Test: Use zstd:chunked base images to measure GHA build speedup

[jiridanek]

Description

This test branch uses the zstd:chunked compressed base images built in PR #2868 to measure whether GHA builds are faster with the new compression format.

Base Images Updated

All 19 .conf files in build-args/ directories updated to use digest-pinned zstd:chunked images:

Image Type	Digest
CPU C9S	sha256:2580cb333113ae2e04a813dbea318ddc9c8e3f68e724f42c0d3d4f83ac35abd0
CUDA C9S (13.0)	sha256:2a4cb3a49e11bc58548a55720060de0cc72387c88adc9b3354785fc1522bca44
CUDA UBI9 (12.8)	sha256:7032289e42fd53b65b0a71008cc4ad21f9db8f00dcb421128904a939da5bb16e
ROCm C9S (6.4)	sha256:f76c06cbc7ed4e653d2f925e4a906b60bab34c4b8d55874bc91bb3f7074d0cd8
ROCm UBI9 (6.4)	sha256:13f2bc5bde88770ff8ad446114274e97668575bf41095915529fe9958f97c0bb

Expected Improvements

Based on benchmark results:

Metric	Improvement
CUDA image pulls	~53% faster
CUDA builds	~64% faster
CPU image pulls	~18% faster

Test Plan

• Compare GHA workflow run times against a baseline run with gzip base images
• Monitor build times for jupyter-minimal, jupyter-datascience, runtimes

Related

• Parent PR: Feat/base image zstd compression #2868 (zstd:chunked compression for base images)
• Benchmark report: docs/benchmark-zstd-chunked-results.md

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✨ Finishing touches

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