{"adoption": {"forks": 178, "observed_at": "2026-08-28T04:03:42.925658+00:00", "stars": 1133}, "canonical_url": "https://ross.abutalabs.com/products/simai", "card": {"archived": false, "artifact_type": "library", "description": null, "domain": ["simulation", "machine-learning", "networking", "microservices", "large-language-models", "performance"], "enriched": true, "function": ["simulation", "machine-learning", "networking", "benchmarking", "llm-training", "llm-inference"], "health_score": 79, "homepage": null, "language": "Python", "license": "Apache-2.0", "license_family": "permissive", "maturity": "active", "member_repos": ["aliyun/SimAI"], "name": "aliyun/SimAI", "platform": ["python"], "pushed_at": "2026-08-14T09:18:27+00:00", "repo": "aliyun/SimAI", "stars": 1133, "tags": ["network-simulation", "gpu-clusters", "collective-communication", "nsdi-paper", "training-simulation", "inference-simulation", "alibaba-cloud", "linux"], "topics": [], "urls": [], "use_cases": ["simulate network traffic of large-scale LLM training on GPU clusters", "evaluate network designs for distributed AI training before deployment", "model prefill/decode disaggregated inference performance", "estimate GPU memory and decode latency for LLM inference", "generate training workloads for models like DeepSeek and Qwen", "analyze collective communication flows offline with SimCCL"], "what_it_is": "SimAI is a large-scale network simulation toolkit from Alibaba Cloud for modeling AI training and inference workloads on GPU clusters, published at NSDI'25. It combines workload generation (AICB), collective communication modeling (SimCCL), and request scheduling (adapted from Vidur) to simulate end-to-end distributed LLM training and prefill/decode inference.", "when_to_avoid": ["you need a production training or serving framework rather than a simulator", "you want quick single-GPU model benchmarking", "you need cycle-accurate hardware simulation"], "when_to_choose": ["you are designing or evaluating network topologies and congestion control for AI clusters", "you need to predict training or inference performance without running real GPU jobs", "you want to study collective communication behavior at scale"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/simai", "repo": "aliyun/SimAI", "role": "main", "score": 66}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:03:42.925658+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-30T06:37:24.727487+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "baa4d4f48a1e427565f799dbe0ee25f945d97b817d5096c78360d9d0413b8aa6", "fetched_at": "2026-08-28T04:03:42.925658+00:00", "kind": "readme", "missing": false, "url": "https://github.com/aliyun/SimAI"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:03:42.925658+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-30T06:37:24.727487+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "baa4d4f48a1e427565f799dbe0ee25f945d97b817d5096c78360d9d0413b8aa6", "fetched_at": "2026-08-28T04:03:42.925658+00:00", "kind": "readme", "missing": false, "url": "https://github.com/aliyun/SimAI"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-30T06:37:24.727487+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "baa4d4f48a1e427565f799dbe0ee25f945d97b817d5096c78360d9d0413b8aa6", "fetched_at": "2026-08-28T04:03:42.925658+00:00", "kind": "readme", "missing": false, "url": "https://github.com/aliyun/SimAI"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:03:42.925658+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:03:42.925658+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:03:42.925658+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-30T06:37:24.727487+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "baa4d4f48a1e427565f799dbe0ee25f945d97b817d5096c78360d9d0413b8aa6", "fetched_at": "2026-08-28T04:03:42.925658+00:00", "kind": "readme", "missing": false, "url": "https://github.com/aliyun/SimAI"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:03:42.925658+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:03:42.925658+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-30T06:37:24.727487+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "baa4d4f48a1e427565f799dbe0ee25f945d97b817d5096c78360d9d0413b8aa6", "fetched_at": "2026-08-28T04:03:42.925658+00:00", "kind": "readme", "missing": false, "url": "https://github.com/aliyun/SimAI"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:03:42.925658+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:03:42.925658+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:03:42.925658+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-30T06:37:24.727487+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "baa4d4f48a1e427565f799dbe0ee25f945d97b817d5096c78360d9d0413b8aa6", "fetched_at": "2026-08-28T04:03:42.925658+00:00", "kind": "readme", "missing": false, "url": "https://github.com/aliyun/SimAI"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:03:42.925658+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:03:42.925658+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-30T06:37:24.727487+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "baa4d4f48a1e427565f799dbe0ee25f945d97b817d5096c78360d9d0413b8aa6", "fetched_at": "2026-08-28T04:03:42.925658+00:00", "kind": "readme", "missing": false, "url": "https://github.com/aliyun/SimAI"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-30T06:37:24.727487+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "baa4d4f48a1e427565f799dbe0ee25f945d97b817d5096c78360d9d0413b8aa6", "fetched_at": "2026-08-28T04:03:42.925658+00:00", "kind": "readme", "missing": false, "url": "https://github.com/aliyun/SimAI"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-30T06:37:24.727487+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "baa4d4f48a1e427565f799dbe0ee25f945d97b817d5096c78360d9d0413b8aa6", "fetched_at": "2026-08-28T04:03:42.925658+00:00", "kind": "readme", "missing": false, "url": "https://github.com/aliyun/SimAI"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-30T06:37:24.727487+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "baa4d4f48a1e427565f799dbe0ee25f945d97b817d5096c78360d9d0413b8aa6", "fetched_at": "2026-08-28T04:03:42.925658+00:00", "kind": "readme", "missing": false, "url": "https://github.com/aliyun/SimAI"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 97, "longevity": 49, "rhythm": 35}, "computed_at": "2026-09-02T17:46:02.011165+00:00", "flags": ["no_releases"], "formula": "round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)", "inputs": {"age_days": 691, "days_push": 19, "days_rel": null, "gap_med": null, "n_releases_24m": 0}, "score": 66, "version": 2}, "staleness": {"enrichment_outdated": false, "low_confidence": false, "scrape_days": 9, "stale_scrape": false}}