Turtle
1c29d96067
Every recorded case states what it measures and which user scenario it affects, shown on hover in the report. Endpoints whose workers report process CPU time default to the measured non-CPU share and busy parallelism; the Session corpus worker now reports CPU time per endpoint. Machine profiles carry logical CPU counts, and the page shows each default share with its source and can reset overrides.
59 lines
4.6 KiB
TypeScript
59 lines
4.6 KiB
TypeScript
/**
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* Reviewed machine profiles for the scaled-scenario benchmark report.
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*
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* `cpuScore` is the PassMark single-thread rating retrieved on 2026-10-07 from cpubenchmark.net. Measured
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* endpoints run on one JavaScript thread, so the report scales their CPU-bound share by the single-thread
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* ratio. `cores` limits endpoints whose measured CPU time shows more than one busy CPU; memory size is not
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* modelled. PassMark ratings across ISAs, for burstable or shared vCPUs, and for hybrid efficiency cores, are
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* coarse.
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*
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* `ioLatencyUs` is a typical synchronous 4 KiB random-access latency at queue depth 1 for the profile's
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* default storage. Laptop values come from published SSD reviews for the interface generation; cloud values
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* come from the provider's documented latency class for its default system disk. They are estimates.
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*/
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/** One modelled machine with its CPU and default-storage performance. */
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export interface MachineProfile {
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readonly id: string
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readonly label: string
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readonly cpu: string
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readonly cpuScore: number
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/** Logical CPUs: hardware threads on laptops, vCPUs on cloud instances. */
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readonly cores: number
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readonly storage: string
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readonly ioLatencyUs: number
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/** Lower-case substrings of `os.cpus()[0].model` that identify the measuring machine as this profile. */
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readonly cpuModelMatches?: readonly string[]
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}
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/** Profiles in report order. */
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export const MACHINE_PROFILES: readonly MachineProfile[] = [
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{ id: 'laptop-2015-win', label: '2015 Windows laptop', cpu: 'Intel Core i5-5200U', cpuScore: 1486, cores: 4, storage: 'SATA SSD', ioLatencyUs: 90 },
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{ id: 'laptop-2015-mac', label: '2015 MacBook Pro 13"', cpu: 'Intel Core i5-5257U', cpuScore: 1737, cores: 4, storage: 'PCIe AHCI SSD', ioLatencyUs: 90 },
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{ id: 'laptop-2019-win', label: '2019 Windows laptop', cpu: 'Intel Core i5-8265U', cpuScore: 2003, cores: 8, storage: 'NVMe PCIe 3.0 SSD', ioLatencyUs: 70 },
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{ id: 'laptop-2023-win', label: '2023 Windows laptop', cpu: 'Intel Core i5-1335U', cpuScore: 3241, cores: 12, storage: 'NVMe PCIe 4.0 SSD', ioLatencyUs: 55 },
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{ id: 'laptop-2023-mac', label: '2023 MacBook Air', cpu: 'Apple M2', cpuScore: 4208, cores: 8, storage: 'Apple SSD', ioLatencyUs: 55, cpuModelMatches: ['apple m2'] },
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{ id: 'laptop-2026-win', label: '2026 Windows laptop', cpu: 'Intel Core Ultra 5 225H', cpuScore: 4247, cores: 14, storage: 'NVMe PCIe 4.0 SSD', ioLatencyUs: 50 },
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{ id: 'laptop-2026-mac', label: '2026 MacBook', cpu: 'Apple M5', cpuScore: 6341, cores: 10, storage: 'Apple SSD', ioLatencyUs: 50, cpuModelMatches: ['apple m5'] },
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{ id: 'aws-t3', label: 'AWS t3.medium', cpu: 'Intel Xeon Platinum 8259CL', cpuScore: 1948, cores: 2, storage: 'EBS gp3', ioLatencyUs: 500 },
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{ id: 'aws-m6i', label: 'AWS m6i.large', cpu: 'Intel Xeon Platinum 8375C', cpuScore: 2474, cores: 2, storage: 'EBS gp3', ioLatencyUs: 500 },
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{ id: 'aws-m7i', label: 'AWS m7i.large', cpu: 'Intel Xeon Platinum 8488C', cpuScore: 3113, cores: 2, storage: 'EBS gp3', ioLatencyUs: 500 },
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{ id: 'aws-m7g', label: 'AWS m7g.large', cpu: 'AWS Graviton3 (Neoverse V1)', cpuScore: 1554, cores: 2, storage: 'EBS gp3', ioLatencyUs: 500 },
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{ id: 'gcp-n2', label: 'GCP n2-standard-4', cpu: 'Intel Xeon Platinum 8273CL', cpuScore: 2200, cores: 4, storage: 'pd-balanced', ioLatencyUs: 800 },
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{ id: 'azure-d4s-v5', label: 'Azure D4s v5', cpu: 'Intel Xeon Ice Lake (8375C rating)', cpuScore: 2474, cores: 4, storage: 'Premium SSD P10', ioLatencyUs: 1000 },
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{ id: 'aliyun-g7', label: 'Alibaba Cloud ecs.g7.xlarge', cpu: 'Intel Xeon Ice Lake (8375C rating)', cpuScore: 2474, cores: 4, storage: 'ESSD PL0', ioLatencyUs: 400 },
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{ id: 'github-ubuntu-24.04', label: 'GitHub ubuntu-24.04 runner', cpu: 'AMD EPYC 7763', cpuScore: 2517, cores: 2, storage: 'Azure managed disk', ioLatencyUs: 300, cpuModelMatches: ['epyc 7763'] },
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{ id: 'github-ubuntu-24.04-genoa', label: 'GitHub ubuntu-24.04 runner (Genoa)', cpu: 'AMD EPYC 9V74', cpuScore: 2888, cores: 2, storage: 'Azure managed disk', ioLatencyUs: 300, cpuModelMatches: ['epyc 9v74'] },
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{ id: 'reference-m4-pro', label: 'Calibration reference', cpu: 'Apple M4 Pro', cpuScore: 4547, cores: 14, storage: 'Apple SSD', ioLatencyUs: 55, cpuModelMatches: ['apple m4'] },
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]
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/**
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* Identify the measuring machine among the reviewed profiles.
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* @param cpuModel - `os.cpus()[0].model` of the machine that ran the benchmarks.
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* @returns the matching profile id, or `undefined` when no profile describes the machine.
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*/
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export function matchMachineProfile(cpuModel: string): string | undefined {
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const model = cpuModel.toLowerCase()
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return MACHINE_PROFILES.find(profile => profile.cpuModelMatches?.some(match => model.includes(match)) === true)?.id
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}
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