The Final Touch: Routing GPU Proving to the Correct Device

In a single-line message that belies its architectural significance, the assistant reports:

Now update the select_gpu(tid) call to use gpu_base: [edit] /tmp/czk/extern/supraseal-c2/cuda/groth16_cuda.cu Edit applied successfully.

This is message [msg 461] in a conversation spanning a multi-GPU debugging saga. On its surface, it is a trivial edit — renaming a variable in a select_gpu() call. But this line represents the culmination of a fundamental architectural correction that threads through five layers of code, from C++ CUDA kernels up through Rust FFI bindings, bellperson prover functions, pipeline orchestration, and finally the engine's GPU worker logic. Understanding why this single rename matters requires tracing the chain of reasoning that led to it.

The Problem: A Lazy Hack Exposed

The story begins with a SnapDeals workload of 16 identical partitions running on a dual-GPU RTX 4000 Ada host with 20 GB of VRAM. The system kept crashing with out-of-memory (OOM) errors. The initial diagnosis (see [msg 442]) revealed that two Rust workers were entering the C++ GPU proving code simultaneously, both routing to GPU 0, causing VRAM exhaustion. The C++ code at line 483 of groth16_cuda.cu contained the root cause:

size_t n_gpus = std::min(ngpus(), num_circuits);

For partitioned proofs, num_circuits is always 1, so n_gpus is always 1, and the loop at line 883 spawns a single thread with tid=0, which calls select_gpu(0). Every worker — regardless of which GPU the Rust engine assigned it to — would prove on GPU 0. The second GPU sat idle while GPU 0 was overloaded.

The initial "fix" was a shared mutex ([msg 443]) that serialized all partition proofs onto GPU 0, preventing the OOM but wasting the second GPU entirely. The user immediately called this out in [msg 444]: "Isn't the shared lock just a lazy hack?" — and it was. The CuZK proving engine was designed for sophisticated multi-GPU interlocking, with data transfer and compute phases meant to overlap across devices. The shared mutex reduced it to single-GPU operation.

The Proper Fix: Threading a GPU Index

The assistant's response in [msg 445] acknowledged the criticism and pivoted to the real solution: thread a gpu_index parameter through the entire call chain so the C++ code uses the GPU assigned by the Rust engine. The plan was outlined in [msg 452] with a todo list spanning five layers:

  1. C++ groth16_cuda.cu: Add int gpu_index parameter; when >= 0, force n_gpus = 1 and use select_gpu(gpu_index) instead of select_gpu(0).
  2. Rust FFI supraseal-c2/src/lib.rs: Pass the new parameter through extern "C" declarations.
  3. Bellperson prover functions: Thread the parameter through prove_start and prove_from_assignments.
  4. Pipeline layer: Thread through gpu_prove and gpu_prove_start.
  5. Engine engine.rs: Revert the shared mutex hack and pass the assigned GPU ordinal. The assistant adopted a disciplined bottom-up approach, starting with the C++ layer and working upward. Messages [msg 457] through [msg 460] applied the C++ changes: adding the parameter to function signatures, updating the forward declaration and sync wrapper, modifying the implementation of generate_groth16_proofs_start_c, and replacing the n_gpus = min(ngpus(), num_circuits) logic with conditional branching based on gpu_index.

Message 461: The Critical Variable Rename

Message [msg 461] is the final C++ edit. It replaces select_gpu(tid) with select_gpu(gpu_base). The variable gpu_base was introduced in the preceding edit ([msg 460]) and is defined as:

The Thinking Process

The assistant's reasoning, visible across the preceding messages, reveals careful consideration of several factors:

Why bottom-up? The assistant explains in [msg 457]: "I'll work bottom-up: C++ first, then supraseal-c2 Rust, then bellperson, then pipeline, then engine." This is a classic systems-engineering approach — start with the lowest layer that actually executes the work, ensure the interface is correct, then propagate the change upward through each abstraction layer. Any mistake in the C++ signature would cascade through all the Rust layers, so getting it right first minimizes rework.

Why -1 for auto mode? The assistant chose -1 as the sentinel value meaning "use default GPU selection" ([msg 455]). This is a natural choice in CUDA programming where GPU indices are zero-based non-negative integers. It allows callers that don't care about GPU assignment (e.g., non-engine paths like standalone tests) to pass -1 and get the legacy behavior.

What about the d_a_cache? The assistant identified a secondary concern in [msg 456]: the global d_a_cache singleton would thrash between GPUs if two workers on different devices both tried to use it concurrently. The cache already had a gpu_id field and could reallocate on a different GPU, but concurrent access from different devices would cause repeated frees and reallocations. The assistant noted this as a concern but deferred it — the immediate priority was correct GPU routing. (In the subsequent chunk, the assistant would address this by making d_a_cache a per-GPU array.)

Assumptions and Knowledge

This message makes several implicit assumptions. First, that the select_gpu() function correctly sets the CUDA device context for all subsequent operations — if select_gpu() has side effects beyond device selection, the rename could introduce subtle bugs. Second, that the gpu_base variable is correctly initialized in all branches of the preceding logic — the assistant trusts its own edit in [msg 460] without re-verifying. Third, that the per-GPU mutex mechanism (restored from the shared-mutex hack) will correctly serialize access to each GPU independently, preventing the original OOM while allowing true multi-GPU parallelism.

The input knowledge required to understand this message is substantial. One must understand the CUDA programming model (device selection, stream contexts, memory allocation per device), the Groth16 proving pipeline (MSM, NTT, multi-exponentiation), the Rust FFI boundary (extern "C" declarations, pointer passing, error handling via RustError), and the partitioned proof architecture where a single circuit's proof is split across multiple workers.

Output Knowledge Created

This message creates a corrected GPU routing path. Before it, the C++ code was structurally incapable of using multiple GPUs for partitioned proofs — the min(ngpus(), num_circuits) logic ensured that single-circuit proofs always landed on GPU 0. After it, the code respects the GPU assignment passed from the Rust engine, enabling true load balancing. The 16 SnapDeals partitions can now distribute across both GPUs, each proving on its assigned device without OOM or wasted capacity.

The message also establishes a pattern for the subsequent layers. The gpu_index parameter now exists in the C++ function signature; the Rust FFI, bellperson, pipeline, and engine edits (which follow in messages [msg 462] onward) are mechanical propagation of this parameter through each layer. The hardest architectural decision — how to route single-circuit proofs to the correct GPU — has been solved at the bottom of the stack.

Significance

What makes this message noteworthy is not the complexity of the edit itself — renaming a variable is trivial — but the chain of reasoning that led to it. The assistant had to recognize that the shared mutex was a hack, trace the root cause to a single line of C++ (n_gpus = min(ngpus(), num_circuits)), design a parameter-threading strategy across five layers, and execute it bottom-up. The rename from tid to gpu_base is the moment where the entire multi-GPU fix becomes operational. It transforms the CuZK proving engine from a de facto single-GPU system into one that can actually leverage multiple devices, honoring the sophisticated interlocking design that the engine was meant to support.