CuZK PCE generation docs
In this sub-session, the assistant extended the Pre-Compiled Constraint Evaluator (PCE) extraction to support WinningPoSt, WindowPoSt, and SnapDeals proof types in the CuZK proving engine, and added a partitioned pipeline for SnapDeals to overlap synthesis and GPU proving. However, enabling PCE for WindowPoSt caused a crash due to a mismatch in input counts between the witness and the PCE. The assistant traced the root cause to the is_extensible() flag: RecordingCS returned false while WitnessCS returned true, causing different synthesis paths. The fix involved making RecordingCS fully extensible by implementing is_extensible() and extend() methods, and correcting its initialization to pre-allocate a ONE input, ensuring structural parity. The changes compiled cleanly and restored correct proving for WindowPoSt with PCE enabled.
The Complete Odyssey: Building, Debugging, and Automating a GPU Proving Infrastructure for Filecoin
Segments
- The assistant implemented PCE extraction for all proof types and resolved a WindowPoSt crash by aligning the extensibility behavior of RecordingCS with WitnessCS.Implement PCE extraction for all proof types, Add partitioned pipeline for SnapDeals, Debug WindowPoSt crash with PCE, Fix is_extensible() mismatch in constraint systems, Correct RecordingCS initialization, Update extract_precompiled_circuit function
- Fixed the WindowPoSt PCE crash by harmonizing constraint system types, deployed the fixes to a remote host confirming PoRep PCE extraction works, and isolated remaining random PoRep partition failures as a pre-existing GPU pipeline race condition.Fix PCE witness generation inconsistency by harmonizing CS types, Add protobuf-compiler to installation guides, Deploy PCE and synthesis fixes to remote host, Validate PoRep PCE extraction on remote host, Diagnose random PoRep partition invalidity as pre-existing GPU race condition
- Investigated and fixed PoRep partitioned proof failures on a multi-GPU remote host caused by a GPU race condition from incorrect CUDA_VISIBLE_DEVICES handling, implementing a shared mutex fix.diagnose PoRep partitioned proof failures on multi-GPU host, identify root cause of GPU race condition from CUDA_VISIBLE_DEVICES, implement shared mutex fix for single-circuit GPU work, edit engine.rs to use single mutex for num_circuits=1
- Implemented and deployed a proper multi-GPU fix for PoRep proofs by threading gpu_index through the call chain, verified load balancing on the remote host, and began preparing a Docker container for parameter fetching.Implement multi-GPU fix via gpu_index parameter threading across C++ and Rust layers, Deploy and verify multi-GPU fix on remote test host with load balancing, Begin Docker container packaging for Curio/CuZK/CUDA parameter fetching
- Constructed a Docker container for Curio/cuzk mainnet proving with runtime param fetch, and debugged multiple build blockers (jq, libcuda symlink, PEP 668, SPDK pip error).Write Dockerfile.cuzk multi-stage build, Write entrypoint.sh for param fetch, Fix missing jq dependency in build, Fix missing libcuda.so.1 symlink, Fix Python PEP 668 pip restriction, Debug pip uninstall error in SPDK setup
- Completed the Docker build and pushed to Docker Hub, resolved multiple build blockers (SPDK pip conflict, libcudart linker error, missing runtime libs), created benchmark/run scripts with portavailc tunnel support, fixed a spurious StorageMetaGC error, and designed a comprehensive vast.ai management system.Complete Docker build and push to Docker Hub, Fix SPDK pip upgrade conflict in Docker build, Fix libcudart_static.a linker error in Docker build, Install missing runtime libraries in Docker image, Create benchmark.sh and run.sh scripts, Add portavailc tunnel support to entrypoint, Fix StorageMetaGC error in curio, Design vast.ai management system in vast-cuzk-plan.md
- Deployed the vast-manager management service with a comprehensive web UI dashboard, fixed a routing bug, and investigated a missing VAST_CONTAINERLABEL environment variable in a new instance.deploy vast-manager service to controller host, fix DELETE /bad-host routing bug, implement web UI for vast-manager, add ring buffer log system, update entrypoint for log shipping, debug missing VAST_CONTAINERLABEL env var, manually register instance as workaround
- Resolved VAST_CONTAINERLABEL availability, fixed vast-manager monitor matching, hardened benchmark scripts against failures, redeployed on hosts 93197 and 88910 with new instances, and diagnosed OOM on low-memory instance, shifting focus to hardware-aware pipeline configuration.Resolve VAST_CONTAINERLABEL env var availability, Fix vast-manager monitor matching logic (label vs idMap), Harden benchmark.sh and entrypoint.sh against benchmark failures, Rebuild and push Docker image with updated entrypoint, Destroy old instances and clean stale DB entries, Create new instances with --onstart-cmd workaround, Diagnose OOM kill on low-memory instance and propose partition worker fix
- This sub-session resolved OOM failures in low-RAM instances by implementing dynamic hardware-aware configuration and a PCE-cache-dependent warmup strategy, then shifted to a data-driven experimental system for automatic hardware discovery after persistent performance issues.Fix OOM in benchmark warmup by detecting missing PCE cache and using reduced partition workers, Refactor entrypoint.sh for dynamic benchmark concurrency based on RAM and GPU count, Fix lifecycle bug in vast-manager handleBenchDone to destroy underperforming instances, Deploy hardened Docker image and new instances (Czechia, Belgium), Increase benchmark timeout from 20 to 45 minutes, Add post-restart warmup proof in benchmark.sh, Refine partition worker logic for ~256GB machines, Shift to data-driven experimental system for hardware discovery, Implement host_perf database table, Implement offer search API with GPU/RAM/price filters and known host performance overlay, Implement deploy endpoint, Implement foundational UI code for the new system
- Overhauled the vast-manager UI with a comprehensive Offers panel and deployment workflow, fixed a critical data integrity issue by switching bad_hosts/host_perf to use machine_id, and investigated a new benchmark failure on a deployed instance.Overhaul vast-manager UI with Offers panel and deployment controls, Fix data integrity by switching bad_hosts/host_perf to machine_id, Fix port 1234 tunnel forwarding in entrypoint for curio startup, Improve instance lifecycle persistence and metadata retention, Investigate benchmark failure on new RTX PRO 4000 instance
- This sub-session hardened the vast-manager platform with enhanced benchmark error reporting, UI bulk actions, and backend refinements, then pivoted to a deep investigation of a PoRep PSProve CuZK failure, identifying a JSON serialization round-trip issue and structural differences between code paths.harden vast-manager benchmark error reporting, enhance web UI with persistent deploy settings and bulk actions, refine backend to keep highest benchmark score and reject bad hosts, investigate PoRep PSProve CuZK failure mode, compare PSProve and normal CuZK code paths for structural differences, identify JSON serialization round-trip bug with custom marshalers, analyze Rust CuZK VanillaProof deserialization, identify SectorNum type mismatch in C1OutputWrapper
- The assistant continued the deep investigation of the PSProve PoRep CuZK failure by tracing RegisteredSealProof enum mappings across Go, C, and Rust, confirming structural parity, ruling out fr32 seed masking as the intermittent cause, and adding diagnostic logging and an extended roundtrip test to capture the exact byte-level discrepancy.Trace RegisteredSealProof enum mappings across Go, C, and Rust, Investigate and rule out fr32 seed masking as cause of intermittent failure, Extend 2KiB roundtrip test to cover CuZK wrapper and FFI C2 verification path, Add diagnostic logging to computePoRep in task_prove.go
- Deployed the critical self-check fix to production cuzk, proactively patched the same bug in two additional pipeline paths, and hot-swapped the daemon with a locally built binary to prevent intermittent invalid proofs from reaching the ProofShare protocol.Deploy self-check fix to production cuzk worker, Fix same bug in batched multi-sector pipeline path, Fix same bug in single-sector pipeline path, Build minimal cuzk binary with CUDA 13 devel environment, Upload binary and hot-swap production daemon, Ensure all pipeline modes enforce self-check
- Fixed two critical production bugs in the ProofShare system—a deadlock from HTTP 429 retries and a cuzk job ID collision causing partition proof mixing—then consolidated all fixes and pushed the final Docker image.fix TaskRequestProofs deadlock from HTTP 429 retries, fix cuzk job ID collision for concurrent proofshare challenges, add queue cleanup and dedup improvements, rebuild Curio binary in Docker and deploy to remote host, audit all cuzk RequestId callers for similar vulnerabilities, consolidate proofshare fixes into single commit, build and push final Docker image
- Designed a comprehensive memory management architecture for the cuzk GPU proving engine, replacing a fragile static concurrency limit with a robust memory-aware admission control system.Audit memory lifecycle for 32 GiB PoRep proofs, Identify dead working_memory_budget config, Design unified memory budget system, Specify LRU eviction for SRS/PCE caches, Design two-phase working memory release, Write cuzk-memory-manager.md specification
- Implemented the core of the new unified memory manager for cuzk, creating the memory.rs module, updating config with unified budget fields, making SrsManager budget-aware with eviction support, replacing static PCE caches with a PceCache struct, and partially modifying engine.rs to wire the budget into the pipeline.Create memory.rs module with MemoryBudget, MemoryReservation, detect_system_memory, and estimation constants, Update config.rs with unified budget fields and deprecation warnings for old fields, Rewrite SrsManager for budget-aware loading with last_used tracking and eviction, Replace static OnceLock PCE caches with PceCache struct in pipeline.rs, Update extract_and_cache_pce_from_* and synthesize_auto to use PceCache, Partially modify engine.rs to add reservation field and wire budget into SrsManager
- Completed the core engine integration of the unified memory manager, replacing static partition workers with budget-based admission control, two-phase memory release, and on-demand SRS/PCE loading.Complete engine.rs memory manager integration, Wire evictor callback and budget-based dispatch, Implement two-phase GPU memory release, Update cuzk.example.toml for new config, Update cuzk-bench for PceCache, Remove deprecated config fields and preload logic
- Finalized the budget-based memory manager implementation, deployed it to a remote machine, fixed a runtime panic in the evictor callback, and diagnosed concurrency bottlenecks and OOM issues requiring a properly sized safety margin.Fix compile errors and clean up imports, Update PceCache call site in bench, Validate memory manager with real-world benchmark, Assess remote host environment and config gaps, Deploy memory-manager binary to remote host, Fix evictor runtime panic (blocking_lock in async), Diagnose concurrency bottlenecks and OOM under budget
- Completed deployment and successful end-to-end testing of the unified budget-based memory manager, then designed and implemented a status tracking system with HTTP endpoint for monitoring pipeline progress.Deploy and test unified budget-based memory manager on remote machine, Diagnose and fix OOM by adjusting budget for co-resident processes, Complete end-to-end proof verification with memory manager, Design JSON status API schema for pipeline monitoring, Implement StatusTracker module with RwLock-backed snapshots, Wire status tracker into Engine lifecycle events, Add status_listen config option to DaemonConfig, Extend process_partition_result to accept status tracker
- Finalized the cuzk status API as a committed feature and integrated live monitoring into the vast-manager HTML UI with an SSH ControlMaster-based polling endpoint and a comprehensive visualization panel.Commit status API changes, Integrate live monitoring into vast-manager UI, Add cuzk-status API endpoint with SSH ControlMaster polling, Build live visualization panel for proof pipeline, Implement polling lifecycle with AbortController
- Deployed and refined the vast-manager cuzk status panel, fixed GPU worker idle display bug and job ID truncation, implemented ordered partition scheduling, and resolved overlay filesystem deployment issues.Deploy cuzk status panel in vast-manager, Fix GPU worker idle race condition, Fix job ID truncation in status, Change synth_max to budget-based, Implement ordered partition scheduling, Debug overlay filesystem deployment issue
- This sub-session investigated GPU utilization bottlenecks in the cuzk proving pipeline by adding precise timing instrumentation to the GPU worker loop and finalizer, and planned deployment of the instrumented binary for live workload analysis.Investigate GPU utilization idle gaps in cuzk pipeline, Add timing instrumentation to GPU worker loop, Add timing instrumentation to finalizer, Identify potential bottlenecks (tracker lock, malloc_trim, C++ mutex), Plan deployment of instrumented binary for log analysis
- Resolved GPU underutilization by identifying the H2D transfer bottleneck and implemented core components of a zero-copy pinned memory pool solution.Identify GPU underutilization root cause, Design zero-copy pinned memory pool, Implement PinnedPool struct, Modify bellperson for pinned backing, Validate compilation with cargo check
- Fully wired the zero-copy pinned memory pool (PinnedPool) into the cuzk engine and synthesis paths, integrating it with the memory budget system and creating a fallback path, then built a Docker image for deployment.wire PinnedPool into engine and synthesis paths, create synthesize_circuits_batch_with_prover_factory, implement fallback path for pool exhaustion, build Docker image for pinned pool binary, compile and verify clean build
- Deployed and debugged the pinned memory pool for GPU underutilization, fixing budget integration and dispatch burst issues to achieve near-zero H2D transfer times.deploy pinned memory pool fix, fix pinned pool budget integration, implement GPU queue depth throttle, diagnose dispatch burst problem, implement semaphore-based reactive dispatch, improve pinned buffer reuse ratio
- Iteratively refined GPU pipeline dispatch from a semaphore to a PI-controlled pacer with EMA feed-forward and a synthesis throughput cap to stabilize scheduling across varying workloads.Implement P-controller GPU dispatch, Implement PI-controlled dispatch pacer, Add synthesis throughput cap with anti-windup, Deploy and test pacer variants
- Completed PI pacer tuning with re-bootstrap logic and synthesis concurrency cap, then shifted to production deployment infrastructure.Tune PI controller parameters for dispatch pacer, Add re-bootstrap detection and slow bootstrap to dispatch pacer, Add max_parallel_synthesis configuration field, Build production Docker image for cuzk, Configure default memory budget for vast.ai environments
- Finalized production deployment by updating default memory safety margin to 10GiB, rewriting Docker scripts for memory-budget-driven configuration, building and pushing the Docker image, and addressing benchmark configuration issues including synthesis concurrency, benchmark client concurrency, status_listen endpoint, and ANSI escape code stripping.Update default safety margin to 10GiB, Rewrite Docker scripts for memory-budget config, Build and push Docker image, Fix benchmark and run script configuration, Plan ANSI escape code stripping for UI
- Fixed deployment configuration issues, improved benchmark reliability, resolved SSH connectivity problems, and implemented a comprehensive memcheck system for OOM prevention.Fix synthesis_concurrency and benchmark concurrency defaults, Add status_listen to benchmark config and strip ANSI codes from UI, Restructure benchmark into three-phase warmup/timed/cooldown model, Diagnose and fix SSH connectivity issues and improve error handling, Design and build memcheck.sh utility for cgroup-aware memory detection, Integrate memcheck into vast-manager API, UI, and entrypoint.sh, Add auto-restart logic for cuzk/curio and set CURIO_NODE_NAME, Rebuild Docker image and deploy updated vast-manager
- Finalized cgroup-aware memory detection for cuzk, fixed memcheck bugs, deployed to vast.ai instances, then added a memprobe utility and OOM recovery loop to handle memory-constrained nodes.Implement cgroup-aware memory detection in detect_system_memory(), Fix memcheck.sh GPU JSON parsing and pinning detection bugs, Develop memprobe utility for empirical safety margin measurement, Add OOM recovery loop with budget reduction to benchmark.sh, Deploy and verify cgroup-aware memory budgeting on real vast.ai instances, Investigate OOM crash root cause (PinnedPool accounting, kernel overhead)
- Diagnosed and fixed a bash script bug in benchmark.sh that masked OOM crashes, then designed a proper budget-aware pinned pool integration after rejecting an ad-hoc capacity cap.Fix benchmark.sh OOM recovery exit code capture, Analyze memory budget accounting for pinned pool, Design budget-aware pinned pool integration, Reject ad-hoc capacity cap in favor of principled solution
- Implemented unit tests, UI enhancements, and deployed the budget-integrated pinned memory pool to the RTX 5090 test machine, validating its design in production with successful SnapDeals proof completion.Refactor pinned_pool.rs for testability with mock CUDA allocator, Add unit and integration tests for budget-integrated pinned pool, Enhance vast-manager UI with pinned pool and budget breakdown, Build and push Docker image for budget-integrated pool, Deploy cuzk binary to RTX 5090 test machine, Deploy vast-manager binary to management host, Validate budget-integrated pinned pool in production with SnapDeals proofs
- This sub-session pivoted from deploying the budget-integrated pinned pool and fixing a critical production crash to designing, building, and iteratively hardening a fully autonomous LLM-driven fleet management agent for cuzk proving infrastructure, resolving major failures in demand sensing, context management, and operational stability.Fix cuzk daemon supervisor crash bug, Deploy budget-integrated pinned pool to constrained machines, Build autonomous LLM fleet management agent, Fix agent scaling and demand sensing logic, Expand vast-manager UI with agent panels, Build diagnostic grounding sub-agent system, Implement context management and verdict system, Fix context overflow and session reset bugs, Harden agent loop with debounce and locks, Implement event-driven agent triggering