dse-loop

Automate design space exploration by running programs and tuning parameters.

14.4k|1.3k|Updated Mar 10, 2026

Search Tags:#optimization #eda #parameter tuning #dse #design space exploration #computer architecture

Ready to run

npx skills add https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep --skill dse-loop

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: dse-loop
Source: https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/tree/main/skills/dse-loop
Command: npx skills add https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep --skill dse-loop

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the iterative process of exploring design spaces for complex systems, such as computer architecture or EDA, by running programs, analyzing results, and tuning parameters until an objective is met or a timeout occurs.

Core Features & Use Cases

Autonomous Exploration: Runs a program, analyzes its output, and intelligently selects the next set of parameters to test.
Parameter Tuning: Optimizes system configurations based on defined objectives (e.g., maximize performance, minimize area).
Use Case: Automatically tune the cache size, associativity, and pipeline width of a CPU design to maximize Instructions Per Cycle (IPC) within a given time budget.

Quick Start

Use the dse-loop skill to run gem5 simulations and tune L1D_SIZE, L2_SIZE, and ROB_ENTRIES to maximize IPC with a 3-hour timeout.

Frequently Asked Questions about dse-loop

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

FAQPage Schema

How do I automate design space exploration for computer architecture parameters?▼

Automate design space exploration by using a skill that executes programs, parses performance metrics, and iteratively tunes parameters until an objective is met or a timeout occurs. It supports objective-driven optimization and adaptive search strategies for computer architecture configurations.

What is the best way to tune EDA parameters automatically within a time budget?▼

Tune EDA parameters automatically by running iterative program executions with adaptive search strategies and constraint checking. The process intelligently selects the next parameters to test until the defined optimization objective is met or the specified time budget expires.

How does parameter tuning extract objective metrics from program outputs?▼

Parameter tuning extracts objective metrics through programmatic parsing of program outputs. The skill analyzes these extracted performance metrics, logs the results, and uses them for convergence analysis to guide the next iterative parameter selections.

Can I optimize CPU cache size and pipeline width to maximize IPC automatically?▼

Yes, you can optimize CPU cache size, associativity, and pipeline width to maximize IPC. The skill runs simulations, checks constraints, and intelligently selects new parameters to test, driving objective-driven optimization for complex computer architecture designs.

Do I need to parse program outputs manually for design space exploration?▼

No, but the skill requires programmatic parsing of program outputs to extract objective metrics. You must define how the program outputs are parsed so the skill can log results for convergence analysis and intelligently select the next parameters to test.