ScoreCompute
accelerates AI.✳
Your AI sets the goal. ScoreCompute composes, runs and checks the calculations.
Independent tools and checked compositions, with explicit assumptions.
Turn a question into a visible experiment.
Where should
we look next?
Compare viewpoints, challenge the result and see what new information changes.
Enter the Discovery laboratory STRATEGY · MOVE BY MOVEWhat did
the next move change?
Walk through a real chessboard, then request the engine’s analysis.
Explore the chessboard MONTE CARLO · CPU OR CUDACan randomness
find a circle?
Watch the method, choose your sample size, and measure the actual result.
Explore the simulationSee the calculation happen.
Checking availabilitySystem status
A recent monitoring sample is not available. Availability is checked independently of calculations. GPU presence comes from the worker inventory, without reserving capacity or running a benchmark. Stale observations are marked unconfirmed.
MCP observer reconnectingWaiting for a clientSelf-reported identity
Client software reports its own name and version; these are not verified. The AI model is unknown. This public log keeps the last 50 events in memory, without calculation inputs or results.
No calls observed yet. Connect an MCP client or run a calculation in the laboratory.
One mission.
Several ways through.
Give it a goal and your constraints. Rust compares approved plans,
connects the engines and shows why a route was chosen.
Rust chooses the route.
Exact task selection. Explicit uncertainty. A decision you can inspect.
Send a mission to reveal the native plan.
Nothing executes until you start.
The result includes the reasoning.
Compare task value, success bounds and measured work. See when Rust skips an unnecessary simulation or reuses an identical selection.
See what connects.
Know why it works.
Explore the bank. Follow the contracts.
Let Rust find a route from what you have to what you need.
A shared shape is a start.
A valid contract goes further.
Discover registered engines and explicit adapters. Inspect their units, models and prerequisites, then ask the native planner to explain a complete route—or what prevents it.
Reads the live Rust registry. No calculation starts.Use one engine, or compose an approved path. Independent tools remain directly callable through MCP. The atlas exposes their contracts; the Rust planner checks the connections.
MCP documentationMany stops.
One calculated path.
Place the points. Set the rules. Let Rust find the order.
Every segment comes from the engine’s returned route.
A distance can become a question about time.
Explore the Atlas’s separate four-point route example, with an explicit speed, rounding rule and uncertainty model. Assess a deadline without treating a geometric distance as a travel-time prediction.
A question. A real calculation.
From idea to result.
Choose your parameters and run a calculation.
Every result comes from a real Rust engine.
11 laboratory shortcuts.
Separate machines.
A shared calculation.
Offer a little compute. Follow real assignments and verified results.
Start with one small, public experiment.
Waiting for a verifiable network view.
The website is available, but contributor capacity cannot currently be confirmed.
Hardware and aliases are reported by clients. Only accepted calculation results are independently checked. Client instances are not a count of physical machines.
Even a short calculation leaves a trail.
Assignments and verified results, recorded by the coordinator.
Event replay · this diagram does not measure live GPU utilization.
Current jobs & recent receipts
No retained public job to display.
Only public synthetic jobs. Receipts are retained within the pilot’s limits.Latest recorded transitions
Waiting for a confirmed activity history.
Recent history, not a continuous utilization trace. A chunk assignment does not prove a GPU kernel has started.A million points.
One auditable estimate of π.
The coordinator splits a fixed synthetic calculation into small chunks. Available contributors request work; the coordinator checks every returned count on its own CPU.
Your client.
Your start and pause buttons.
- Starts paused. Registration and work begin only after your visible Start action.
- Choose GPUs, CPU threads and duty. CPU is off by default.
- Only compiled public workloads: π on CPU/CUDA and schedule experiments on CPU. No downloaded code or private datasets.
Pilot baseline: Windows x64 and Ubuntu 24.04 x64/glibc, subject to the published artifact’s requirements. Compatible NVIDIA drivers are needed for CUDA.
What this pilot demonstrates—and what it measures
The π workload uses indexed integer points; the schedule workload samples independent duration multipliers on a fixed 16-bit grid. Both are separate models from the hosted scientific engines. No random samples are invented by the interface. Observed throughput counts validated samples from all workloads in the last 60 seconds, divided by 60. Different workloads have different costs; this aggregate is not comparable compute power, theoretical FLOPS or a forecast.
The coordinator deliberately recomputes every chunk on CPU. This pilot demonstrates remote contribution and verification; it does not claim a net speedup. Only the contributor pool is counted here: GPUs in the hosted engine’s inventory are not added a second time. A single physical GPU has been used for hardware validation; a tested multi-GPU cluster is not claimed.
Clients may pause or disconnect. Stale resources receive no new work; jobs can expire. Duty is implemented with small batches and rest periods, not a wattage limit or immediate kernel interruption.
Stronger together.
Connect native engines through checked contracts.
Or join the contributor pilot for a shared, public calculation.