performance: more aggressive time scaling in sample_qc
#297
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This commit addresses the need for increased resource allocation, particularly wall-time, for the concordance rules when processing large samples. - Scaling Time Allocation: We've implemented a more aggressive scaling mechanism for the time allocation in the BIG_TIME dictionary, which gets applied to the resource section of concordance rules. This ensures sufficient resources for processing large samples (e.g., exceeding 90K). - Consistent application: We've also applied this updated scaling to the sample_concordance_king rule to ensure consistent resource allocation across all concordance rules. In particular, we added the more aggressive memory and time allocation to this rule.
Updates `mem_mb` logic to allocate memory based on input file size (`input.size_mb`) for more efficient resource utilization. This data-driven approach avoids over-allocation compared to the previously used dictionary with fixed, potentially excessive values. By dynamically adjusting memory based on input size, we ensure sufficient resources for processing while preventing unnecessary memory usage when wall-time is typically the bottleneck for these specific rules.
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sample_qc subworkflow
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sample_qc subworkflowsample_qc
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We implement two key improvements for resource allocation on rules for sample_qc sub_workflow.
mem_mblogic to scale memory allocation based on the input file size (input.size_mb).Fixes #282