THE CALCKERNEL LANGUAGE
CalcKernel (CK) is a statically typed language for focused numerical workloads. It compiles CK programs to native machine code, with C and WebAssembly outputs for integration into existing systems.
CK is designed for small, compute-heavy routines embedded in larger applications. Its type system, defined numeric rules, and explicit data interfaces help developers reason about what a kernel reads, changes, and returns.
Function signatures name each input and result type. CK checks calls and assignments while you compile.
fn scale(x: f64) -> f64Learn more 02 / 04Conversions are explicit and floating-point rules are defined. Checked integer overflow is available in Native and C builds.
i32 · f64 · checkedLearn more 03 / 04A typed slice carries an address and length. Your application supplies and owns the memory that a kernel reads or updates.
slice<f64> · data · lenLearn more 04 / 04Build a Native executable or library, emit C with an ABI header, or produce a WebAssembly module for a compatible runtime.
Native · C ABI · WasmLearn more This kernel scales each value in a caller-provided f64 slice by a factor. The typed input and in-place update make the data boundary clear; the compiler only applies transformations when their correctness conditions and the target allow them.
Explore the languageexport fn scale(
values: slice<f64>,
factor: f64
) -> void {
let i: u32 = 0;
while i < values.len {
values[i] = values[i] * factor;
i = i + 1;
}
}slice<f64> · while · export fnCompare CK, C++, Rust, JavaScript, Java, and NumPy on the same image-blur and matrix-multiplication inputs. See how each implementation performs with JavaScript as 1.0x.
Apply the same nine-point weighted filter to every interior pixel; border pixels are zero.
| Language | Speedup vs tuned JavaScript |
|---|---|
| C++ | 4.1x |
| Rust | 4.0x |
| CK | 3.7x |
| Java | 2.1x |
| JavaScript | 1.0x |
| NumPy | 0.64x |
The same fixed inputs for every implementation. NumPy calls the native Apple Accelerate matrix library.
| Language | Speedup vs tuned JavaScript |
|---|---|
| NumPy | 117.1x |
| C++ | 5.4x |
| CK | 5.4x |
| Rust | 5.3x |
| Java | 3.2x |
| JavaScript | 1.0x |
JavaScript = 1.0x · same-machine test · compressed bar lengths; compare the multipliers
CK is designed for numerical kernels embedded in a larger system: data transforms, repeated scoring or simulation, and other compute-heavy routines. Keep the data contract at the boundary and let the host application handle orchestration, storage, and user-facing features.
Normalize, scale, or otherwise process numeric arrays supplied by the caller.
slice<f64> → valuesExpress repeated domain calculations with typed inputs, explicit branches, and predictable numeric rules.
score(input) → f64Package the same focused computation as a Native library, C interface, or WebAssembly module.
Native · C ABI · WasmCK focuses on computation kernels. The host application owns memory and handles I/O, networking, and presentation around them.
Keep your application in the tools you know. Use CK where a focused numerical kernel has a clear job and a clear boundary.
Use them when they already fit your project. CK is a narrower language for numerical kernels: one source can become a Native library, C source, or WebAssembly module for an existing host. That focused boundary is the advantage; measure your workload before choosing on speed.
See the measurementsLook for a repeated calculation that profiling shows is costly, with numeric inputs and a boundary you can describe clearly. It is most useful when that kernel must also be shared across applications or targets.
Explore output optionsExport a CK function, build a module, then call it through a host interface. Node.js can load WebAssembly; Python and Rust can call a Native library through its generated C ABI. The host still owns data and memory.
Read the language overview, run a first kernel, then compare results using the same inputs and target machine.
Writing CK in VS Code? Get highlighting, live diagnostics, completion, and navigation. Explore the extension