The Benchmark That Confirmed a Hard Limit: Why Thread Pool Isolation Couldn't Fix Synthesis Contention

Introduction

In the course of optimizing the cuzk SNARK proving engine for Filecoin PoRep C2 proofs, a critical experiment unfolded in message [msg 1971]. This message, seemingly a routine benchmark invocation, actually represents the culmination of a carefully constructed hypothesis about thread pool isolation — and the moment that hypothesis collided with an immutable hardware constraint. The assistant had just implemented a lazy-initialized thread pool to separate CPU synthesis threads from GPU helper threads, and was now running a benchmark to validate whether this architectural change could improve overall proving throughput. The results would prove disappointing but deeply informative, revealing that the synthesis phase of Groth16 proof generation is so aggressively parallel that it demands every available logical core, and that no amount of thread management finesse can circumvent this fundamental requirement.

The Message in Full

The target message reads as follows:

[assistant] Daemon is ready. Run the benchmark:
[bash] /home/theuser/curio/extern/cuzk/target/release/cuzk-bench \
  -a http://127.0.0.1:9820 \
  batch -t porep --c1 /data/32gbench/c1.json \
  --count 5 --concurrency 2 2>&1
[2m2026-02-18T20:26:27.236383Z[0m [32m INFO[0m [2mcuzk_bench[0m[2m:[0m loading C1 output [3mpath[0m[2m=[0m/data/32gbench/c1.json
=== Batch Benchmark ===
proof type:  porep
count:       5
concurrency: 2

  [1/5] COMPLETED — 109.4s (prove=32871 ms, queue=26501 ms)
  [2/5] COMPLETED — 74.6s (prove=26229 ms, queue=251 ms)
  [3/5] COMPLETED — 76.4s (prove=27889 ms, queue=2009 ms)
  [4/5] COMPLETED — 81.0s (prove=28563 ms, queue=1531 ms)
  [5/5] COMPLETED — 78.8s (prove=25949 ms,...

At first glance, this is simply a benchmark run completing. But to understand its significance, one must trace the chain of reasoning that led to this exact moment.

The Context: Thread Pool Isolation and the Contention Hypothesis

The story begins several messages earlier. The cuzk proving engine uses two distinct thread pools: a rayon thread pool for CPU-side synthesis (witness generation, SpMV evaluation, polynomial operations) and a GPU thread pool (the groth16_pool) for managing GPU-side operations like multi-scalar multiplication (MSM) and number-theoretic transforms (NTT). In the original code, both pools competed for the same set of logical cores — all 192 hyperthreads on the 96-core AMD EPYC system. The assistant hypothesized that this competition was causing performance degradation: when the GPU pool's threads (used for b_g2_msm, a ~25s single-threaded operation that gets parallelized across many circuits) contended with the rayon synthesis threads, both suffered.

Messages [msg 1934] through [msg 1950] implemented a solution: replace the global groth16_pool variable with a lazy-initialized pool accessed through get_groth16_pool(), allowing the daemon to configure the GPU thread count independently of the rayon thread count. The configuration was exposed through the daemon's TOML config file, with parameters like rayon_threads and gpu_threads.

The first benchmark with this isolation ([msg 1962]) used a config of rayon_threads=64, gpu_threads=32 — 64 threads for synthesis, 32 for GPU operations. The results were marginally better than baseline (45.4s/proof vs 46.1s/proof) but synthesis had slowed from 39s to 46s. The assistant analyzed this in [msg 1965]:

"The problem is clear: reducing rayon threads to 64 makes synthesis slower (46s vs 39s), which more than offsets the reduced contention benefit. The synthesis is CPU-bound and needs many threads."

The assistant then formulated a new hypothesis: what if synthesis was given 96 threads (all physical cores, no hyperthreading) while GPU got 32? The reasoning was that synthesis only needed to complete faster than GPU time (~27s), so even 35s synthesis would be acceptable as long as the pipeline didn't stall. This led to the creation of a new config file (/tmp/cuzk-isolated2.toml) and the daemon restart that preceded the target message.

Why This Message Was Written

The target message was written to execute a controlled experiment. The assistant needed to answer a specific question: Does giving synthesis 96 physical cores (while limiting GPU to 32) improve throughput over the 64/32 split, or does synthesis still suffer from the reduced thread count?

This was not a casual benchmark. The assistant had already invested significant effort:

  1. Implementing the thread pool isolation code change (messages [msg 1934]-[msg 1950])
  2. Rebuilding the daemon ([msg 1950])
  3. Running the first benchmark with 64/32 split ([msg 1962])
  4. Analyzing those results and formulating the new hypothesis ([msg 1965])
  5. Creating the new config and restarting the daemon ([msg 1966]-[msg 1970]) The target message represents the payoff of this entire chain: the moment of measurement that would validate or invalidate the hypothesis.

The Decisions Made

Several decisions are embedded in this message:

Decision 1: Benchmark parameters. The assistant chose --count 5 --concurrency 2. Five proofs provides enough samples to measure steady-state behavior (after the first proof's PCE cache miss), while concurrency 2 means two proof requests are submitted in parallel, testing the pipeline's ability to overlap synthesis and GPU work.

Decision 2: The specific config tested. The config used synth_threads=96, gpu_threads=32. This was based on the system's topology: 96 physical cores with hyperthreading giving 192 logical cores. The assistant reasoned that 96 threads would occupy all physical cores without hyperthread contention, while 32 GPU threads would be sufficient for the GPU-side operations.

Decision 3: The benchmark tool and endpoint. The assistant used cuzk-bench pointing at http://127.0.0.1:9820, the local daemon instance. This is an HTTP-based benchmark that submits proof requests through the daemon's REST API, measuring end-to-end time including queue wait.

Decision 4: Proceeding despite operational difficulties. The daemon startup had been problematic — messages [msg 1966]-[msg 1968] show the log file wasn't created due to shell backgrounding issues, requiring a switch to nohup and disown in [msg 1969]. The assistant persevered through these operational hurdles to get the benchmark running.

Assumptions Made

The message and its surrounding context reveal several assumptions:

Assumption 1: 96 rayon threads would be sufficient for synthesis. The assistant assumed that giving synthesis all physical cores (96) would restore its performance close to the baseline 39s. This proved incorrect — synthesis still took 47-48s, as revealed in the subsequent analysis ([msg 1972]).

Assumption 2: The bottleneck is thread contention, not absolute thread count. The assistant assumed that the baseline's 192-thread synthesis was faster primarily because it had more threads, and that reducing to 96 would still be "enough" because the GPU pool's threads were now isolated. In reality, synthesis scales almost linearly with thread count up to 192 threads, and reducing to 96 cuts performance proportionally.

Assumption 3: The daemon would start cleanly. The operational difficulties with daemon startup (messages [msg 1966]-[msg 1969]) show the assistant assumed a simple command > log 2>&1 & would work, but the bash tool's environment didn't handle this correctly. This required debugging and a workaround.

Assumption 4: The benchmark results would be comparable to the previous run. The assistant assumed that changing only the thread counts would produce comparable results, but the first proof's 109.4s total time (with 26.5s queue wait) suggests the PCE wasn't preloaded, adding noise to the measurement.

Mistakes and Incorrect Assumptions

The most significant mistake was the core hypothesis itself: that thread pool isolation could improve throughput by reducing contention. The benchmark results show that:

Input Knowledge Required

To fully understand this message, one needs:

  1. The cuzk proving engine architecture: Understanding that proof generation has two phases — CPU synthesis (witness generation + SpMV evaluation) and GPU proving (MSM, NTT, and other elliptic curve operations). These phases communicate through a channel-based pipeline.
  2. The thread pool model: The rayon thread pool handles synthesis; the groth16_pool handles GPU-side operations. Both were originally global and unconfigured.
  3. The system's hardware topology: 96 physical cores with hyperthreading (192 logical), ~754 GiB RAM, NVIDIA GPUs for CUDA operations.
  4. The benchmark methodology: cuzk-bench batch submits proof requests through the daemon's HTTP API. --count 5 runs 5 proofs, --concurrency 2 submits 2 in parallel. The output shows total wall time, prove time (GPU + CPU work), and queue wait time.
  5. The previous benchmark results: The baseline of ~46s/proof with 39s synthesis and ~71% GPU utilization, and the first isolated run with 64/32 split showing 45.4s/proof with 46s synthesis.
  6. The thread pool isolation change: The replacement of groth16_pool with get_groth16_pool() using std::call_once for lazy initialization, allowing configurable thread counts.

Output Knowledge Created

This message produced several pieces of critical knowledge:

  1. Quantitative benchmark data: Five proof completion times with detailed breakdown (prove time vs queue wait). The first proof at 109.4s establishes the cold-start cost; subsequent proofs at 74-81s represent steady-state.
  2. Confirmation of the synthesis thread scaling hypothesis: The results show that synthesis time is directly proportional to available threads. Reducing from 192 to 96 threads increases synthesis from ~39s to ~47-48s, a ~20% slowdown that matches the ~50% reduction in thread count (accounting for hyperthreading efficiency).
  3. Evidence against thread pool isolation as a standalone fix: The benchmark demonstrates that thread pool isolation, while architecturally cleaner, does not improve throughput when it reduces synthesis thread count. The GPU utilization gain (from ~71% to ~78%) is insufficient to offset the synthesis slowdown.
  4. A refined understanding of the bottleneck: The synthesis phase, not GPU contention, is the primary bottleneck. Any optimization that slows synthesis will hurt overall throughput regardless of GPU utilization improvements.
  5. Direction for future optimization: The results implicitly argue for approaches that don't reduce synthesis thread count — such as the Phase 7 per-partition dispatch architecture designed in this same segment, which pipelines synthesis and GPU work without reducing parallelism.

The Thinking Process Visible in the Reasoning

The target message itself is concise — it simply runs a command and reports results. But the thinking process is visible in the surrounding messages and the structure of the experiment itself.

In [msg 1965], the assistant explicitly reasoned through the tradeoffs:

"The key insight is that synthesis only needs to be faster than GPU time (~27s). So even if synthesis is 35s, as long as the second synthesis finishes before the first GPU proof completes, we win."

This reveals a mental model of the pipeline as a producer-consumer system: synthesis produces work units, GPU consumes them. The assistant was thinking in terms of throughput matching — if synthesis can stay ahead of GPU, the pipeline flows. The mistake was underestimating how much synthesis time would increase with fewer threads.

The operational debugging in messages [msg 1966]-[msg 1970] shows systematic troubleshooting: the assistant noticed the log file wasn't created, diagnosed it as a shell backgrounding issue, switched to nohup + disown, verified the daemon was running, waited for SRS preload, and confirmed readiness before running the benchmark. This methodical approach — identify failure, hypothesize cause, implement fix, verify — is characteristic of the assistant's debugging style.

The benchmark parameters themselves reflect thinking about experimental design: --count 5 provides enough samples to distinguish steady-state from cold-start behavior; --concurrency 2 tests the pipeline's overlap capability without overwhelming it. The assistant was designing an experiment to isolate the variable of interest (thread count) while controlling for confounding factors (concurrency level, sample size).

The Broader Significance

While this message appears to document a failed experiment — the hypothesis was not validated — it represents a crucial step in the optimization journey. The benchmark results forced a fundamental realization: synthesis is the primary bottleneck, and it greedily consumes all available CPU resources. This realization directly informed the Phase 7 design (documented in c2-optimization-proposal-7.md) which abandoned the thread isolation approach in favor of a more radical architectural change: per-partition dispatch with cross-sector pipelining.

The Phase 7 design, created in this same segment, treats each of the 10 PoRep C2 partitions as an independent work unit. Instead of batching all 10 partitions and submitting them to the GPU simultaneously (the "thundering herd" approach), Phase 7 dispatches each partition to the GPU as soon as its synthesis completes. This eliminates the GPU idle gap without reducing synthesis parallelism — each partition still uses all available rayon threads for its synthesis, but the GPU starts working immediately on finished partitions rather than waiting for all 10.

The benchmark in [msg 1971] thus served as a critical falsification experiment. It proved that thread pool isolation alone cannot solve the GPU idle problem, clearing the path for the more ambitious Phase 7 architecture. In scientific terms, this was a well-designed experiment that produced a clear negative result — and that result was as valuable as a positive one would have been.

Conclusion

Message [msg 1971] is a deceptively simple benchmark invocation that sits at the intersection of multiple threads of optimization work. It represents the culmination of a thread pool isolation implementation, the testing of a specific hypothesis about CPU-GPU contention, and the production of evidence that would redirect the entire optimization strategy. The benchmark results — showing 74-81s per proof with 47-48s synthesis times — confirmed that synthesis demands every available logical core and cannot be starved without penalty. This negative result was instrumental in motivating the Phase 7 per-partition dispatch architecture, which promises to eliminate GPU idle time without compromising synthesis parallelism. In the broader narrative of the cuzk proving engine optimization, this message is the moment when the team learned that the easy fix wouldn't work — and that the real solution would require rethinking the fundamental pipeline architecture.