FAQ

I get "The map of engines is empty" or "Fail to find engine". What's wrong?

You need to add an engine dependency alongside multik-core. The core module only provides types and interfaces — it does not include an implementation.

Add one of the following:

Make sure all Multik artifact versions match.

The multik-openblas JAR is very large (~115 MB). Can I reduce it?

The JVM artifact bundles native libraries for all desktop platforms (Linux x64, macOS x64/arm64, Windows x64) in a single JAR. Platform-specific artifacts are not yet available.

Workaround: If size is critical, use multik-kotlin instead — it is much smaller and has no native dependencies.

I get GLIBC_2.35 not found on Linux

The pre-built native library in multik-openblas requires glibc 2.35+. Older distributions (e.g., Ubuntu 20.04) do not have it.

Solutions:

• Upgrade to Ubuntu 22.04+ or equivalent.

• Use multik-kotlin instead.

• Build the native library from source against your system's glibc.

How do I select or switch between engines?

multik-default auto-detects and loads the best engine. You can switch at runtime:

Why is the first Multik call slow?

The native engine (OpenBLAS) is lazily loaded on first use — the library is extracted from the JAR and loaded via JNI. Subsequent calls are fast.

Workarounds:

• Perform a small warm-up call during application startup.

• Use multik-kotlin if startup latency matters more than computation speed.

Does Multik work on Android?

Yes, but with caveats:

• Use multik-kotlin, not multik-openblas or multik-default. The OpenBLAS JAR bundles desktop .so files that cause build errors like "libmultik_jni-linuxX64.so is not an ABI" or AAB packaging failures.

• On older Android devices, multik-default may crash with NoClassDefFoundError.

• The native engine currently supports arm64-v8a only; armv7 and x86_64 Android ABIs are not supported.

Does Multik work on Kotlin/Native, JS, and WASM?

multik-kotlin supports JVM, JS, Native, and WASM targets.

multik-openblas is available only on JVM and desktop Native (Linux x64, macOS x64/arm64, Windows x64). It is not available on iOS, JS, or WASM.

Reshaping a sliced array produces wrong data

Slicing returns a view that shares the underlying data buffer with non-contiguous strides. reshape assumes contiguous memory, so it can produce incorrect results on views.

Fix: Call .copy() before reshaping:

Mixing numeric types causes a runtime error

Multik does not support the generic Number type as an element type. When you mix types like 1.0 (Double) and 2 (Int) in mk[1.0, 2], the compiler infers Number, which compiles but fails at runtime.

Fix: Ensure all elements use the same type:

dot on sliced views can return incorrect results

Computing dot on a row extracted from a 2D array (which is a view) may produce wrong results, especially with the native engine.

Fix: Copy the slice first:

Integer division truncates

mk.ndarray(mk[5]) / 2 yields [2], not [2.5]. Use Double or Float arrays for fractional results.

Does Multik support broadcasting?

No. Multik does not support NumPy-style broadcasting. Array-array operations require both operands to have the same shape.

Workaround: Use .map or create a same-shaped array of the scalar value.

Does Multik support boolean masks or where?

No. Element-wise comparisons that return boolean arrays (like array == 0), boolean indexing (array[mask]), and np.where(condition, x, y) are not yet supported.

Workaround: Use filter, mapIndexed, or manual iteration:

How do I do matrix multiplication?

Use mk.linalg.dot(a, b) or the infix syntax a dot b. This handles matrix-matrix, matrix-vector, and vector-vector products. See dot for details.

Can I read .npy files?

.npy format is supported on JVM only. It is not available on Native, JS, or WASM targets.

Can I read CSV files with complex numbers?

CSV reading exists but has known issues when parsing complex numbers formatted by NumPy. As a workaround, parse the file manually and construct the complex array in code.