394ocs-000Jocs-000J.xmlSingle Instruction Multiple Vector (SIMD) › Vector intrinsicsIntrinsics appear like regular libary functions. You include the relevant header, and then you can use it just like any other lib. E.g. assuming a visual c++ compiler, if you wanted to add four float numbers to another four numbers, you would include the xmmintrin.h header which contains the following declaration for the _mm_add_ps intrinsic:However unlike lib functions, intrinsics are implemented directly in compilers. The example SSE intrinsic typically compiles to a single instruction, x86 and amd64 instructions. For the time it takes CPU to call a library function, it might have completed dozen of these functions.For all x86 the current best practice is to use <immintrin.h> which loads in the the correct compatible instruction set. __MMX__ -- X86 MMX :: mmintrin.h __SSE__ -- X86 SSE :: xmmintrin.h __SSE2__ -- X86 SSE2 :: emmintrin.h __VEC__ -- altivec functions :: altivec.h __ARM_NEON__ -- ARM Neon functions :: arm_neon.h Operation Altivec Neon MMX/SSE/SSE2 loading vec_ld vld1q_f32 _mm_set_epi16 vector vec_splat vld1q_s16 _mm_set1_epi16 vec_splat_s16 vsetq_lane_f32 _mm_set1_pi16 vec_splat_s32 vld1_u8 _mm_set_pi16 vec_splat_s8 vdupq_lane_s16 _mm_load_ps vec_splat_u16 vdupq_n_s16 _mm_set1_ps vec_splat_u32 vmovq_n_f32 _mm_loadh_pi vec_splat_u8 vset_lane_u8 _mm_loadl_pi storing vec_st vst1_u8 vector vst1q_s16 _mm_store_ps vst1q_f32 vst1_s16 add vec_madd vaddq_s16 _mm_add_epi16 vec_mladd vaddq_f32 _mm_add_pi16 vec_adds vmlaq_n_f32 _mm_add_ps subtract vec_sub vsubq_s16 multiply vec_madd vmulq_n_s16 _mm_mullo_epi16 vec_mladd vmulq_s16 _mm_mullo_pi16 vmulq_f32 _mm_mul_ps vmlaq_n_f32 arithmetic vec_sra vshrq_n_s16 _mm_srai_epi16 shift vec_srl _mm_srai_pi16 vec_sr byte vec_perm vtbl1_u8 _mm_shuffle_pi16 permutation vec_sel vtbx1_u8 _mm_shuffle_ps vec_mergeh vget_high_s16 vec_mergel vget_low_s16 vdupq_lane_s16 vdupq_n_s16 vmovq_n_f32 vbsl_u8 type vec_cts vmovl_u8 _mm_packs_pu16 conversion vec_unpackh vreinterpretq_s16_u16 vec_unpackl vcvtq_u32_f32 vec_cts vqmovn_s32 _mm_cvtps_pi16 vec_ctu vqmovun_s16 _mm_packus_epi16 vqmovn_u16 vcvtq_f32_s32 vmovl_s16 vmovq_n_f32 vector vec_pack vcombine_u16 combination vec_packsu vcombine_u8 vcombine_s16 maximum _mm_max_ps minimum _mm_min_ps vector _mm_andnot_ps logic _mm_and_ps _mm_or_ps rounding vec_trunc misc _mm_empty Context395ocs-0009ocs-0009.xmlSingle Instruction Multiple Vector (SIMD)Note2025320Single vector instruction sets are extensions to the original architecture instruction sets, and thus you have to invest extra effort to use and support them. With compiled code, you need to write inline assembly, or use vector intrinsics.255ocs-000Jocs-000J.xmlVector intrinsicsIntrinsics appear like regular libary functions. You include the relevant header, and then you can use it just like any other lib. E.g. assuming a visual c++ compiler, if you wanted to add four float numbers to another four numbers, you would include the xmmintrin.h header which contains the following declaration for the _mm_add_ps intrinsic:However unlike lib functions, intrinsics are implemented directly in compilers. The example SSE intrinsic typically compiles to a single instruction, x86 and amd64 instructions. For the time it takes CPU to call a library function, it might have completed dozen of these functions.For all x86 the current best practice is to use <immintrin.h> which loads in the the correct compatible instruction set. __MMX__ -- X86 MMX :: mmintrin.h __SSE__ -- X86 SSE :: xmmintrin.h __SSE2__ -- X86 SSE2 :: emmintrin.h __VEC__ -- altivec functions :: altivec.h __ARM_NEON__ -- ARM Neon functions :: arm_neon.h Operation Altivec Neon MMX/SSE/SSE2 loading vec_ld vld1q_f32 _mm_set_epi16 vector vec_splat vld1q_s16 _mm_set1_epi16 vec_splat_s16 vsetq_lane_f32 _mm_set1_pi16 vec_splat_s32 vld1_u8 _mm_set_pi16 vec_splat_s8 vdupq_lane_s16 _mm_load_ps vec_splat_u16 vdupq_n_s16 _mm_set1_ps vec_splat_u32 vmovq_n_f32 _mm_loadh_pi vec_splat_u8 vset_lane_u8 _mm_loadl_pi storing vec_st vst1_u8 vector vst1q_s16 _mm_store_ps vst1q_f32 vst1_s16 add vec_madd vaddq_s16 _mm_add_epi16 vec_mladd vaddq_f32 _mm_add_pi16 vec_adds vmlaq_n_f32 _mm_add_ps subtract vec_sub vsubq_s16 multiply vec_madd vmulq_n_s16 _mm_mullo_epi16 vec_mladd vmulq_s16 _mm_mullo_pi16 vmulq_f32 _mm_mul_ps vmlaq_n_f32 arithmetic vec_sra vshrq_n_s16 _mm_srai_epi16 shift vec_srl _mm_srai_pi16 vec_sr byte vec_perm vtbl1_u8 _mm_shuffle_pi16 permutation vec_sel vtbx1_u8 _mm_shuffle_ps vec_mergeh vget_high_s16 vec_mergel vget_low_s16 vdupq_lane_s16 vdupq_n_s16 vmovq_n_f32 vbsl_u8 type vec_cts vmovl_u8 _mm_packs_pu16 conversion vec_unpackh vreinterpretq_s16_u16 vec_unpackl vcvtq_u32_f32 vec_cts vqmovn_s32 _mm_cvtps_pi16 vec_ctu vqmovun_s16 _mm_packus_epi16 vqmovn_u16 vcvtq_f32_s32 vmovl_s16 vmovq_n_f32 vector vec_pack vcombine_u16 combination vec_packsu vcombine_u8 vcombine_s16 maximum _mm_max_ps minimum _mm_min_ps vector _mm_andnot_ps logic _mm_and_ps _mm_or_ps rounding vec_trunc misc _mm_empty Links Utilizing the other 80% of your system's performance: Starting with Vectorization Improving perf with simd intrinsics in three use cases Basics of SIMD programming SIMD Keyword OpenMP, R, Parallelism SIMD a practical guide Organizing SIMD code - stackoverflow SSE SSE2 and SSE3 for GNU C++ [closed] - stackoverflow SIMD, memory locality, vectorization, and branch point prediction Code in ARM assembly: Rounding and arithmetic (scalar) Comparing SIMD on x86-64 and arm64