Using MIND Core v1 Today

This page gives a practical, end-to-end guide to using the MIND Core v1 toolchain: surface language → IR → autodiff → MLIR → CPU runtime → conformance.

1. Installing mindc

From source

Clone and build:

git clone https://github.com/cputer/mind.git
cargo build --release
./target/release/mindc --help

Validating installation

mindc --version
mindc --stability

Both commands reflect the published Core v1 stability & versioning contract.

2. Writing your first Core v1 program

Create a file simple.mind:

fn main(x: tensor<f32>[2, 2]) -> tensor<f32>[2, 2] {
  let y = x + x
  return y
}

Compile to IR:

mindc simple.mind -o simple.ir

3. Running through the CPU runtime

Use the runtime CLI (from mind-runtime repo):

runtime run simple.ir --input x=[1,2,3,4]

Expected output:

[[2,4],[6,8]]

4. Using autodiff

Extend simple.mind:

fn main(x: tensor<f32>[2]) -> tensor<f32>[1] {
  let y = sum(x)
  return y
}

Generate gradient IR:

mindc simple.mind --grad --func main -o grad.ir

5. Lowering to MLIR (CPU backend)

mindc main.mind --mlir -o main.mlir

6. Verifying conformance

CPU baseline:

mindc conformance --profile cpu

GPU profile:

mindc conformance --profile gpu

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