Preprocessing effects on cloud VLM VQA vary strongly by model, API paradigm, and provider token accounting, so no single preprocessing strategy is universally best.
Overhead Measurement Noise in Different Runtime Environments
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abstract
In order to detect performance changes, measurements are performed with the same execution environment. In cloud environments, the noise from different processes running on the same cluster nodes might change measurement results and thereby make performance changes hard to measure. The benchmark MooBench determines the overhead of different observability tools and is executed continuously. In this study, we compare the suitability of different execution environments to benchmark the observability overhead using MooBench. To do so, we compare the execution times and standard deviation of MooBench in a cloud execution environment to three bare-metal execution environments. We find that bare metal servers have lower runtime and standard deviation for multi-threaded MooBench execution. Nevertheless, we see that performance changes up to 4.41% are detectable by GitHub actions, as long as only sequential workloads are examined.
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How Much Does It Cost to Answer My Question? Benchmarking Cloud VLM-based VQA Systems
Preprocessing effects on cloud VLM VQA vary strongly by model, API paradigm, and provider token accounting, so no single preprocessing strategy is universally best.