The intrinsics are available via a header that is standardized by Interfacing with the rest of the program requires some Using inline or even an external assembler is ok - but The GCC vector extension syntax seems to be mainly focused onĪrithmetic operations and some useful operations are lacking. The different vector extension on different architectures to The idea of the vector extensions is to abstract away With GCC there are few alternatives how to use those SIMD instructions: Although, some instructions might perform better withĪligned data (as documented) this isn't the general rule. Which simplifies its usage and enables more use cases, in Some older SIMD extension it has relaxed alignment requirements, that 32Ĭharacters can be packed into one register. It features registers of 256 bit width, i.e. Intel has to offer on many of its CPUs - e.g. The AVX2 extension is a relatively recent SIMD implementation We see that the compiler doesn't directly inline the memchr() call but justĬalls the version from glibc. Including auto-vectorization, thus, perhaps a naiveįind_memchr ( char const *, char const *, char ): pushq %rbx movq %rsi, %rbx movl %edx, %esi movq %rbx, %rdx movsbl %sil, %esi subq %rdi, %rdx call memchr testq %rax, %rax cmove %rbx, %rax popq %rbx ret Modern compilers include sophisticated loop optimizations Doesn't a compiler optimize a naive loop on its own? ¶ Runs 1 second or so faster than the 4 times unrolled find_find Unrolling is really the best we can do with respect to unrolling.įor this benchmark, on the Intel i7, the sweet spot is indeed an Taking this result into account, we may question if 4 times this version is 9 percent slower than the naive This unroll factor turns out to be sub-optimal on the _attribute_((optimize("unroll-loops"))) - cf.įind_unroll_), the GCC automatically unrolls the loop 8 Update (): When compiling the naive implementation Specialization for random-access iterators. Just one implementation that uses a simple loop, i.e. Update (): Interestingly, the LLVM libc++ĭoesn't implement any specializations for std::find(). This optimization is promising because on a super-scalarĪrchitecture, multiple statements might be executed The fall-through switch-case statement that deals with the last The 8 return statements are a consequence of that and Instructions are a direct result of having 4 if statements in the This example is a minimal version of a real parser that doesĮnough to see differences in implementation details of a Let's see which of those expectations are actually met. It is also possible that the compiler directly inlines memchr() calls with an optimized implementation. In fact, std::find() could even just call memchr() for a Again, if available one that uses SIMD instructions. Similarly, one expects that the libc implementation of memchr()ĭoes runtime dispatching based on the available CPUĮxtensions (and perhaps the search range size) and uses a specialized Multiple data) vector instructions, where available. For example, one that uses SIMD (single instruction Searching a range of char elements we expect a specialized Iterators but if we use - say - random access iterators for ForĮxample, the minimum requirement for the range are input Highly optimized and specialized for different arguments. Like with other STL algorithms one expects that std::find() is Doesn't a compiler optimize a naive loop on its own?.
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