/aris-dse-loop

name: aris-dse-loop
description: "Autonomous design space exploration loop for computer architecture and EDA. Runs a program, analyzes results, tunes parameters, and iterates until objective is met or timeout. Use when user says \"DSE\", \"design space exploration\", \"sweep parameters\", \"optimize\", \"find best config\", or wants iterative parameter tuning."
argument-hint: "[task-description — include program, parameters, objective, and timeout]"
allowed-tools: Bash(*), Read, Grep, Glob, Write, Edit, Agent
license: MIT
metadata:
  author: wanshuiyin/ARIS
  version: "1.0.0"

DSE Loop: Autonomous Design Space Exploration

Autonomously explore a design space: run → analyze → pick next parameters → repeat, until the objective is met or timeout is reached. Designed for computer architecture and EDA problems.

Context: $ARGUMENTS

Safety Rules — READ FIRST

**NEVER do any of the following:**

• `sudo` anything
• `rm -rf`, `rm -r`, or any recursive deletion
• `rm` any file you did not create in this session
• Overwrite existing source files without reading them first
• `git push`, `git reset --hard`, or any destructive git operation
• Kill processes you did not start

**If a step requires any of the above, STOP and report to the user.**

Constants (override via $ARGUMENTS)

| Constant | Default | Description | |----------|---------|-------------| | `TIMEOUT` | 2h | Total wall-clock budget. Stop exploring after this. | | `MAX_ITERATIONS` | 50 | Hard cap on number of design points evaluated. | | `PATIENCE` | 10 | Stop early if no improvement for this many consecutive iterations. | | `OBJECTIVE` | minimize | `minimize` or `maximize` the target metric. |

Override inline: `/aris-dse-loop "task desc — timeout: 4h, max_iterations: 100, patience: 15"`

Typical Use Cases

| Problem | Program | Parameters | Objective | |---------|---------|-----------|-----------| | Microarch DSE | gem5 simulation | cache size, assoc, pipeline width, ROB size, branch predictor | maximize IPC or minimize area×delay | | Synthesis tuning | yosys/DC script | optimization passes, target freq, effort level | minimize area at timing closure | | RTL parameterization | verilator sim | data width, FIFO depth, pipeline stages, buffer sizes | meet throughput target at min area | | Compiler flags | gcc/llvm build + benchmark | -O levels, unroll factor, vectorization, scheduling | minimize runtime or code size | | Placement/routing | openroad/innovus | utilization, aspect ratio, layer config | minimize wirelength / timing | | Formal verification | abc/sby | bound depth, engine, timeout per property | maximize coverage in time budget | | Memory subsystem | cacti / ramulator | bank count, row buffer policy, scheduling | optimize bandwidth/energy |

Workflow

Phase 0: Parse Task & Setup

1. **Parse $ARGUMENTS** to extract:

• **Program**: what to run (command, script, or Makefile target)
• **Parameter space**: which knobs to tune and their ranges/options (may be incomplete — see step 2)
• **Objective metric**: what to optimize (and how to extract it from output)
• **Constraints**: hard limits that must not be violated (e.g., timing must close)
• **Timeout**: wall-clock budget
• **Success criteria**: when is the result "good enough" to stop early?

2. **Infer missing parameter ranges** — If the user provides parameter names but NOT ranges/options, you MUST infer them before exploring:

a. **Read the source code** — search for the parameter names in the codebase:

• Look for argparse/click definitions, config files, Makefile variables, module parameters, `#define`, `parameter` (SystemVerilog), `localparam`, etc.
• Extract defaults, types, and any comments hinting at valid values

b. **Apply domain knowledge** to set reasonable ranges: | Parameter type | Inference strategy | |---------------|-------------------| | Cache/memory sizes | Powers of 2, typically 1KB–16MB | | Associativity | Powers of 2: 1, 2, 4, 8, 16 | | Pipeline width / issue width | Small integers: 1, 2, 4, 8 | | Buffer/queue/FIFO depth | Powers of 2: 4, 8, 16, 32, 64 | | Clock period / frequency | Based on technology node; try ±50% from default | | Bound depth (BMC/formal) | Geometric: 5, 10, 20, 50, 100 | | Timeout values | Geometric: 10s, 30s, 60s, 120s, 300s | | Boolean/enum flags | Enumerate all options found in source | | Continuous (learning rate, threshold) | Log-scale sweep: 5 points spanning 2 orders of magnitude around default | | Integer counts (threads, cores) | Linear: from 1 to hardware max |

c. **Start conservative** — begin with 3-5 values per parameter. Expand range later if the best result is at a boundary.

d. **Log inferred ranges** — write the inferred parameter space to `dse_results/inferred_params.md` so the user can review:

      # Inferred Parameter Space

      | Parameter | Source | Default | Inferred Range | Reasoning |
      |-----------|--------|---------|---------------|-----------|
      | CACHE_SIZE | config.py:42 | 32768 | [8192, 16384, 32768, 65536, 131072] | powers of 2, ±2x from default |
      | ASSOC | config.py:43 | 4 | [1, 2, 4, 8] | standard associativities |
      | BMC_DEPTH | run_bmc.py:15 | 10 | [5, 10, 20, 50] | geometric, common BMC depths |

e. **Boundary expansion** — during the search, if the best result is at the min or max of a range, automatically extend that range by one step in that direction (but log the extension).

3. **Read the project** to understand:

• How to run the program
• Where results are produced (stdout, log files, reports)
• How to parse the objective metric from output
• Current/baseline configuration (if any)

4. **Create working directory**: `dse_results/` in project root

• `dse_results/dse_log.csv` — one row per design point
• `dse_results/DSE_REPORT.md` — final report
• `dse_results/DSE_STATE.json` — state