phase 7 was expected to shine. The assistant immediately proceeded to run throughput tests with 5 proofs at concurrency levels 3 and 2 (messages 2110 and 2111), achieving ~45–50 seconds per proof wall-clock time — a significant improvement over the single-proof cold-start latency.

Nor does this message reveal the GPU utilization patterns. The user's observation in message 2112 that "GPU use is pretty jumpy" pointed to the next optimization frontier: the per-job overhead and pipeline smoothness. The assistant's subsequent analysis revealed that the inter-partition GPU gaps were caused by CPU-side contention (mutex locking in generate_groth16_proofs_c, proof serialization, malloc_trim), leading directly to the design of Phase 8's dual-GPU-worker interlock.

Input and Output Knowledge

The input knowledge required to understand this message includes: the Phase 7 architecture specification, the cuzk proving engine's pipeline model, the PoRep circuit structure with 10 partitions, the benchmark tool's command-line interface, and the concept of cold-start vs. warm-proof latency.

The output knowledge created by this message is concrete and actionable: the Phase 7 architecture works, the baseline cold-start latency is 72.8 seconds, the GPU prove time is 38.8 seconds (3.9s per partition), and the synthesis overhead is approximately 34 seconds. These numbers become the baseline against which all future optimizations are measured.

Conclusion

Message 2106 is a milestone in the cuzk project's optimization journey. It represents the first successful validation of a fundamental architectural change — the shift from monolithic proof generation to per-partition dispatch. The 72.8-second number is not just a latency measurement; it is proof that the design works, that the code compiles and runs, and that the predicted performance characteristics hold in practice. From this single data point, the assistant would go on to diagnose GPU utilization gaps, design the Phase 8 dual-worker interlock, and continue pushing toward the goal of continuous, memory-efficient, GPU-saturated proof generation.

In the broader narrative of the cuzk project, this message is the moment when Phase 7 transitioned from theory to reality. The architecture was no longer a design document; it was running code, producing real proofs, and generating real data. The 72.8 seconds would soon be improved upon, but this first breath of Phase 7 remains a critical reference point — the baseline from which all future progress was measured.