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ggml.c
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#include "ggml.h"
#if defined(_MSC_VER) || defined(__MINGW32__)
#include <malloc.h> // using malloc.h with MSC/MINGW
#elif !defined(__FreeBSD__)
#include <alloca.h>
#endif
#include <assert.h>
#include <time.h>
#include <math.h>
#include <stdlib.h>
#include <string.h>
#include <stdint.h>
#include <stdio.h>
// if C99 - static_assert is noop
// ref: https://stackoverflow.com/a/53923785/4039976
#ifndef static_assert
#define static_assert(cond, msg) struct global_scope_noop_trick
#endif
#if defined _MSC_VER || defined(__MINGW32__)
#if !defined(__MINGW32__)
#include <Windows.h>
#else
// ref: https://github.com/ggerganov/whisper.cpp/issues/168
#include <windows.h>
#include <errno.h>
#endif
typedef volatile LONG atomic_int;
typedef atomic_int atomic_bool;
static void atomic_store(atomic_int* ptr, LONG val) {
InterlockedExchange(ptr, val);
}
static LONG atomic_load(atomic_int* ptr) {
return InterlockedCompareExchange(ptr, 0, 0);
}
static LONG atomic_fetch_add(atomic_int* ptr, LONG inc) {
return InterlockedExchangeAdd(ptr, inc);
}
static LONG atomic_fetch_sub(atomic_int* ptr, LONG dec) {
return atomic_fetch_add(ptr, -(dec));
}
typedef HANDLE pthread_t;
typedef DWORD thread_ret_t;
static int pthread_create(pthread_t* out, void* unused, thread_ret_t(*func)(void*), void* arg) {
HANDLE handle = CreateThread(NULL, 0, (LPTHREAD_START_ROUTINE) func, arg, 0, NULL);
if (handle == NULL)
{
return EAGAIN;
}
*out = handle;
return 0;
}
static int pthread_join(pthread_t thread, void* unused) {
return (int) WaitForSingleObject(thread, INFINITE);
}
static int sched_yield (void) {
Sleep (0);
return 0;
}
#else
#include <pthread.h>
#include <stdatomic.h>
typedef void* thread_ret_t;
#endif
#ifdef __HAIKU__
#define static_assert(cond, msg) _Static_assert(cond, msg)
#endif
#define GGML_DEBUG 0
#define GGML_GELU_FP16
#if UINTPTR_MAX == 0xFFFFFFFF
#define GGML_MEM_ALIGN 4
#else
#define GGML_MEM_ALIGN 16
#endif
#define MAX(a, b) ((a) > (b) ? (a) : (b))
#define MIN(a, b) ((a) < (b) ? (a) : (b))
#define UNUSED(x) (void)(x)
#define SWAP(x, y, T) do { T SWAP = x; x = y; y = SWAP; } while (0)
#define GGML_ASSERT(x) \
do { \
if (!(x)) { \
fprintf(stderr, "GGML_ASSERT: %s:%d: %s\n", __FILE__, __LINE__, #x); \
abort(); \
} \
} while (0)
#ifdef GGML_USE_ACCELERATE
#include <Accelerate/Accelerate.h>
#elif GGML_USE_OPENBLAS
#include <cblas.h>
#endif
// floating point type used to accumulate sums
typedef double ggml_float;
// 16-bit float
// on Arm, we use __fp16
// on x86, we use uint16_t
#ifdef __ARM_NEON
// if YCM cannot find <arm_neon.h>, make a symbolic link to it, for example:
//
// $ ln -sfn /Library/Developer/CommandLineTools/usr/lib/clang/13.1.6/include/arm_neon.h ./src/
//
#include <arm_neon.h>
float ggml_fp16_to_fp32(ggml_fp16_t x) {
return x;
}
ggml_fp16_t ggml_fp32_to_fp16(float x) {
return x;
}
#define GGML_FP16_TO_FP32(x) (x)
#define GGML_FP32_TO_FP16(x) (x)
#else
#ifdef __wasm_simd128__
#include <wasm_simd128.h>
#else
#ifdef __POWER9_VECTOR__
#include <altivec.h>
#undef bool
#define bool _Bool
#else
#include <immintrin.h>
#endif
#endif
#ifdef __F16C__
float ggml_fp16_to_fp32(ggml_fp16_t h) {
return _cvtsh_ss(h);
}
ggml_fp16_t ggml_fp32_to_fp16(float f) {
return _cvtss_sh(f, 0);
}
#define GGML_FP16_TO_FP32(x) _cvtsh_ss(x)
#define GGML_FP32_TO_FP16(x) _cvtss_sh(x, 0)
#else
// FP16 <-> FP32
// ref: https://github.com/Maratyszcza/FP16
static inline float fp32_from_bits(uint32_t w) {
union {
uint32_t as_bits;
float as_value;
} fp32;
fp32.as_bits = w;
return fp32.as_value;
}
static inline uint32_t fp32_to_bits(float f) {
union {
float as_value;
uint32_t as_bits;
} fp32;
fp32.as_value = f;
return fp32.as_bits;
}
float ggml_fp16_to_fp32(ggml_fp16_t h) {
const uint32_t w = (uint32_t) h << 16;
const uint32_t sign = w & UINT32_C(0x80000000);
const uint32_t two_w = w + w;
const uint32_t exp_offset = UINT32_C(0xE0) << 23;
#if defined(__STDC_VERSION__) && (__STDC_VERSION__ >= 199901L) || defined(__GNUC__) && !defined(__STRICT_ANSI__)
const float exp_scale = 0x1.0p-112f;
#else
const float exp_scale = fp32_from_bits(UINT32_C(0x7800000));
#endif
const float normalized_value = fp32_from_bits((two_w >> 4) + exp_offset) * exp_scale;
const uint32_t magic_mask = UINT32_C(126) << 23;
const float magic_bias = 0.5f;
const float denormalized_value = fp32_from_bits((two_w >> 17) | magic_mask) - magic_bias;
const uint32_t denormalized_cutoff = UINT32_C(1) << 27;
const uint32_t result = sign |
(two_w < denormalized_cutoff ? fp32_to_bits(denormalized_value) : fp32_to_bits(normalized_value));
return fp32_from_bits(result);
}
ggml_fp16_t ggml_fp32_to_fp16(float f) {
#if defined(__STDC_VERSION__) && (__STDC_VERSION__ >= 199901L) || defined(__GNUC__) && !defined(__STRICT_ANSI__)
const float scale_to_inf = 0x1.0p+112f;
const float scale_to_zero = 0x1.0p-110f;
#else
const float scale_to_inf = fp32_from_bits(UINT32_C(0x77800000));
const float scale_to_zero = fp32_from_bits(UINT32_C(0x08800000));
#endif
float base = (fabsf(f) * scale_to_inf) * scale_to_zero;
const uint32_t w = fp32_to_bits(f);
const uint32_t shl1_w = w + w;
const uint32_t sign = w & UINT32_C(0x80000000);
uint32_t bias = shl1_w & UINT32_C(0xFF000000);
if (bias < UINT32_C(0x71000000)) {
bias = UINT32_C(0x71000000);
}
base = fp32_from_bits((bias >> 1) + UINT32_C(0x07800000)) + base;
const uint32_t bits = fp32_to_bits(base);
const uint32_t exp_bits = (bits >> 13) & UINT32_C(0x00007C00);
const uint32_t mantissa_bits = bits & UINT32_C(0x00000FFF);
const uint32_t nonsign = exp_bits + mantissa_bits;
return (sign >> 16) | (shl1_w > UINT32_C(0xFF000000) ? UINT16_C(0x7E00) : nonsign);
}
#define GGML_FP16_TO_FP32(x) ggml_fp16_to_fp32(x)
#define GGML_FP32_TO_FP16(x) ggml_fp32_to_fp16(x)
#endif // __F16C__
#endif // __ARM_NEON
//
// global data
//
// precomputed gelu table for f16 (128 KB)
static ggml_fp16_t table_gelu_f16[1 << 16];
// precomputed exp table for f16 (128 KB)
static ggml_fp16_t table_exp_f16[1 << 16];
//
// timing
//
#if defined(_MSC_VER) || defined(__MINGW32__)
static int64_t timer_freq;
void ggml_time_init(void) {
LARGE_INTEGER frequency;
QueryPerformanceFrequency(&frequency);
timer_freq = frequency.QuadPart;
}
int64_t ggml_time_ms(void) {
LARGE_INTEGER t;
QueryPerformanceCounter(&t);
return (t.QuadPart * 1000) / timer_freq;
}
int64_t ggml_time_us(void) {
LARGE_INTEGER t;
QueryPerformanceCounter(&t);
return (t.QuadPart * 1000000) / timer_freq;
}
#else
void ggml_time_init(void) {}
int64_t ggml_time_ms(void) {
struct timespec ts;
clock_gettime(CLOCK_MONOTONIC, &ts);
return (int64_t)ts.tv_sec*1000 + (int64_t)ts.tv_nsec/1000000;
}
int64_t ggml_time_us(void) {
struct timespec ts;
clock_gettime(CLOCK_MONOTONIC, &ts);
return (int64_t)ts.tv_sec*1000000 + (int64_t)ts.tv_nsec/1000;
}
#endif
int64_t ggml_cycles(void) {
return clock();
}
int64_t ggml_cycles_per_ms(void) {
return CLOCKS_PER_SEC/1000;
}
#ifdef GGML_PERF
#define ggml_perf_time_ms() ggml_time_ms()
#define ggml_perf_time_us() ggml_time_us()
#define ggml_perf_cycles() ggml_cycles()
#define ggml_perf_cycles_per_ms() ggml_cycles_per_ms()
#else
#define ggml_perf_time_ms() 0
#define ggml_perf_time_us() 0
#define ggml_perf_cycles() 0
#define ggml_perf_cycles_per_ms() 0
#endif
//
// cache line
//
#if defined(__cpp_lib_hardware_interference_size)
#define CACHE_LINE_SIZE hardware_destructive_interference_size
#else
#define CACHE_LINE_SIZE 64
#endif
static const size_t CACHE_LINE_SIZE_F32 = CACHE_LINE_SIZE/sizeof(float);
//
// simd mappings
//
// we define a common set of C macros which map to specific intrinsics based on the current architecture
// we then implement the fundamental computation operations below using only these macros
// adding support for new architectures requires to define the corresponding SIMD macros
//
// GGML_F32_STEP / GGML_F16_STEP
// number of elements to process in a single step
//
// GGML_F32_EPR / GGML_F16_EPR
// number of elements to fit in a single register
//
#if defined(__ARM_NEON) && defined(__ARM_FEATURE_FMA)
#define GGML_SIMD
// F32 NEON
#define GGML_F32_STEP 16
#define GGML_F32_EPR 4
#define GGML_F32x4 float32x4_t
#define GGML_F32x4_ZERO vdupq_n_f32(0.0f)
#define GGML_F32x4_SET1(x) vdupq_n_f32(x)
#define GGML_F32x4_LOAD vld1q_f32
#define GGML_F32x4_STORE vst1q_f32
#define GGML_F32x4_FMA(a, b, c) vfmaq_f32(a, b, c)
#define GGML_F32x4_ADD vaddq_f32
#define GGML_F32x4_MUL vmulq_f32
#if defined(__ARM_FEATURE_QRDMX)
#define GGML_F32x4_REDUCE_ONE(x) vaddvq_f32(x)
#else
#define GGML_F32x4_REDUCE_ONE(x) \
(vgetq_lane_f32(x, 0) + \
vgetq_lane_f32(x, 1) + \
vgetq_lane_f32(x, 2) + \
vgetq_lane_f32(x, 3))
#endif
#define GGML_F32x4_REDUCE(res, x) \
{ \
for (int i = 0; i < GGML_F32_ARR/2; ++i) { \
x[2*i] = vaddq_f32(x[2*i], x[2*i+1]); \
} \
for (int i = 0; i < GGML_F32_ARR/4; ++i) { \
x[4*i] = vaddq_f32(x[4*i], x[4*i+2]); \
} \
for (int i = 0; i < GGML_F32_ARR/8; ++i) { \
x[8*i] = vaddq_f32(x[8*i], x[8*i+4]); \
} \
res = GGML_F32x4_REDUCE_ONE(x[0]); \
}
#define GGML_F32_VEC GGML_F32x4
#define GGML_F32_VEC_ZERO GGML_F32x4_ZERO
#define GGML_F32_VEC_SET1 GGML_F32x4_SET1
#define GGML_F32_VEC_LOAD GGML_F32x4_LOAD
#define GGML_F32_VEC_STORE GGML_F32x4_STORE
#define GGML_F32_VEC_FMA GGML_F32x4_FMA
#define GGML_F32_VEC_ADD GGML_F32x4_ADD
#define GGML_F32_VEC_MUL GGML_F32x4_MUL
#define GGML_F32_VEC_REDUCE GGML_F32x4_REDUCE
// F16 NEON
#if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC)
#define GGML_F16_STEP 32
#define GGML_F16_EPR 8
#define GGML_F16x8 float16x8_t
#define GGML_F16x8_ZERO vdupq_n_f16(0.0f)
#define GGML_F16x8_SET1(x) vdupq_n_f16(x)
#define GGML_F16x8_LOAD vld1q_f16
#define GGML_F16x8_STORE vst1q_f16
#define GGML_F16x8_FMA(a, b, c) vfmaq_f16(a, b, c)
#define GGML_F16x8_ADD vaddq_f16
#define GGML_F16x8_MUL vmulq_f16
#define GGML_F16x8_REDUCE(res, x) \
{ \
for (int i = 0; i < GGML_F16_ARR/2; ++i) { \
x[2*i] = vaddq_f16(x[2*i], x[2*i+1]); \
} \
for (int i = 0; i < GGML_F16_ARR/4; ++i) { \
x[4*i] = vaddq_f16(x[4*i], x[4*i+2]); \
} \
for (int i = 0; i < GGML_F16_ARR/8; ++i) { \
x[8*i] = vaddq_f16(x[8*i], x[8*i+4]); \
} \
const float32x4_t t0 = vcvt_f32_f16(vget_low_f16 (x[0])); \
const float32x4_t t1 = vcvt_f32_f16(vget_high_f16(x[0])); \
res = vaddvq_f32(vaddq_f32(t0, t1)); \
}
#define GGML_F16_VEC GGML_F16x8
#define GGML_F16_VEC_ZERO GGML_F16x8_ZERO
#define GGML_F16_VEC_SET1 GGML_F16x8_SET1
#define GGML_F16_VEC_LOAD GGML_F16x8_LOAD
#define GGML_F16_VEC_STORE GGML_F16x8_STORE
#define GGML_F16_VEC_FMA GGML_F16x8_FMA
#define GGML_F16_VEC_ADD GGML_F16x8_ADD
#define GGML_F16_VEC_MUL GGML_F16x8_MUL
#define GGML_F16_VEC_REDUCE GGML_F16x8_REDUCE
#else
// if FP16 vector arithmetic is not supported, we use FP32 instead
// and take advantage of the vcvt_ functions to convert to/from FP16
#define GGML_F16_STEP 16
#define GGML_F16_EPR 4
#define GGML_F32Cx4 float32x4_t
#define GGML_F32Cx4_ZERO vdupq_n_f32(0.0f)
#define GGML_F32Cx4_SET1(x) vdupq_n_f32(x)
#define GGML_F32Cx4_LOAD(x) vcvt_f32_f16(vld1_f16(x))
#define GGML_F32Cx4_STORE(x, y) vst1_f16(x, vcvt_f16_f32(y))
#define GGML_F32Cx4_FMA(a, b, c) vfmaq_f32(a, b, c)
#define GGML_F32Cx4_ADD vaddq_f32
#define GGML_F32Cx4_MUL vmulq_f32
#define GGML_F32Cx4_REDUCE GGML_F32x4_REDUCE
#define GGML_F16_VEC GGML_F32Cx4
#define GGML_F16_VEC_ZERO GGML_F32Cx4_ZERO
#define GGML_F16_VEC_SET1 GGML_F32Cx4_SET1
#define GGML_F16_VEC_LOAD GGML_F32Cx4_LOAD
#define GGML_F16_VEC_STORE GGML_F32Cx4_STORE
#define GGML_F16_VEC_FMA GGML_F32Cx4_FMA
#define GGML_F16_VEC_ADD GGML_F32Cx4_ADD
#define GGML_F16_VEC_MUL GGML_F32Cx4_MUL
#define GGML_F16_VEC_REDUCE GGML_F32Cx4_REDUCE
#endif
#elif defined(__AVX__)
#define GGML_SIMD
// F32 AVX
#define GGML_F32_STEP 32
#define GGML_F32_EPR 8
#define GGML_F32x8 __m256
#define GGML_F32x8_ZERO _mm256_setzero_ps()
#define GGML_F32x8_SET1(x) _mm256_set1_ps(x)
#define GGML_F32x8_LOAD _mm256_loadu_ps
#define GGML_F32x8_STORE _mm256_storeu_ps
#if defined(__FMA__)
#define GGML_F32x8_FMA(a, b, c) _mm256_fmadd_ps(b, c, a)
#else
#define GGML_F32x8_FMA(a, b, c) _mm256_add_ps(_mm256_mul_ps(b, c), a)
#endif
#define GGML_F32x8_ADD _mm256_add_ps
#define GGML_F32x8_MUL _mm256_mul_ps
#define GGML_F32x8_REDUCE(res, x) \
{ \
for (int i = 0; i < GGML_F32_ARR/2; ++i) { \
x[2*i] = _mm256_add_ps(x[2*i], x[2*i+1]); \
} \
for (int i = 0; i < GGML_F32_ARR/4; ++i) { \
x[4*i] = _mm256_add_ps(x[4*i], x[4*i+2]); \
} \
for (int i = 0; i < GGML_F32_ARR/8; ++i) { \
x[8*i] = _mm256_add_ps(x[8*i], x[8*i+4]); \
} \
const __m128 t0 = _mm_add_ps(_mm256_castps256_ps128(x[0]), \
_mm256_extractf128_ps(x[0], 1)); \
const __m128 t1 = _mm_hadd_ps(t0, t0); \
res = _mm_cvtss_f32(_mm_hadd_ps(t1, t1)); \
}
// TODO: is this optimal ?
#define GGML_F32_VEC GGML_F32x8
#define GGML_F32_VEC_ZERO GGML_F32x8_ZERO
#define GGML_F32_VEC_SET1 GGML_F32x8_SET1
#define GGML_F32_VEC_LOAD GGML_F32x8_LOAD
#define GGML_F32_VEC_STORE GGML_F32x8_STORE
#define GGML_F32_VEC_FMA GGML_F32x8_FMA
#define GGML_F32_VEC_ADD GGML_F32x8_ADD
#define GGML_F32_VEC_MUL GGML_F32x8_MUL
#define GGML_F32_VEC_REDUCE GGML_F32x8_REDUCE
// F16 AVX
#define GGML_F16_STEP 32
#define GGML_F16_EPR 8
// F16 arithmetic is not supported by AVX, so we use F32 instead
// we take advantage of the _mm256_cvt intrinsics to convert F16 <-> F32
#define GGML_F32Cx8 __m256
#define GGML_F32Cx8_ZERO _mm256_setzero_ps()
#define GGML_F32Cx8_SET1(x) _mm256_set1_ps(x)
#define GGML_F32Cx8_LOAD(x) _mm256_cvtph_ps(_mm_loadu_si128((__m128i *)(x)))
#define GGML_F32Cx8_STORE(x, y) _mm_storeu_si128((__m128i *)(x), _mm256_cvtps_ph(y, 0))
#define GGML_F32Cx8_FMA GGML_F32x8_FMA
#define GGML_F32Cx8_ADD _mm256_add_ps
#define GGML_F32Cx8_MUL _mm256_mul_ps
#define GGML_F32Cx8_REDUCE GGML_F32x8_REDUCE
#define GGML_F16_VEC GGML_F32Cx8
#define GGML_F16_VEC_ZERO GGML_F32Cx8_ZERO
#define GGML_F16_VEC_SET1 GGML_F32Cx8_SET1
#define GGML_F16_VEC_LOAD GGML_F32Cx8_LOAD
#define GGML_F16_VEC_STORE GGML_F32Cx8_STORE
#define GGML_F16_VEC_FMA GGML_F32Cx8_FMA
#define GGML_F16_VEC_ADD GGML_F32Cx8_ADD
#define GGML_F16_VEC_MUL GGML_F32Cx8_MUL
#define GGML_F16_VEC_REDUCE GGML_F32Cx8_REDUCE
#elif defined(__POWER9_VECTOR__)
// TODO: uncomment this when it works
//#define GGML_SIMD
// F32 POWER9
#define GGML_F32_STEP 32
#define GGML_F32_EPR 8
// TODO: not tested !!
#define GGML_F32x4 __vector float
#define GGML_F32x4_ZERO (__vector float){0.0f, 0.0f, 0.0f, 0.0f}
#define GGML_F32x4_SET1(x) (__vector float){x, x, x, x}
#define GGML_F32x4_LOAD vec_vsx_ld
#define GGML_F32x4_STORE vec_vsx_st
#define GGML_F32x4_FMA(a, b, c) vec_madd(b, c, a)
#define GGML_F32x4_ADD vec_add
#define GGML_F32x4_MUL vec_mul
#define GGML_F32x4_REDUCE(res, x) \
{ \
for (int i = 0; i < GGML_F32_ARR/2; ++i) { \
x[2*i] = vec_add(x[2*i], x[2*i+1]); \
} \
for (int i = 0; i < GGML_F32_ARR/4; ++i) { \
x[4*i] = vec_add(x[4*i], x[4*i+2]); \
} \
for (int i = 0; i < GGML_F32_ARR/8; ++i) { \
x[8*i] = vec_add(x[8*i], x[8*i+4]); \
} \
res = vec_extract(x[0], 0) + \
vec_extract(x[0], 1) + \
vec_extract(x[0], 2) + \
vec_extract(x[0], 3); \
}
#define GGML_F32_VEC GGML_F32x4
#define GGML_F32_VEC_ZERO GGML_F32x4_ZERO
#define GGML_F32_VEC_SET1 GGML_F32x4_SET1
#define GGML_F32_VEC_LOAD GGML_F32x4_LOAD
#define GGML_F32_VEC_STORE GGML_F32x4_STORE
#define GGML_F32_VEC_FMA GGML_F32x4_FMA
#define GGML_F32_VEC_ADD GGML_F32x4_ADD
#define GGML_F32_VEC_MUL GGML_F32x4_MUL
#define GGML_F32_VEC_REDUCE GGML_F32x4_REDUCE
// F16 POWER9
// TODO: implement here
// ...
#elif defined(__wasm_simd128__)
#define GGML_SIMD
// F32 WASM
#define GGML_F32_STEP 16
#define GGML_F32_EPR 4
#define GGML_F32x4 v128_t
#define GGML_F32x4_ZERO wasm_f32x4_splat(0.0f)
#define GGML_F32x4_SET1(x) wasm_f32x4_splat(x)
#define GGML_F32x4_LOAD wasm_v128_load
#define GGML_F32x4_STORE wasm_v128_store
#define GGML_F32x4_FMA(a, b, c) wasm_f32x4_add(wasm_f32x4_mul(b, c), a)
#define GGML_F32x4_ADD wasm_f32x4_add
#define GGML_F32x4_MUL wasm_f32x4_mul
#define GGML_F32x4_REDUCE(res, x) \
{ \
for (int i = 0; i < GGML_F32_ARR/2; ++i) { \
x[2*i] = wasm_f32x4_add(x[2*i], x[2*i+1]); \
} \
for (int i = 0; i < GGML_F32_ARR/4; ++i) { \
x[4*i] = wasm_f32x4_add(x[4*i], x[4*i+2]); \
} \
for (int i = 0; i < GGML_F32_ARR/8; ++i) { \
x[8*i] = wasm_f32x4_add(x[8*i], x[8*i+4]); \
} \
res = wasm_f32x4_extract_lane(x[0], 0) + \
wasm_f32x4_extract_lane(x[0], 1) + \
wasm_f32x4_extract_lane(x[0], 2) + \
wasm_f32x4_extract_lane(x[0], 3); \
}
#define GGML_F32_VEC GGML_F32x4
#define GGML_F32_VEC_ZERO GGML_F32x4_ZERO
#define GGML_F32_VEC_SET1 GGML_F32x4_SET1
#define GGML_F32_VEC_LOAD GGML_F32x4_LOAD
#define GGML_F32_VEC_STORE GGML_F32x4_STORE
#define GGML_F32_VEC_FMA GGML_F32x4_FMA
#define GGML_F32_VEC_ADD GGML_F32x4_ADD
#define GGML_F32_VEC_MUL GGML_F32x4_MUL
#define GGML_F32_VEC_REDUCE GGML_F32x4_REDUCE
// F16 WASM
#define GGML_F16_STEP 16
#define GGML_F16_EPR 4
inline static v128_t __wasm_f16x4_load(const ggml_fp16_t * p) {
float tmp[4];
tmp[0] = GGML_FP16_TO_FP32(p[0]);
tmp[1] = GGML_FP16_TO_FP32(p[1]);
tmp[2] = GGML_FP16_TO_FP32(p[2]);
tmp[3] = GGML_FP16_TO_FP32(p[3]);
return wasm_v128_load(tmp);
}
inline static void __wasm_f16x4_store(ggml_fp16_t * p, v128_t x) {
float tmp[4];
wasm_v128_store(tmp, x);
p[0] = GGML_FP32_TO_FP16(tmp[0]);
p[1] = GGML_FP32_TO_FP16(tmp[1]);
p[2] = GGML_FP32_TO_FP16(tmp[2]);
p[3] = GGML_FP32_TO_FP16(tmp[3]);
}
#define GGML_F16x4 v128_t
#define GGML_F16x4_ZERO wasm_f32x4_splat(0.0f)
#define GGML_F16x4_SET1(x) wasm_f32x4_splat(x)
#define GGML_F16x4_LOAD(x) __wasm_f16x4_load(x)
#define GGML_F16x4_STORE(x, y) __wasm_f16x4_store(x, y)
#define GGML_F16x4_FMA GGML_F32x4_FMA
#define GGML_F16x4_ADD wasm_f32x4_add
#define GGML_F16x4_MUL wasm_f32x4_mul
#define GGML_F16x4_REDUCE(res, x) \
{ \
for (int i = 0; i < GGML_F16_ARR/2; ++i) { \
x[2*i] = wasm_f32x4_add(x[2*i], x[2*i+1]); \
} \
for (int i = 0; i < GGML_F16_ARR/4; ++i) { \
x[4*i] = wasm_f32x4_add(x[4*i], x[4*i+2]); \
} \
for (int i = 0; i < GGML_F16_ARR/8; ++i) { \
x[8*i] = wasm_f32x4_add(x[8*i], x[8*i+4]); \
} \
res = wasm_f32x4_extract_lane(x[0], 0) + \
wasm_f32x4_extract_lane(x[0], 1) + \
wasm_f32x4_extract_lane(x[0], 2) + \
wasm_f32x4_extract_lane(x[0], 3); \
}
#define GGML_F16_VEC GGML_F16x4
#define GGML_F16_VEC_ZERO GGML_F16x4_ZERO
#define GGML_F16_VEC_SET1 GGML_F16x4_SET1
#define GGML_F16_VEC_LOAD GGML_F16x4_LOAD
#define GGML_F16_VEC_STORE GGML_F16x4_STORE
#define GGML_F16_VEC_FMA GGML_F16x4_FMA
#define GGML_F16_VEC_ADD GGML_F16x4_ADD
#define GGML_F16_VEC_MUL GGML_F16x4_MUL
#define GGML_F16_VEC_REDUCE GGML_F16x4_REDUCE
#endif
// GGML_F32_ARR / GGML_F16_ARR
// number of registers to use per step
#ifdef GGML_SIMD
#define GGML_F32_ARR (GGML_F32_STEP/GGML_F32_EPR)
#define GGML_F16_ARR (GGML_F16_STEP/GGML_F16_EPR)
#endif
//
// fundamental operations
//
inline static void ggml_vec_set_i8(const int n, int8_t * x, const int8_t v) { for (int i = 0; i < n; ++i) x[i] = v; }
inline static void ggml_vec_set_i16(const int n, int16_t * x, const int16_t v) { for (int i = 0; i < n; ++i) x[i] = v; }
inline static void ggml_vec_set_i32(const int n, int32_t * x, const int32_t v) { for (int i = 0; i < n; ++i) x[i] = v; }
inline static void ggml_vec_set_f16(const int n, ggml_fp16_t * x, const int32_t v) { for (int i = 0; i < n; ++i) x[i] = v; }
inline static void ggml_vec_add_f32 (const int n, float * z, const float * x, const float * y) { for (int i = 0; i < n; ++i) z[i] = x[i] + y[i]; }
inline static void ggml_vec_acc_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] += x[i]; }
inline static void ggml_vec_acc1_f32(const int n, float * y, const float v) { for (int i = 0; i < n; ++i) y[i] += v; }
inline static void ggml_vec_sub_f32 (const int n, float * z, const float * x, const float * y) { for (int i = 0; i < n; ++i) z[i] = x[i] - y[i]; }
inline static void ggml_vec_set_f32 (const int n, float * x, const float v) { for (int i = 0; i < n; ++i) x[i] = v; }
inline static void ggml_vec_cpy_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = x[i]; }
inline static void ggml_vec_neg_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = -x[i]; }
inline static void ggml_vec_mul_f32 (const int n, float * z, const float * x, const float * y) { for (int i = 0; i < n; ++i) z[i] = x[i]*y[i]; }
inline static void ggml_vec_div_f32 (const int n, float * z, const float * x, const float * y) { for (int i = 0; i < n; ++i) z[i] = x[i]/y[i]; }
inline static void ggml_vec_dot_f32(const int n, float * restrict s, const float * restrict x, const float * restrict y) {
ggml_float sumf = 0.0;
#ifdef GGML_SIMD
const int np = (n & ~(GGML_F32_STEP - 1));
GGML_F32_VEC sum[GGML_F32_ARR] = { GGML_F32_VEC_ZERO };
GGML_F32_VEC ax[GGML_F32_ARR];
GGML_F32_VEC ay[GGML_F32_ARR];
for (int i = 0; i < np; i += GGML_F32_STEP) {
for (int j = 0; j < GGML_F32_ARR; j++) {
ax[j] = GGML_F32_VEC_LOAD(x + i + j*GGML_F32_EPR);
ay[j] = GGML_F32_VEC_LOAD(y + i + j*GGML_F32_EPR);
sum[j] = GGML_F32_VEC_FMA(sum[j], ax[j], ay[j]);
}
}
// reduce sum0..sum3 to sum0
GGML_F32_VEC_REDUCE(sumf, sum);
// leftovers
for (int i = np; i < n; ++i) {
sumf += x[i]*y[i];
}
#else
// scalar
for (int i = 0; i < n; ++i) {
sumf += x[i]*y[i];
}
#endif
*s = sumf;
}
inline static void ggml_vec_dot_f16(const int n, float * restrict s, ggml_fp16_t * restrict x, ggml_fp16_t * restrict y) {
ggml_float sumf = 0.0;
#if defined(GGML_SIMD)
const int np = (n & ~(GGML_F16_STEP - 1));
GGML_F16_VEC sum[GGML_F16_ARR] = { GGML_F16_VEC_ZERO };
GGML_F16_VEC ax[GGML_F16_ARR];
GGML_F16_VEC ay[GGML_F16_ARR];
for (int i = 0; i < np; i += GGML_F16_STEP) {
for (int j = 0; j < GGML_F16_ARR; j++) {
ax[j] = GGML_F16_VEC_LOAD(x + i + j*GGML_F16_EPR);
ay[j] = GGML_F16_VEC_LOAD(y + i + j*GGML_F16_EPR);
sum[j] = GGML_F16_VEC_FMA(sum[j], ax[j], ay[j]);
}
}
// reduce sum0..sum3 to sum0
GGML_F16_VEC_REDUCE(sumf, sum);
// leftovers
for (int i = np; i < n; ++i) {
sumf += GGML_FP16_TO_FP32(x[i])*GGML_FP16_TO_FP32(y[i]);
}
#elif defined(__POWER9_VECTOR__)
// TODO: this is temporary because I cannot fit it in the GGML_SIMD pattern like all other architectures without
// being able to test it. hoping someone with access to a POWER9 machine can help out here.
const int n32 = (n & ~31);
vector float sum0 = vec_splats (0.0f);
for (int i = 0; i < n32; i += 32) {
// Use vec_xl, not vec_ld, because x is sometimes unaligned.
vector unsigned short x0 = vec_xl(i * 2 + 0, x);
vector unsigned short x1 = vec_xl(i * 2 + 16, x);
vector unsigned short x2 = vec_xl(i * 2 + 32, x);
vector unsigned short x3 = vec_xl(i * 2 + 48, x);
vector unsigned short y0 = vec_xl(i * 2 + 0, y);
vector unsigned short y1 = vec_xl(i * 2 + 16, y);
vector unsigned short y2 = vec_xl(i * 2 + 32, y);
vector unsigned short y3 = vec_xl(i * 2 + 48, y);
vector float fx0l = vec_extract_fp32_from_shortl(x0);
vector float fx0h = vec_extract_fp32_from_shorth(x0);
vector float fx1l = vec_extract_fp32_from_shortl(x1);
vector float fx1h = vec_extract_fp32_from_shorth(x1);
vector float fx2l = vec_extract_fp32_from_shortl(x2);
vector float fx2h = vec_extract_fp32_from_shorth(x2);
vector float fx3l = vec_extract_fp32_from_shortl(x3);
vector float fx3h = vec_extract_fp32_from_shorth(x3);
vector float fy0l = vec_extract_fp32_from_shortl(y0);
vector float fy0h = vec_extract_fp32_from_shorth(y0);
vector float fy1l = vec_extract_fp32_from_shortl(y1);
vector float fy1h = vec_extract_fp32_from_shorth(y1);
vector float fy2l = vec_extract_fp32_from_shortl(y2);
vector float fy2h = vec_extract_fp32_from_shorth(y2);
vector float fy3l = vec_extract_fp32_from_shortl(y3);
vector float fy3h = vec_extract_fp32_from_shorth(y3);
sum0 = vec_add(sum0, vec_mul(fx0l, fy0l));
sum0 = vec_add(sum0, vec_mul(fx0h, fy0h));
sum0 = vec_add(sum0, vec_mul(fx1l, fy1l));
sum0 = vec_add(sum0, vec_mul(fx1h, fy1h));
sum0 = vec_add(sum0, vec_mul(fx2l, fy2l));
sum0 = vec_add(sum0, vec_mul(fx2h, fy2h));
sum0 = vec_add(sum0, vec_mul(fx3l, fy3l));
sum0 = vec_add(sum0, vec_mul(fx3h, fy3h));
}
sumf = vec_extract(sum0, 0) + vec_extract(sum0, 1)
+ vec_extract(sum0, 2) + vec_extract(sum0, 3);
for (int i = n32; i < n; ++i) {
sumf += GGML_FP16_TO_FP32(x[i])*GGML_FP16_TO_FP32(y[i]);
}
#else
for (int i = 0; i < n; ++i) {
sumf += GGML_FP16_TO_FP32(x[i])*GGML_FP16_TO_FP32(y[i]);
}
#endif
*s = sumf;
}
inline static void ggml_vec_mad_f32(const int n, float * restrict y, const float * restrict x, const float v) {
#if defined(GGML_SIMD)
const int np = (n & ~(GGML_F32_STEP - 1));
GGML_F32_VEC vx = GGML_F32_VEC_SET1(v);
GGML_F32_VEC ax[GGML_F32_ARR];
GGML_F32_VEC ay[GGML_F32_ARR];
for (int i = 0; i < np; i += GGML_F32_STEP) {
for (int j = 0; j < GGML_F32_ARR; j++) {
ax[j] = GGML_F32_VEC_LOAD(x + i + j*GGML_F32_EPR);
ay[j] = GGML_F32_VEC_LOAD(y + i + j*GGML_F32_EPR);
ay[j] = GGML_F32_VEC_FMA(ay[j], ax[j], vx);
GGML_F32_VEC_STORE(y + i + j*GGML_F32_EPR, ay[j]);
}
}
// leftovers
for (int i = np; i < n; ++i) {
y[i] += x[i]*v;
}
#else
// scalar
for (int i = 0; i < n; ++i) {
y[i] += x[i]*v;
}
#endif
}
inline static void ggml_vec_mad_f16(const int n, ggml_fp16_t * restrict y, ggml_fp16_t * restrict x, const float v) {
#if defined(GGML_SIMD)
const int np = (n & ~(GGML_F16_STEP - 1));
GGML_F16_VEC vx = GGML_F16_VEC_SET1(v);
GGML_F16_VEC ax[GGML_F16_ARR];
GGML_F16_VEC ay[GGML_F16_ARR];
for (int i = 0; i < np; i += GGML_F16_STEP) {
for (int j = 0; j < GGML_F16_ARR; j++) {
ax[j] = GGML_F16_VEC_LOAD(x + i + j*GGML_F16_EPR);
ay[j] = GGML_F16_VEC_LOAD(y + i + j*GGML_F16_EPR);
ay[j] = GGML_F16_VEC_FMA(ay[j], ax[j], vx);
GGML_F16_VEC_STORE(y + i + j*GGML_F16_EPR, ay[j]);
}
}
// leftovers
for (int i = np; i < n; ++i) {
GGML_ASSERT(false);
y[i] = GGML_FP32_TO_FP16(GGML_FP16_TO_FP32(y[i]) + GGML_FP16_TO_FP32(x[i])*v);
}
#elif defined(__POWER9_VECTOR__)
// TODO: this is temporary because I cannot fit it in the GGML_SIMD pattern like all other architectures without
// being able to test it. hoping someone with access to a POWER9 machine can help out here.
const int n32 = (n & ~31);
for (int i = 0; i < n32; i += 32) {
// Use vec_xl, not vec_ld, because x is sometimes unaligned!
vector unsigned short x0 = vec_xl(i * 2 + 0, x);
vector unsigned short x1 = vec_xl(i * 2 + 16, x);
vector unsigned short x2 = vec_xl(i * 2 + 32, x);
vector unsigned short x3 = vec_xl(i * 2 + 48, x);
vector unsigned short y0 = vec_xl(i * 2 + 0, y);
vector unsigned short y1 = vec_xl(i * 2 + 16, y);
vector unsigned short y2 = vec_xl(i * 2 + 32, y);
vector unsigned short y3 = vec_xl(i * 2 + 48, y);
vector float v4 = vec_splats(v);
vector float fx0l = vec_extract_fp32_from_shortl(x0);
vector float fx0h = vec_extract_fp32_from_shorth(x0);
vector float fx1l = vec_extract_fp32_from_shortl(x1);
vector float fx1h = vec_extract_fp32_from_shorth(x1);
vector float fx2l = vec_extract_fp32_from_shortl(x2);
vector float fx2h = vec_extract_fp32_from_shorth(x2);
vector float fx3l = vec_extract_fp32_from_shortl(x3);
vector float fx3h = vec_extract_fp32_from_shorth(x3);
vector float fy0l = vec_extract_fp32_from_shortl(y0);
vector float fy0h = vec_extract_fp32_from_shorth(y0);
vector float fy1l = vec_extract_fp32_from_shortl(y1);
vector float fy1h = vec_extract_fp32_from_shorth(y1);
vector float fy2l = vec_extract_fp32_from_shortl(y2);
vector float fy2h = vec_extract_fp32_from_shorth(y2);
vector float fy3l = vec_extract_fp32_from_shortl(y3);
vector float fy3h = vec_extract_fp32_from_shorth(y3);
fy0l = vec_madd(fx0l, v4, fy0l);
fy0h = vec_madd(fx0h, v4, fy0h);
fy1l = vec_madd(fx1l, v4, fy1l);
fy1h = vec_madd(fx1h, v4, fy1h);
fy2l = vec_madd(fx2l, v4, fy2l);
fy2h = vec_madd(fx2h, v4, fy2h);
fy3l = vec_madd(fx3l, v4, fy3l);
fy3h = vec_madd(fx3h, v4, fy3h);
y0 = vec_pack_to_short_fp32(fy0h, fy0l);
y1 = vec_pack_to_short_fp32(fy1h, fy1l);
y2 = vec_pack_to_short_fp32(fy2h, fy2l);
y3 = vec_pack_to_short_fp32(fy3h, fy3l);
vec_xst(y0, i * 2 + 0, y);
vec_xst(y1, i * 2 + 16, y);
vec_xst(y2, i * 2 + 32, y);
vec_xst(y3, i * 2 + 48, y);
}
for (int i = n32; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(GGML_FP16_TO_FP32(y[i]) + GGML_FP16_TO_FP32(x[i])*v);
}
#else
for (int i = 0; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(GGML_FP16_TO_FP32(y[i]) + GGML_FP16_TO_FP32(x[i])*v);
}
#endif
}
//inline static void ggml_vec_scale_f32(const int n, float * y, const float v) { for (int i = 0; i < n; ++i) y[i] *= v; }
inline static void ggml_vec_scale_f32(const int n, float * y, const float v) {
#if defined(GGML_SIMD)
const int np = (n & ~(GGML_F32_STEP - 1));
GGML_F32_VEC vx = GGML_F32_VEC_SET1(v);
GGML_F32_VEC ay[GGML_F32_ARR];
for (int i = 0; i < np; i += GGML_F32_STEP) {
for (int j = 0; j < GGML_F32_ARR; j++) {
ay[j] = GGML_F32_VEC_LOAD(y + i + j*GGML_F32_EPR);
ay[j] = GGML_F32_VEC_MUL(ay[j], vx);
GGML_F32_VEC_STORE(y + i + j*GGML_F32_EPR, ay[j]);
}
}
// leftovers
for (int i = np; i < n; ++i) {
y[i] *= v;
}
#else
// scalar
for (int i = 0; i < n; ++i) {
y[i] *= v;
}
#endif
}
inline static void ggml_vec_norm_f32 (const int n, float * s, const float * x) { ggml_vec_dot_f32(n, s, x, x); *s = sqrt(*s); }
inline static void ggml_vec_sqr_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = x[i]*x[i]; }
inline static void ggml_vec_sqrt_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = sqrt(x[i]); }
inline static void ggml_vec_abs_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = fabsf(x[i]); }
inline static void ggml_vec_sgn_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = (x[i] > 0.f) ? 1.f : ((x[i] < 0.f) ? -1.f : 0.f); }
inline static void ggml_vec_step_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = (x[i] > 0.f) ? 1.f : 0.f; }
inline static void ggml_vec_relu_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = (x[i] > 0.f) ? x[i] : 0.f; }
static const ggml_float GELU_COEF_A = 0.044715;
static const ggml_float SQRT_2_OVER_PI = 0.79788456080286535587989211986876;