Monte Carlo estimate of π with Rust and CUDA

What does a real call return?

With 1,000,000 samples and seed 42 on CUDA, the estimate is 3.14076 with an interval of [3.13753, 3.14397]. The absolute error is 0.00084.

Recorded on 2 November 2026 through the public MCP endpoint, service release 0.17.1. Inputs and full responses, response SHA-256 ae1818c1c0ce…. Verdict values are the literal values the tool returns. Run the same inputs yourself to compare; elapsed times vary, and a new release may change the figures.

Checked against

• Quarter-circle area π/4, known π, seeded sequence reproducibility and preservation under partitioning.
• CPU/CUDA agreement test exists and is ignored by default; it requires an actual CUDA device.

Recorded on release 0.16.1. These checks cover the listed cases, not every input. Evidence cards.

How it works

The engine samples points uniformly in a unit square and counts those inside the quarter circle. Four times that proportion estimates π. Random values depend on the seed and global sample index, so worker assignment does not change the experiment.

Inputs and units

Provide 100 to 5,000,000 samples, an integer seed and a CPU or CUDA backend. Optionally select CUDA device IDs from the available hardware.

What the result contains

The result includes the estimate, absolute error, Wilson interval, convergence history, a bounded sample for plotting, execution time and device provenance.

Example MCP call

{
  "name": "simulate_pi",
  "arguments": {
    "samples": 1000000,
    "seed": 42,
    "backend": "cuda"
  }
}

Send this tool name and arguments through a connected MCP client. Discover the authoritative input schema with tools/list.

Call this engine in one command

Node.js 20+ and npm. This downloads a small remote MCP client; it does not install the engine locally.

npx --yes --package https://scorecompute.com/downloads/scorecompute-call-0.14.2.tgz scorecompute-call simulate_pi --arguments '{"samples":1000000,"seed":42,"backend":"cuda"}'

Client download, PowerShell input and verification →

Cite this engine

Engine identified by source hash, source SHA-256 99b263fac08d…. Evidence recorded on release 0.16.1; the public service currently runs 0.17.1. Replace the access date when you cite it.

ScoreCompute. Monte Carlo estimate of π with Rust and CUDA (simulate_pi), identified by source hash, source SHA-256 99b263fac08d3432200a85dcf05b92209780ecdf69afbeaea53bb8c464b5db90. Evidence release 0.16.1, service release 0.17.1. https://scorecompute.com/engines/simulate-pi/ (accessed YYYY-MM-DD).

All engine citations · Evidence card

Execution and availability

ScoreCompute exposes this tool through MCP Streamable HTTP. Rust computation runs on a connected worker; the public website and MCP gateway run separately. Among these 22 scientific tools, CUDA is implemented for simulate_pi; the other scientific engines run on CPU. The separate contributor network runs two compiled public workloads: a π estimate and fixed synthetic schedule probes. Requests are bounded and concurrent work may be refused when capacity is occupied.

Record inputs, assumptions and returned provenance when sharing a result. The public observatory displays software client names and tool activity, without publishing calculation arguments or results.