The Microbenchmark Pivot: How a Single Message Rescued Phase 4 of the cuzk SNARK Engine

"That's exactly what we need. Let me build a quick synth-only subcommand for fast A/B iteration."

This single sentence, spoken by the AI assistant in message 1001 of a long-running coding session, marks a critical turning point in the performance engineering of the cuzk pipelined SNARK proving engine for Filecoin. The message itself is deceptively brief — a confirmation and a todo-list update — but it sits at the confluence of a multi-day regression diagnosis that had already consumed dozens of messages and involved reverting optimizations, instrumenting CUDA kernels, and running end-to-end GPU proofs. To understand why this message matters, one must understand the crisis that preceded it.

The Phase 4 Regression Crisis

By the time we reach message 1001, the cuzk project has already achieved remarkable results. Phases 0 through 3 are complete and committed: a pipelined SNARK proving engine that can generate a 32 GiB PoRep C2 proof in 88.9 seconds — a solid baseline. Phase 4, however, is the compute-optimization phase, and it has gone badly wrong.

Five optimizations from the design document c2-optimization-proposal-4.md were implemented as "Wave 1 quick wins":

The Diagnosis Unfolds

The assistant's disciplined approach to performance engineering is visible in the preceding messages. First, CUDA timing instrumentation (CUZK_TIMING printf's) was added to the GPU code to get phase-level breakdowns. Then the A2 pre-sizing optimization was partially reverted from the pipeline code. A build-system nuance was discovered — CUDA compilation artifacts live outside cargo's standard output directory and weren't being invalidated properly. The printf output was being lost due to full buffering when stdout was redirected to a file, requiring a fix to use fprintf(stderr, ...) with fflush.

Once the timing data was finally collected, the culprit was clear: B1 (cudaHostRegister) added 5.7 seconds of overhead by touching every page of ~125 GiB of host memory, far exceeding the estimated 150-300 ms. Reverting B1 brought the total down to 94.4s, but synthesis was still 60.3s vs the 54.7s baseline — a 5.6s regression that had to be explained.

The SmallVec Mystery

The only synthesis change remaining was A1 (SmallVec). The assistant's reasoning in message 992 shows deep microarchitectural analysis: each (usize, Scalar) tuple is 40 bytes, and with INDEXER_INLINE_CAP = 4, each Indexer struct balloons from ~24 bytes (Vec: pointer + length + capacity) to ~170 bytes (SmallVec: inline buffer + discriminant + length). During the enforce() hot loop — called millions of times during parallel synthesis — three LinearCombination objects are created, each containing two Indexers, totaling ~1020 bytes of inline stack data per call versus ~144 bytes with Vec.

The user's response to the assistant's question about investigation strategy was "Fit to cache line? Consider CPU caches, maybe avx ops" — prompting the assistant to consider Zen4 cache characteristics. The assistant then changed the inline capacity from 4 to 1, reasoning that most LCs have exactly one term, and a 56-byte Indexer would fit in a single cache line.

But the user then asked: "Mircobench possible?" — suggesting a faster iteration method than the full end-to-end daemon test that required GPU proving, SRS loading, and daemon startup.

Message 1001: The Pivot

Message 1001 is the assistant's response to that suggestion. The full text reads:

[assistant] That's exactly what we need. Let me build a quick synth-only subcommand for fast A/B iteration. [todowrite] {"todos":[{"content":"Finish reverting A2 from synthesize_porep_c2_batch call in pipeline.rs (~line 750)","priority":"high","status":"completed"},{"content":"Build with --features cuda-supraseal","priority":"high","status":"completed"},{"content":"Run instrumented single-proof test to see CUZK_TIMIN... [ { "content": "Finish reverting A2 from synthesize_porep_c2_batch call in pipeline.rs (~line 750)", "status": "completed", "priority": "high" }, { "content": "Build with --features cuda-supraseal", "status": "completed", "priority": "high" }, { "content": "Run instrumented single-proof test to see CUZK_TIMING breakdown", "status": "completed", "priority": "high" }, { "content": "Analyze timing data and decide which changes to keep/revert", ... ]

The message is doing two things simultaneously. First, it's acknowledging the user's suggestion and committing to build a dedicated microbenchmark — a standalone subcommand that times only the circuit synthesis path without needing the daemon, GPU, or SRS loading. Second, it's updating the todo list to reflect what has been accomplished and what remains.

The Thinking Process

The assistant's reasoning in this message is implicit but can be reconstructed from the context. The key insight is that the full end-to-end test cycle is slow: start daemon (~2s SRS load), run proof (~90s), collect logs, kill daemon. To test four SmallVec configurations (Vec, cap=1, cap=2, cap=4) with multiple iterations each, this would take hours. A synth-only microbenchmark that calls synthesize_porep_c2_batch() directly and times just the CPU synthesis would complete in ~55 seconds per configuration — and since it doesn't need the GPU or daemon, multiple configurations can be tested in rapid succession.

The todo list update is also revealing. Three high-priority items are marked completed: reverting A2, building with CUDA features, and running the instrumented test. These were the blocking items that had to be finished before the microbenchmark approach could bear fruit. The fourth item — "Analyze timing data and decide which changes to keep/revert" — remains open, and the microbenchmark is the tool to resolve it.

Assumptions and Input Knowledge

This message makes several assumptions. It assumes that the synthesis path can be cleanly isolated from the GPU proving path — that synthesize_porep_c2_batch() can be called standalone without initializing CUDA context or loading SRS. It assumes that the C1 JSON input file contains all the data needed for synthesis (which it does — the C1 output includes the circuit inputs). It assumes that the cuzk-bench binary can be extended with a new subcommand without excessive refactoring.

The input knowledge required to understand this message is substantial. One must know:

The Output Knowledge Created

This message creates a clear decision point. The todo list formalizes the state of the investigation: three blocking items are done, and the path forward is to build the microbenchmark. In the messages that follow (1002-1034), the assistant reads main.rs, adds the SynthOnly subcommand with feature-gated cuzk-core dependency, builds it, and runs the four configurations. The results are definitive:

| Configuration | Synthesis avg | Delta vs Vec | |---|---|---| | Vec (original) | 55.4s | baseline | | SmallVec cap=1 | 59.8s | +8.0% slower | | SmallVec cap=2 | 56.6s | +2.4% slower | | SmallVec cap=4 | 61.1s | +10.5% slower |

SmallVec is categorically slower on this Zen4 Threadripper PRO 7995WX system. The hypothesis that Zen4's jemalloc thread-local cache is fast enough (~10-15ns per allocation) that the larger SmallVec stack frames cause more L1d cache pressure than they save in allocation overhead is confirmed.

The Broader Significance

Message 1001 exemplifies disciplined performance engineering. When faced with a confusing regression, the assistant did not guess or rely on intuition — it built instrumentation, collected data, reverted one optimization at a time, and when the iteration cycle was too slow, it built a faster tool. The synth-only microbenchmark reduced the test cycle from ~90 seconds (full E2E) to ~55 seconds (synthesis only), and more importantly, eliminated the GPU dependency entirely, allowing rapid A/B testing of four configurations in minutes.

The message also demonstrates the importance of listening to user suggestions. The user's simple question "Mircobench possible?" triggered a tool-building effort that conclusively resolved the regression and saved the Phase 4 Wave 1 commit from including a harmful optimization. Without the microbenchmark, the team might have accepted the 6s synthesis regression, attributing it to noise or other factors, and committed a net-negative change.

In the end, the Phase 4 Wave 1 changes that survive are A4 (parallel B_G2) and D4 (per-MSM window tuning) — both genuine improvements that shave ~0.5s off the GPU phase. The synthesis regression is avoided entirely by reverting A1 back to Vec. The total with only the helpful changes projects to ~88.5s, a slight but real improvement over the 88.9s baseline. Message 1001 is the pivot point that made this outcome possible.