# Intrinsics for Short Vector Math Library Operations (SVML)

The Intel® oneAPI DPC++/C++ Compiler provides short vector math library (SVML) intrinsics to compute vector math functions. These intrinsics are available for IA-32 and Intel® 64 architectures running on supported operating systems. The prototypes for the SVML intrinsics are available in the immintrin.h file.

To use these intrinsics, include the immintrin.h file as follows:

    #include <immintrin.h>

The SVML intrinsics do not have any corresponding instructions.

The SVML intrinsics are vector variants of corresponding scalar math operations using `__m128`, `__m128d`, `__m256`, `__m256d`, and `__m256i` data types. They take packed vector arguments, perform the operation on each element of the packed vector argument, and return a packed vector result.

For example, the argument to the `_mm_sin_ps` intrinsic is a packed 128-bit vector of four 32-bit precision floating point numbers. The intrinsic computes the sine of each of these four numbers and returns the four results in a packed 128-bit vector.

Using SVML intrinsics is faster than repeatedly calling the scalar math functions. However, the intrinsics differ from the scalar functions in accuracy.

### Note

Many routines in the Short Vector Math Library (SVML) are more optimized for Intel® microprocessors than for non-Intel microprocessors.

This section also includes information about 512-bit intrinsics for SVML.

Parent topic: Intrinsics

- Intrinsics for Division Operations (512-bit)
- Intrinsics for Division Operations
- Intrinsics for Error Function Operations (512-bit)
- Intrinsics for Error Function Operations
- Intrinsics for Exponential Operations (512-bit)
- Intrinsics for Exponential Operations
- Intrinsics for Logarithmic Operations (512-bit)
- Intrinsics for Logarithmic Operations
- Intrinsics for Reciprocal Operations (512-bit)
- Intrinsics for Root Function Operations (512-bit)
- Intrinsics for Rounding Operations (512-bit)
- Intrinsics for Square Root and Cube Root Operations
- Intrinsics for Trigonometric Operations (512-bit)
- Intrinsics for Trigonometric Operations