STYLE REQUIREMENTS ================== 1. Most code in this sub-directory is expected to be upstreamed into glibc so the GNU Coding Standard and glibc specific conventions should be followed to ease upstreaming. 2. ABI and symbols: the code should be written so it is suitable for inclusion into a libc with minimal changes. This e.g. means that internal symbols should be hidden and in the implementation reserved namespace according to ISO C and POSIX rules. If possible the built shared libraries and static library archives should be usable to override libc symbols at link time (or at runtime via LD_PRELOAD). This requires the symbols to follow the glibc ABI (other than symbol versioning), this cannot be done reliably for static linking so this is a best effort requirement. 3. API: include headers should be suitable for benchmarking and testing code and should not conflict with libc headers. CONTRIBUTION GUIDELINES FOR math SUB-DIRECTORY ============================================== 1. Math functions have quality and performance requirements. 2. Quality: - Worst-case ULP error should be small in the entire input domain (for most common double precision scalar functions the target is < 0.66 ULP error, and < 1 ULP for single precision, even performance optimized function variant should not have > 5 ULP error if the goal is to be a drop in replacement for a standard math function), this should be tested statistically (or on all inputs if possible in reasonable amount of time). The ulp tool is for this and runulp.sh should be updated for new functions. - All standard rounding modes need to be supported but in non-default rounding modes the quality requirement can be relaxed. (Non-nearest rounded computation can be slow and inaccurate but has to be correct for conformance reasons.) - Special cases and error handling need to follow ISO C Annex F requirements, POSIX requirements, IEEE 754-2008 requirements and Glibc requiremnts: https://www.gnu.org/software/libc/manual/html_mono/libc.html#Errors-in-Math-Functions this should be tested by direct tests (glibc test system may be used for it). - Error handling code should be decoupled from the approximation code as much as possible. (There are helper functions, these take care of errno as well as exception raising.) - Vector math code does not need to work in non-nearest rounding mode and error handling side effects need not happen (fenv exceptions and errno), but the result should be correct (within quality requirements, which are lower for vector code than for scalar code). - Error bounds of the approximation should be clearly documented. - The code should build and pass tests on arm, aarch64 and x86_64 GNU linux systems. (Routines and features can be disabled on specific targets, but the build must complete). On aarch64, both little- and big-endian targets are supported as well as valid combinations of architecture extensions. The configurations that should be tested depend on the contribution. 3. Performance: - Common math code should be benchmarked on modern aarch64 microarchitectures over typical inputs. - Performance improvements should be documented (relative numbers can be published; it is enough to use the mathbench microbenchmark tool which should be updated for new functions). - Attention should be paid to the compilation flags: for aarch64 fma contraction should be on and math errno turned off so some builtins can be inlined. - The code should be reasonably performant on x86_64 too, e.g. some rounding instructions and fma may not be available on x86_64, such builtins turn into libc calls with slow code. Such slowdown is not acceptable, a faster fallback should be present: glibc and bionic use the same code on all targets. (This does not apply to vector math code).