メニュー
Manage large-scale OrcaFlex batch processing with parallel execution, adaptive worker scaling, memory optimization, and progress tracking for efficient simulation campaigns.
デフォルトでは、最初にソースを確認する Prompt が選択されています。直接コマンドに切り替えるか、ローカルコピーをダウンロードすることもできます。
インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
直接コマンドでは確認用 Prompt が省略されます。実行前にソースを確認してください。
npx skills add https://github.com/vamseeachanta/workspace-hub --skill orcaflex-batch-managerコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
ローカルで確認しますか？SkillsMP が現在取得できるファイルをダウンロードできます。
Write outbound email and external messages in Vamsee Achanta's voice — a subtle offer to help, never bold or rash claims. Load before drafting ANY email, LinkedIn/Collide reply, proposal note, or outreach sent under his name.
Save/publish analysis or computation results from ANY ecosystem repo to Hugging Face as a queryable, viewer-renderable dataset. Use when the user wants to "save results to hugging face", "publish dataset to HF", "hugging face data saving", "save analysis results", "hf dataset", "make results queryable", or "render via datasets-server API". Reshapes nested results into flat parquet tables, writes a dataset card with a viewer `configs:` block and provenance, applies license/public-vs-private routing, enforces a domain data-quality gate (faithful-to-source != correct), publishes to `aceengineer/<repo>-<projection>`, and verifies via the datasets-server API.
Clone, create, fork, configure, and manage GitHub repositories. Manage remotes, secrets, releases, and workflows. Works with gh CLI or falls back to git + GitHub REST API via curl.
SKILL.md を表示中
SOC 職業分類に基づく
| name | orcaflex-batch-manager |
| description | Manage large-scale OrcaFlex batch processing with parallel execution, adaptive worker scaling, memory optimization, and progress tracking for efficient simulation campaigns. |
| type | reference |
| version | 1.0.0 |
| updated | "2026-01-17T00:00:00.000Z" |
| category | engineering |
| triggers | ["batch processing","parallel simulations","batch manager","run multiple models","simulation campaign","large batch","parallel OrcaFlex","job queue"] |
| capabilities | [] |
| requires |
| [] |
| tags | ["marine","offshore","orcaflex","batch-processing","parallel","simulation"] |
| related_skills | ["orcaflex-modeling","orcaflex-post-processing","orcaflex-operability","orcaflex-results-comparison"] |
| scripts_exempt | true |
Before starting a batch simulation campaign, query the wiki for relevant domain knowledge:
bash scripts/knowledge/wiki-query-context.sh "OrcaFlex batch simulation" --domains engineering,marine-engineering
Check results for: solver settings, convergence guidance, known pitfalls, and related standards. Log consulted wiki pages in your output per the retrieval contract (#2208).
from digitalmodel.orcaflex.universal.batch_processor import BatchProcessor
from pathlib import Path
def run_batch(input_dir: str, output_dir: str, max_workers: int = 20):
"""
Run batch processing on OrcaFlex models.
Args:
input_dir: Directory containing model files
*See sub-skills for full details.*
### Adaptive Parallel Processing
```python
from digitalmodel.orcaflex.universal.batch_processor import BatchProcessor
from pathlib import Path
import psutil
class AdaptiveBatchProcessor(BatchProcessor):
"""Batch processor with adaptive resource management."""
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
*See sub-skills for full details.*
### Chunk-Based Processing
```python
from digitalmodel.orcaflex.universal.batch_processor import BatchProcessor
from pathlib import Path
import time
def process_in_chunks(
input_dir: str,
output_dir: str,
chunk_size: int = 50,
pause_seconds: int = 5
*See sub-skills for full details.*
### Progress Tracking and Checkpoints
```python
from digitalmodel.orcaflex.universal.batch_processor import BatchProcessor
from pathlib import Path
import json
import time
class CheckpointBatchProcessor(BatchProcessor):
"""Batch processor with checkpoint save/restore."""
def __init__(self, checkpoint_file: str = "batch_checkpoint.json", **kwargs):
*See sub-skills for full details.*
### File Size Optimization
```python
from pathlib import Path
import os
def sort_by_file_size(files: list, reverse: bool = True) -> list:
"""
Sort files by size for optimal processing order.
Processing large files first with fewer workers,
then small files with more workers.
*See sub-skills for full details.*
### Performance Metrics
```python
from dataclasses import dataclass, field
from typing import Dict, List
import time
import json
@dataclass
class BatchMetrics:
"""Track batch processing performance metrics."""
*See sub-skills for full details.*
## Related Skills
- [orcaflex-modeling](../orcaflex-modeling/SKILL.md) - Run OrcaFlex simulations
- [orcaflex-operability](../orcaflex-operability/SKILL.md) - Multi-sea-state campaigns
- [orcaflex-post-processing](../orcaflex-post-processing/SKILL.md) - Extract results
- [orcaflex-results-comparison](../orcaflex-results-comparison/SKILL.md) - Compare results
## References
- Python concurrent.futures documentation
- psutil system monitoring
- Source: `src/digitalmodel/modules/orcaflex/universal/batch_processor.py`
- Source: `src/digitalmodel/modules/orcaflex/orcaflex_parallel_analysis.py`
## Sub-Skills
- [Basic Batch Configuration (+1)](basic-batch-configuration/SKILL.md)
- [Resource Management (+2)](resource-management/SKILL.md)
## Sub-Skills
- [Error Handling](error-handling/SKILL.md)
## Sub-Skills
- [Version Metadata](version-metadata/SKILL.md)
- [[1.0.0] - 2026-01-17](100-2026-01-17/SKILL.md)
- [Parallel Execution (+1)](parallel-execution/SKILL.md)
- [Batch Results JSON (+1)](batch-results-json/SKILL.md)