The Push That Made It Real: Shipping a CUDA Proving Stack to Docker Hub

[assistant] [bash] docker tag curio-cuzk:latest theuser/curio-cuzk:latest && docker push theuser/curio-cuzk:latest
The push refers to repository [docker.io/theuser/curio-cuzk]
f8eb87492d82: Preparing
5f70bf18a086: Preparing
b10cd5d44fc0: Preparing
661891e5dc85: Preparing
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431eddc1f16f: Preparing
65249b72f876: Preparing
8e97afa52d2e: Preparing
9bc297f16020: Preparing
48371d64208f: Preparing
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22df1df9d581: Preparing
b7ec8fd7c485: Preparing
dab2da33fe40: Preparing
b5c4de646bba: Preparing
1824133...

At first glance, message 708 of this opencode session looks mundane — a Docker tag and push command, followed by a list of layer hashes being prepared for upload. But this message is anything but ordinary. It is the culmination of a grueling multi-hour debugging and build cycle, the moment when a complex CUDA-accelerated Filecoin proving stack finally crossed the threshold from a local development artifact into a deployable, publicly available container image. This message represents the transition from building to shipping.

The Long Road to a Green Build

To understand why this push matters, one must appreciate the journey that preceded it. The Docker image being pushed — theuser/curio-cuzk:latest — contains the full CuZK proving stack: the curio daemon, sptool, cuzk-daemon, and cuzk-bench binaries, all linked against CUDA 13 supraseal support. Building this image was not straightforward.

The session's earlier messages document a cascade of build blockers, each requiring diagnosis and surgical fixes. The Debian-managed python3-pip package conflicted with the SPDK pip upgrade, requiring its removal. The libcudart_static.a linker error demanded adding /usr/local/cuda/lib64 to LIBRARY_PATH. Missing runtime libraries — libconfig++, libaio, libfuse3, libarchive — had to be explicitly installed. Each of these was a separate iteration of edit-build-fail-fix, visible in the conversation as the assistant and user worked through the Dockerfile together.

Beyond the build itself, the assistant had been simultaneously developing the runtime scripts that would live inside the container. The benchmark.sh script had undergone multiple revisions: fixing argument names (-n to --count, -j to --concurrency), adding a wait loop for curio fetch-params to handle vast.ai's background on-start execution, auto-detecting the parameter cache directory, and generating a minimal TOML config so the daemon would look in the right place for SRS parameters instead of its hardcoded /data/zk/params default. The run.sh script was created from scratch to start the cuzk daemon in the foreground with proper signal handling.

The immediate trigger for message 708 was the user's request in message 706: "build/push". But between that request and the push lay an important intermediate step. In messages 701–702, the user had specified a default configuration:

[daemon]
listen = "0.0.0.0:9820"
[srs]
param_cache = "/data/zk/params"
preload = ["porep-32g"]
[synthesis]
partition_workers = 16
[gpus]
gpu_workers_per_device = 2
gpu_threads = 32

The assistant integrated this configuration into both run.sh and benchmark.sh (messages 703–704), then performed a fresh build (message 707). That build succeeded, producing image sha256:2193d91215a6eb904f462dd1a68869881d1d6272fe54052639ff4c8894e689af. Message 708 is the immediate next step: pushing that successfully built image to Docker Hub.

What the Push Actually Accomplishes

The command in message 708 does two things in sequence. First, docker tag curio-cuzk:latest theuser/curio-cuzk:latest creates an additional tag for the locally built image, associating it with the Docker Hub repository theuser/curio-cuzk. This is a critical step because the local tag curio-cuzk:latest exists only on the build machine; without the theuser/ prefix, Docker would not know where to push it. The tag effectively says "this image belongs to the theuser/curio-cuzk repository on Docker Hub."

Second, docker push theuser/curio-cuzk:latest uploads the image layers to Docker Hub. The output shows 19 layers being prepared — each corresponding to a step in the multi-stage Dockerfile. The "Preparing" status means Docker is calculating checksums and determining which layers already exist on the registry (for incremental pushes, only new or changed layers are uploaded). The truncated output shows the first 19 layers; the full push would continue with the remaining layers until completion.

The image itself is substantial — approximately 3GB compressed, containing CUDA runtime libraries, the Filecoin proof parameters directory structure, and multiple compiled binaries. The push to a public registry makes this image available to any vast.ai instance or other Docker-compatible host without requiring the build toolchain or source code.

Assumptions and Decisions Embedded in This Moment

Several assumptions are baked into this push. The most significant is the assumption that the build is correct — that the image compiles cleanly, that the runtime scripts work, that the daemon can find its parameters, and that the CUDA libraries are properly linked. The assistant and user had already validated some of these through earlier test runs (the benchmark had been executed on a remote host, revealing the param cache mismatch and the -n argument error), but each fix iteration introduced new potential for breakage. The push represents a bet that the current state is good enough for deployment.

Another assumption concerns the target environment. The image is designed for vast.ai instances running NVIDIA GPUs with CUDA support. The configuration defaults — 16 partition workers, 2 GPU workers per device, 32 GPU threads — are tuned for high-end instances with substantial RAM and multiple GPUs. The assistant had earlier included logic to auto-detect RAM and adjust worker counts accordingly, but the hardcoded defaults in the config file assume a powerful machine.

The choice of theuser/curio-cuzk:latest as the tag is also a decision worth noting. Using :latest means any consumer who pulls theuser/curio-cuzk without specifying a tag will get this image. This is convenient for iteration but risky — it means there is no versioning discipline, no canary deployment, no staged rollout. Every push overwrites latest, and if a subsequent build is broken, consumers pulling latest will get the broken version. The session does not show any use of versioned tags like :v1.0.0 or :build-20260310.

The Thinking Process Visible in the Session

While message 708 itself contains no explicit reasoning — it is a straightforward bash command — the thinking process is visible in the surrounding context. The assistant's decisions follow a clear pattern: diagnose the failure, identify the root cause, implement the fix, rebuild, and push. When the benchmark failed with "C1 parse failed: SRS param file not found," the assistant traced the issue to the daemon's hardcoded config default overriding the FIL_PROOFS_PARAMETER_CACHE environment variable. The fix — generating a minimal TOML config at runtime — shows an understanding of the daemon's configuration precedence rules.

Similarly, when the user reported the -n argument error, the assistant recognized it as a mismatch between the benchmark script's argument names and cuzk-bench batch's actual CLI. The assistant searched the codebase for the correct argument names (--count, --concurrency) and applied the fix. This pattern of reading source code to understand tool behavior, rather than guessing, is a hallmark of the assistant's approach.

The push in message 708 is also notable for what it does not contain: there is no smoke test, no verification that the pushed image actually works on a fresh host, no integration test. The assistant's follow-up message (709) simply states "Done. theuser/curio-cuzk:latest pushed." The validation would come later, when the user runs benchmark.sh on a vast.ai instance (message 710) and encounters a new issue: the daemon starts but takes too long to respond because it's loading a 25.7 GiB PCE file.

Input Knowledge and Output Knowledge

To understand message 708, one needs to know: what Docker tagging and pushing means; that theuser is a Docker Hub username; that the image contains a CUDA-accelerated Filecoin proving stack; that the build had been iterated multiple times to resolve linker errors, missing dependencies, and configuration mismatches; and that the user and assistant are working toward deploying this stack on vast.ai GPU instances.

The message creates new knowledge in the form of a publicly available Docker image. Anyone with Docker and a GPU can now run docker pull theuser/curio-cuzk:latest and obtain the complete proving environment. This is a significant milestone: the project has moved from a source-code artifact (a Git repository with a Dockerfile) to a deployable container image. The push also establishes a baseline for future iterations — subsequent pushes will only need to upload changed layers, making the cycle faster.

Conclusion

Message 708 is the quiet climax of a long debugging and build session. It is the moment when all the individual fixes — the linker flags, the pip workarounds, the config generation, the argument name corrections — coalesce into a single deployable artifact. The push command itself is unremarkable, a standard Docker workflow. But the context transforms it into something more: a declaration that the software is ready for the real world. The layers being prepared are not just filesystem snapshots; they are the accumulated solutions to every problem encountered along the way. And the registry that receives them is not just storage — it is the distribution channel that will carry this proving stack to GPU instances across the globe, where it will generate Filecoin proofs for the storage network.