Unary Operations

Prefer `@.` for multi-op elementwise expressions so every operator is dotted (especially unary negation). This ensures broadcast operations are fused. See [Kernel Fusion](perf/kernel_fusion.md).

The following unary operations are supported and can be broadcast over NDArray:

• -, !, abs, acos, acosh, asin, asinh, atan, atanh, cbrt, conj, cos, cosh, deg2rad, exp, exp2, expm1, floor, imag, isfinite, log, log10, log1p, log2, rad2deg, real, sign, signbit, sin, sinh, sqrt, tan, tanh, ^2, ^-1 or inv

Differences from Base Julia

• The acosh function in Julia will error on inputs outside of the domain (x >= 1), but cuNumeric.jl will return NaN.

cuNumeric.unary_reduction_map Constant

Supported Unary Reduction Operations

The following unary reduction operations are supported and can be applied directly to NDArray values:

• all • any • maximum • minimum • prod • sum

These operations follow standard Julia semantics.

Reduction over specific dimensions is supported via the dims keyword argument, following the same semantics as Julia's base reduction functions.

Examples

A = cuNumeric.ones(5)

maximum(A)
sum(A)

# Reduce over a specific dimension
B = cuNumeric.ones(3, 4)
sum(B, dims=1)    # 1×4 result
sum(B, dims=2)    # 3×1 result

# Reduce over multiple dimensions
sum(B, dims=(1,2))  # 1×1 result

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