Current personal computer CPUs have the capability for up to four times faster single precision floating point calculations when utilizing SSE instructions. Unfortunately, the learning curve is high and good documentation on the subject is scarce. In fact, most I could find was endless reference manuals listing available instructions and short tutorials, but little discussion on SSE and generally SIMD design concerns. Exception to this was Intel's optimization reference manual, but it is very low level in nature. The examples are mostly in x86. Additionally, Intel's manual is not in liberty to unbiasedly discuss SSE's weak and strong points as it must help to sell CPUs.
The very first problem with SSE is how access the instructions without resorting to writing x86 assembly. To this end, some C/C++ compilers come with so called SSE intrinsics headers. These provide a set of C functions, which give almost direct access to the vectorized instructions and the needed packaged data types. Unfortunately, coding with the C intrinsics is very inconvenient and results in unreadable code. I present a case here, that this can be solved with C++ operator overloading capabilities without sacrificing performance. Additionally, each version of SSE is accessed by a different intrinsics header and the correct selection and detection should be handled by the wrapping C++ class.
The second problem is that converting algorithms to effectively
use even width four SIMD, as used by SSE, is at most times a very nontrivial task. In fact, depending on the problem domain, not infrequently vectorization is not
worth the trouble versus the possible benefit. However, in some cases it is the
difference between rendering an image 60 frames per second versus 15
frames per second or running a scientific calculation in a week instead of a month.
This guide addresses both of the above mentioned problems. Several algorithms will be transformed into SIMD design and the arising practical difficulties will be discussed. A convenient way to access the SSE extensions with the C++ operator overloading capabilities will be demonstrated. Performance benefits will be determined by benchmarking and evaluating the compiler's instruction output.