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| "name": "request_throughput",
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| "dataType": "sc:Float",
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| "fileObject": {
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| "@id": "mse-validation-summary-parquet"
|
| },
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| "extract": {
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| "column": "request_throughput"
|
| }
|
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|
| },
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| {
|
| "@type": "cr:Field",
|
| "@id": "mse-validation-summary/successful_requests",
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| "name": "successful_requests",
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| "fileObject": {
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| "@id": "mse-validation-summary-parquet"
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| "column": "successful_requests"
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|
| "@type": "cr:Field",
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| "@id": "mse-validation-summary/failed_requests",
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| "fileObject": {
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| "@id": "mse-validation-summary-parquet"
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| },
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| "extract": {
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| "column": "failed_requests"
|
| }
|
| }
|
| },
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| {
|
| "@type": "cr:Field",
|
| "@id": "mse-validation-summary/median_ttft_ms",
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| "name": "median_ttft_ms",
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| "fileObject": {
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| "@id": "mse-validation-summary-parquet"
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| },
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| "extract": {
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| "column": "median_ttft_ms"
|
| }
|
| }
|
| },
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| {
|
| "@type": "cr:Field",
|
| "@id": "mse-validation-summary/median_tpot_ms",
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| "name": "median_tpot_ms",
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| "dataType": "sc:Float",
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| "source": {
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| "fileObject": {
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| "@id": "mse-validation-summary-parquet"
|
| },
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| "extract": {
|
| "column": "median_tpot_ms"
|
| }
|
| }
|
| }
|
| ]
|
| },
|
| {
|
| "@type": "cr:RecordSet",
|
| "@id": "per-layer-kernel-summary",
|
| "name": "Per-Layer Kernel Summary",
|
| "description": "Per-component analytical OI decomposition and NCU kernel profiles for Llama-3.1-8B on H100 (prefill phase).",
|
| "field": [
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| {
|
| "@type": "cr:Field",
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| "@id": "per-layer-kernel-summary/record_type",
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| "name": "record_type",
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| "dataType": "sc:Text",
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| "@id": "per-layer-kernel-summary-parquet"
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| },
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| "extract": {
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| "column": "record_type"
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| }
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| }
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| },
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| {
|
| "@type": "cr:Field",
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| "@id": "per-layer-kernel-summary/model",
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| "name": "model",
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| "dataType": "sc:Text",
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| "fileObject": {
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| "@id": "per-layer-kernel-summary-parquet"
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| },
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| "extract": {
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| "column": "model"
|
| }
|
| }
|
| },
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| {
|
| "@type": "cr:Field",
|
| "@id": "per-layer-kernel-summary/hardware",
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| "name": "hardware",
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| "dataType": "sc:Text",
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| "fileObject": {
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| "@id": "per-layer-kernel-summary-parquet"
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| },
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| "extract": {
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| "column": "hardware"
|
| }
|
| }
|
| },
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| {
|
| "@type": "cr:Field",
|
| "@id": "per-layer-kernel-summary/phase",
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| "name": "phase",
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| "dataType": "sc:Text",
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| "source": {
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| "fileObject": {
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| "@id": "per-layer-kernel-summary-parquet"
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| },
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| "extract": {
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| "column": "phase"
|
| }
|
| }
|
| },
|
| {
|
| "@type": "cr:Field",
|
| "@id": "per-layer-kernel-summary/batch_size",
|
| "name": "batch_size",
|
| "dataType": "sc:Integer",
|
| "source": {
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| "fileObject": {
|
| "@id": "per-layer-kernel-summary-parquet"
|
| },
|
| "extract": {
|
| "column": "batch_size"
|
| }
|
| }
|
| },
|
| {
|
| "@type": "cr:Field",
|
| "@id": "per-layer-kernel-summary/sequence_length",
|
| "name": "sequence_length",
|
| "dataType": "sc:Integer",
|
| "source": {
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| "fileObject": {
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| "@id": "per-layer-kernel-summary-parquet"
|
| },
|
| "extract": {
|
| "column": "sequence_length"
|
| }
|
| }
|
| },
|
| {
|
| "@type": "cr:Field",
|
| "@id": "per-layer-kernel-summary/component_name",
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| "name": "component_name",
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| "dataType": "sc:Text",
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| "@id": "per-layer-kernel-summary-parquet"
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| },
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| "extract": {
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| "column": "component_name"
|
| }
|
| }
|
| },
|
| {
|
| "@type": "cr:Field",
|
| "@id": "per-layer-kernel-summary/bound",
|
| "name": "bound",
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| "@id": "per-layer-kernel-summary-parquet"
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| },
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| "extract": {
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| "column": "bound"
|
| }
|
| }
|
| },
|
| {
|
| "@type": "cr:Field",
|
| "@id": "per-layer-kernel-summary/flops",
|
| "name": "flops",
|
| "dataType": "sc:Float",
|
| "source": {
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| "fileObject": {
|
| "@id": "per-layer-kernel-summary-parquet"
|
| },
|
| "extract": {
|
| "column": "flops"
|
| }
|
| }
|
| },
|
| {
|
| "@type": "cr:Field",
|
| "@id": "per-layer-kernel-summary/bytes_accessed",
|
| "name": "bytes_accessed",
|
| "dataType": "sc:Float",
|
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|
| "@id": "per-layer-kernel-summary-parquet"
|
| },
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| "extract": {
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| "column": "bytes_accessed"
|
| }
|
| }
|
| },
|
| {
|
| "@type": "cr:Field",
|
| "@id": "per-layer-kernel-summary/operational_intensity",
|
| "name": "operational_intensity",
|
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|
| "fileObject": {
|
| "@id": "per-layer-kernel-summary-parquet"
|
| },
|
| "extract": {
|
| "column": "operational_intensity"
|
| }
|
| }
|
| },
|
| {
|
| "@type": "cr:Field",
|
| "@id": "per-layer-kernel-summary/kernel_name",
|
| "name": "kernel_name",
|
| "dataType": "sc:Text",
|
| "source": {
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| "fileObject": {
|
| "@id": "per-layer-kernel-summary-parquet"
|
| },
|
| "extract": {
|
| "column": "kernel_name"
|
| }
|
| }
|
| },
|
| {
|
| "@type": "cr:Field",
|
| "@id": "per-layer-kernel-summary/duration_us",
|
| "name": "duration_us",
|
| "dataType": "sc:Float",
|
| "source": {
|
| "fileObject": {
|
| "@id": "per-layer-kernel-summary-parquet"
|
| },
|
| "extract": {
|
| "column": "duration_us"
|
| }
|
| }
|
| },
|
| {
|
| "@type": "cr:Field",
|
| "@id": "per-layer-kernel-summary/compute_sm_throughput_pct",
|
| "name": "compute_sm_throughput_pct",
|
| "dataType": "sc:Float",
|
| "source": {
|
| "fileObject": {
|
| "@id": "per-layer-kernel-summary-parquet"
|
| },
|
| "extract": {
|
| "column": "compute_sm_throughput_pct"
|
| }
|
| }
|
| },
|
| {
|
| "@type": "cr:Field",
|
| "@id": "per-layer-kernel-summary/dram_throughput_pct",
|
| "name": "dram_throughput_pct",
|
| "dataType": "sc:Float",
|
| "source": {
|
| "fileObject": {
|
| "@id": "per-layer-kernel-summary-parquet"
|
| },
|
| "extract": {
|
| "column": "dram_throughput_pct"
|
| }
|
| }
|
| }
|
| ]
|
| }
|
| ],
|
| "rai:hasSyntheticData": true,
|
| "rai:dataLimitations": "Results cover NVIDIA H100, A100, RTX 3090, and RTX 2080 Ti GPUs only and may not generalize to other accelerators (AMD, Intel, TPU). Benchmark configurations are pinned to vLLM 0.19.0 and SGLang 0.5.9; results do not represent other engine versions. Concurrency levels (1-320) may not cover extreme-scale deployments. Not recommended as sole basis for hardware purchasing decisions or for comparing model task quality.",
|
| "rai:dataBiases": "Model selection over-represents Meta Llama and Alibaba Qwen families. Hardware is exclusively NVIDIA GPUs. Workload profiles are author-designed approximations of production traffic; real deployment patterns may differ.",
|
| "rai:personalSensitiveInformation": "No personally identifiable information is present. All API endpoints and credentials are stripped. Workload traces use synthetic random tokens or publicly available coding benchmarks.",
|
| "rai:dataUseCases": "Established uses: relative comparison of inference engine throughput, latency benchmarking under controlled conditions, TTFT scaling with context length in multi-turn sessions, per-kernel performance modelling. Not established: absolute latency prediction for production, model quality comparison, cost estimation.",
|
| "rai:dataSocialImpact": "Enables reproducible comparison of open-source LLM serving systems, supporting infrastructure research and reducing vendor lock-in.",
|
| "prov:wasDerivedFrom": [
|
| {
|
| "@id": "https://huggingface.co/datasets/princeton-nlp/SWE-bench",
|
| "name": "SWE-Bench"
|
| },
|
| {
|
| "@id": "https://github.com/TerminalBench/TerminalBench",
|
| "name": "TerminalBench"
|
| },
|
| {
|
| "@id": "https://github.com/xlang-ai/OSWorld",
|
| "name": "OSWorld"
|
| },
|
| {
|
| "@id": "https://huggingface.co/datasets/Aeala/ShareGPT_Vicuna_unfiltered",
|
| "name": "ShareGPT"
|
| }
|
| ],
|
| "prov:wasGeneratedBy": [
|
| {
|
| "@type": "prov:Activity",
|
| "@id": "collection-activity",
|
| "name": "Benchmark data collection",
|
| "description": "Models deployed on target GPU with specified serving engine (vLLM 0.19.0 or SGLang 0.5.9) and tensor parallelism. Requests sent per workload profile using closed-loop concurrency control with semaphore-based admission. 3-request warmup before each configuration. Per-request TTFT, TPOT, ITL, E2EL, and token counts recorded via streaming API responses. Kernel profiles collected via Nsight Compute (ncu) with hardware counter metrics. Collection period: March 2026 onwards.",
|
| "prov:qualifiedAssociation": {
|
| "@type": "prov:Association",
|
| "prov:hadRole": "data collector",
|
| "prov:agent": {
|
| "@type": "prov:SoftwareAgent",
|
| "name": "AgentPerfBench benchmarking harness"
|
| }
|
| }
|
| },
|
| {
|
| "@type": "prov:Activity",
|
| "@id": "preprocessing-activity",
|
| "name": "Data preprocessing and quality filtering",
|
| "description": "API credentials and endpoint URLs stripped from all records. Configurations with fewer than 75% of requests completing successfully are excluded. Summary statistics (mean, median, p90, p99 for TTFT, TPOT, ITL, E2EL) computed from successful requests only. Kernel names demangled from NCU output. Duplicate runs deduplicated by (model, hardware, engine, profile, concurrency) key. Results converted to Apache Parquet.",
|
| "prov:qualifiedAssociation": {
|
| "@type": "prov:Association",
|
| "prov:hadRole": "data preprocessor",
|
| "prov:agent": {
|
| "@type": "prov:SoftwareAgent",
|
| "name": "AgentPerfBench build pipeline (build_dataset.py, build_kernels.py, build_perkernel.py)"
|
| }
|
| }
|
| }
|
| ],
|
| "rai:dataCollection": "Automated benchmark collection. Models deployed on target GPU with specified engine and tensor parallelism. Requests sent per workload profile using closed-loop concurrency control with semaphore. Per-request TTFT, TPOT, ITL, E2EL, and token counts recorded. Kernel profiles collected via Nsight Compute (ncu) with hardware counter metrics.",
|
| "rai:dataCollectionType": "Automated measurement via benchmarking scripts. No human subjects or crowdsourcing.",
|
| "rai:dataCollectionMissingData": "Some model-hardware-concurrency combinations are absent due to OOM or engine incompatibility. Concurrency levels exceeding the session-pool size were filtered (see Concurrency filtering in README).",
|
| "rai:dataPreprocessingProtocol": "Credentials and API endpoints stripped. Configurations with fewer than 75% of requests completing successfully are excluded. Summary statistics computed from successful requests. Kernel names demangled from NCU output. Duplicate runs deduplicated by (model, hardware, engine, profile, concurrency) key.",
|
| "rai:dataAnnotationProtocol": "Not applicable. Fully automated benchmark collection with no human annotation.",
|
| "rai:dataAnnotationPlatform": "Not applicable. No human annotation.",
|
| "rai:dataAnnotationAnalysis": "Not applicable. No human annotation."
|
| }
|
|
|