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https://github.com/martinjrobins/diffsl


https://github.com/martinjrobins/diffsl

compiler dsl mass-matrix ode ode-model sparse tensor

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# DiffSL

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A compiler for a domain-specific language for ordinary differential equations (ODEs) of the following form:

$$
M(t) \frac{d\mathbf{u}}{dt} = F(\mathbf{u}, t)
$$

As an example, the following code defines a classic DAE testcase, the Robertson
(1966) problem, which models the kinetics of an autocatalytic reaction, given
by the following set of equations:

$$
\begin{align}
\frac{dx}{dt} &= -0.04x + 10^4 y z \\
\frac{dy}{dt} &= 0.04x - 10^4 y z - 3 \cdot 10^7 y^2 \\
0 &= x + y + z - 1
\end{align}
$$

The DiffSL code for this problem is as follows:

```
in = [k1, k2, k3]
k1 { 0.04 }
k2 { 10000 }
k3 { 30000000 }
u_i {
x = 1,
y = 0,
z = 0,
}
dudt_i {
dxdt = 1,
dydt = 0,
dzdt = 0,
}
M_i {
dxdt,
dydt,
0,
}
F_i {
-k1 * x + k2 * y * z,
k1 * x - k2 * y * z - k3 * y * y,
1 - x - y - z,
}
out_i {
x,
y,
z,
}
```

## DiffSL Language Features

See the [DiffSL language documentation](https://martinjrobins.github.io/diffsl/) for a full description.

* Tensor types:
* Scalars (double precision floating point numbers)
* Vectors (1D arrays of scalars)
* N-dimensional tensor of scalars
* Sparse/dense/diagonal tensors
* Tensor operations:
* Elementwise operations
* Broadcasting
* Tensor contractions/matmul/translation etc via index notation

## Usage

Generally the easiest way to make use of DiffSL is via an ode solver that supports the language, for example the [diffsol](https://github.com/martinjrobins/diffsol) library. Please see the diffsol documentation and consult the [DiffSL language documentation](https://martinjrobins.github.io/diffsl/) for more information.

If you are writing your own ode solver and want to make use of the DiffSL compiler, please either get in touch by opening an issue, contacting the [author](mailto:[email protected]) or by looking at the [diffsol source code](https://github.com/martinjrobins/diffsol/blob/main/src/ode_solver/diffsl.rs).

## Dependencies

To use the llvm backend (optional) You will need to install the [LLVM project](https://llvm.org/). The easiest way to
install this is to use the package manager for your operating system. For
example, on Ubuntu you can install these with the following command:

```bash
sudo apt-get install llvm
```

## Installation

You can install DiffSL using cargo. By default the cranelift backend will be used. To use the llvm backend (which generates more optimised code), you will need to indicate the llvm version you have installed using a feature flag. For example, for llvm 16:

```bash
cargo add diffsl --features llvm16-0
```

Other versions of llvm are also supported given by the features `llvm15-0`, `llvm16-0`, `llvm17-0`, `llvm18-0`.