--- license: mit task_categories: - text-generation tags: - llm-serving - streaming-inference - vllm - systems pretty_name: Stream2LLM Data viewer: false --- # Stream2LLM Dataset Dataset for the paper: *Stream2LLM: Overlap Context Streaming and Prefill for Reduced Time-to-First-Token* (MLSys 2026 artifact evaluation). Contains workload traces, experiment run logs, and performance model measurements used to produce all figures, tables, and inline numbers in the paper. This repository is a git submodule of the main [Stream2LLM artifact](https://github.com/rajveerb/stream2llm/tree/mlsys_artifact) (branch: `mlsys_artifact`). Data files are stored with Git LFS on HuggingFace. To fetch everything: ```bash # Option 1: Clone parent repo with submodules, then pull LFS files git clone --recurse-submodules -b mlsys_artifact https://github.com/rajveerb/stream2llm.git cd stream2llm/data && git lfs install && git lfs pull && cd ../.. # Option 2: If you already cloned without submodules git submodule update --init cd data && git lfs install && git lfs pull && cd .. ``` ## Directory Structure ``` data/ ├── anns/ # ANNS workload data │ ├── res/ # 4,997 pipeline trace CSVs │ ├── retrieved_corpus_content.*.json # Corpus content shards │ ├── query_trace_map_5k.json # Query-to-trace mapping │ └── compute_workload_stats.py # Workload statistics script ├── crawl/ # Crawler workload data │ ├── traces/simpleQA_ALL/ # 4,322 query trace CSVs │ └── compute_workload_stats.py # Workload statistics script ├── perf_model/ # Performance model measurements │ ├── recomputation/ # 7 recomputation latency JSONs │ └── swap/ # 11 swap latency JSONs └── run_log/ # Experiment run logs ├── crawler/ # 5 crawler experiment configurations └── anns/ # 5 ANNS experiment configurations ``` ## Workload Traces ### ANNS (`anns/res/`) 4,997 pipeline trace files from approximate nearest neighbor search workloads. Each file is named `_L10000_W8_query_pipeline_trace.csv` and contains: | Column | Description | |--------|-------------| | `StartTime_us` | Chunk start time in microseconds | | `EndTime_us` | Chunk end time in microseconds | | `StartIteration` | Starting iteration index | | `EndIteration` | Ending iteration index | | `PipelinePool` | Tuple of candidate IDs in the pipeline pool | Each row represents a chunk arrival — a batch of ANNS iterations that produces new candidate results. Queries have 1–26 chunks (median 4), with inter-chunk arrival times ranging from sub-millisecond to ~9 seconds (median 37 ms). ### Crawler (`crawl/traces/simpleQA_ALL/`) 4,322 query trace files from a web crawling workload (SimpleQA question-answering). Each file is named `query_.csv` and contains: | Column | Description | |--------|-------------| | `type` | Event type: `tavily_search` or `page_scrape` | | `startTime` | Event start time in seconds | | `endTime` | Event end time in seconds | | `query` | The original query string (on search rows) | | `links_found` | Number of links returned by search | | `url` | URL scraped (on page_scrape rows) | | `content_length` | Length of scraped content in characters | | `content` | Scraped page text | | `link_idx` | Index of the link being scraped | Each row is a chunk event. The first row is typically a `tavily_search` followed by `page_scrape` events. Queries have 1–17 chunks (median 8), with inter-chunk arrival times of 3 ms to ~35 seconds (median 701 ms). ## Performance Model (`perf_model/`) Microbenchmark measurements for KV cache eviction cost modeling, collected across multiple GPU types (A40, A100, H100, H200) and model configurations (8B, 70B with varying tensor parallelism). - **`recomputation/`**: Recomputation latency in ms, keyed by number of tokens recomputed (e.g., 16, 32, ..., 8192). Each key maps to an array of repeated measurements. - **`swap/`**: Swap (CPU↔GPU transfer) latency in ms, same key structure. Files ending in `_kernel_latency.json` contain kernel-only timings; others include end-to-end transfer overhead. Hardware configurations: `A40`, `A100`, `H100_tp2`, `H100_tp4_70B`, `H200_tp2`, `H200_tp4_70B`. ## Run Logs (`run_log/`) Experiment outputs from the Stream2LLM serving system, organized by workload and configuration. ### Structure ``` run_log///// ├── config_.yaml # Experiment configuration └── run_metrics.csv # Per-event metrics log ``` ### Configurations | Workload | Config Directory | Description | |----------|-----------------|-------------| | Crawler | `H200_enhanced_schedulers_v1_full` | Standard H200 runs | | Crawler | `H200_enhanced_schedulers_v1_full_delay_10` | With 10ms artificial delay (memory pressure) | | Crawler | `H200_..._delay_10_recomp_only` | Delay + recomputation-only eviction | | Crawler | `H200_..._delay_10_swap_only` | Delay + swap-only eviction | | Crawler | `H100_enhanced_schedulers_v1_full` | Standard H100 runs | | ANNS | `H200_enhanced_schedulers_v1_full` | Standard H200 runs | | ANNS | `H200_enhanced_schedulers_v1_500q_delay_30` | With 30ms artificial delay (memory pressure) | | ANNS | `H200_..._delay_30_recomp_only` | Delay + recomputation-only eviction | | ANNS | `H200_..._delay_30_swap_only` | Delay + swap-only eviction | | ANNS | `H100_enhanced_schedulers_v1_full` | Standard H100 runs | ### Schedulers Each configuration contains results for four scheduling policies: - **`default_vllm`**: Default vLLM scheduler (baseline) - **`fcfs`**: First-come-first-served - **`lcas`**: Last-chunk-arrival-stamp scheduler - **`mcps`**: Most-chunks-processed scheduler ### Run Metrics CSV The `run_metrics.csv` file logs timestamped events for each experiment run: | Column | Description | |--------|-------------| | `event_timestamp` | Unix timestamp of the event | | `event_type` | Event type (e.g., `replay_start`, `query_delay`, `chunk_sent`, `response_received`) | | `query_id` | Query identifier | | `request_id` | vLLM request identifier | | `stream` | Whether streaming input was enabled | | `concurrency` | Whether concurrent requests were enabled | | `duration_secs` | Duration of the event in seconds | | `details` | Additional event-specific information | | `request_size` | Size of the request in tokens | | `concurrent_requests` | Number of concurrent requests at event time | | `replay_rate` | Poisson arrival rate used | | `prev_event_type` | Previous event type for this query | ## Corpus Content (`anns/`) The ANNS corpus is stored as sharded JSON files (`retrieved_corpus_content.*.json` and `retrieved_corpus_content.part.*.json`). Each file maps document IDs to their text content, used for constructing input sequences from ANNS retrieval results. The `query_trace_map_5k.json` file maps query IDs to their corresponding pipeline trace filenames and query text.