config-optimizer

Identify optimal Sirius configurations for TPC-H workloads across scale factors.

Updated Mar 18, 2026

Search Tags:#configuration #benchmark #gpu #optimize #dataset #tpch #sirius

Ready to run

npx skills add https://github.com/kindofluke/albatross-data --skill config-optimizer-kindofluke

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: config-optimizer
Source: https://github.com/kindofluke/albatross-data/tree/main/.vibe/skills/config-optimizer
Command: npx skills add https://github.com/kindofluke/albatross-data --skill config-optimizer-kindofluke

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Sirius Config Optimizer helps teams identify the best configuration settings to maximize Sirius performance for TPC-H workloads across different scale factors.

Core Features & Use Cases

Parameterized tuning of key Sirius settings (e.g., threading, cache, and batch sizes) to explore performance across configurations.
Workflow-driven optimization: benchmark baseline, sweep configurations, and report results to guide decisions.
Use Case: When tuning a Sirius deployment for a 1TB scale factor dataset, quickly identify configurations that reduce query latency and improve GPU utilization.

Quick Start

Provide a baseline Sirius configuration and target dataset location, then run the optimization workflow to discover the optimal settings.

Frequently Asked Questions about config-optimizer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I find the best Sirius configuration for TPC-H workloads?▼

To find the best Sirius configuration for TPC-H workloads, provide a baseline configuration and target dataset location, then run the optimization workflow to sweep settings and discover optimal tuning parameters.

What Sirius settings can I tune to improve GPU utilization for TPC-H benchmarks?▼

You can tune key Sirius settings including threading, cache, and batch sizes to explore performance across configurations, which helps reduce query latency and improve GPU utilization for TPC-H benchmarks.

Can I optimize Sirius configurations across multiple TPC-H scale factors?▼

Yes, Sirius configuration optimization can be applied across multiple TPC-H scale factors, allowing you to benchmark baselines, sweep configurations, and report results across different datasets and hardware variations.

What's the best way to benchmark baseline Sirius performance before tuning configurations?▼

The best way to benchmark baseline Sirius performance is to apply the structured optimization workflow, which guides you through baseline benchmarking, configuration space exploration, and final reporting across dataset and hardware variations.

Do I need a specific baseline configuration to start optimizing Sirius for TPC-H?▼

You need to provide an existing baseline Sirius configuration and the target TPC-H dataset location to start the optimization workflow and discover the optimal settings for your specific scale factor.

How does the Sirius configuration optimization workflow handle reporting across different hardware variations?▼

The Sirius configuration optimization workflow handles reporting by documenting results across datasets and hardware variations, applying automated testing prompts to guide decisions during configuration space exploration.