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ggml.c
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ggml.c
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#define _CRT_SECURE_NO_DEPRECATE // Disables ridiculous "unsafe" warnigns on Windows
#define _USE_MATH_DEFINES // For M_PI on MSVC
#include "ggml-impl.h"
#include "ggml-quants.h"
#if defined(_MSC_VER) || defined(__MINGW32__)
#include <malloc.h> // using malloc.h with MSC/MINGW
#elif !defined(__FreeBSD__) && !defined(__NetBSD__) && !defined(__OpenBSD__)
#include <alloca.h>
#endif
#include <assert.h>
#include <errno.h>
#include <time.h>
#include <math.h>
#include <stdlib.h>
#include <string.h>
#include <stdint.h>
#include <inttypes.h>
#include <stdio.h>
#include <float.h>
#include <limits.h>
#include <stdarg.h>
#include <signal.h>
#ifdef GGML_USE_METAL
#include <unistd.h>
#endif
#if defined(_MSC_VER)
// disable "possible loss of data" to avoid hundreds of casts
// we should just be careful :)
#pragma warning(disable: 4244 4267)
// disable POSIX deprecation warnigns
// these functions are never going away, anyway
#pragma warning(disable: 4996)
#endif
#if defined(_WIN32)
#include <windows.h>
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) {
(void) unused;
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) {
(void) unused;
int ret = (int) WaitForSingleObject(thread, INFINITE);
CloseHandle(thread);
return ret;
}
static int sched_yield (void) {
Sleep (0);
return 0;
}
#else
#include <pthread.h>
#include <stdatomic.h>
typedef void * thread_ret_t;
#include <sys/types.h>
#include <sys/stat.h>
#include <unistd.h>
#endif
#ifdef GGML_USE_CPU_HBM
#include <hbwmalloc.h>
#endif
#if defined(__APPLE__)
#include <TargetConditionals.h>
#endif
#if (defined(__linux__) || defined(__APPLE__) || defined(__FreeBSD__) || defined(__NetBSD__) || defined(__OpenBSD__)) && \
(!defined(TARGET_OS_TV) && !defined(TARGET_OS_WATCH))
#include <sys/wait.h>
void ggml_print_backtrace(void) {
/*
#include <execinfo.h>
#include <dlfcn.h>
void * trace[100];
int nptrs = backtrace(trace, sizeof(trace)/sizeof(trace[0]));
backtrace_symbols_fd(trace, nptrs, STDERR_FILENO);
*/
// backtrack_symbols does not show line numbers, use gdb instead
char attach[32];
snprintf(attach, sizeof(attach), "attach %d", getpid());
int pid = fork();
if (pid == 0) {
execlp("gdb", "gdb", "--batch",
"-ex", "set style enabled on",
"-ex", attach,
"-ex", "bt -frame-info source-and-location",
"-ex", "detach",
"-ex", "quit",
NULL);
} else {
waitpid(pid, NULL, 0);
}
}
#else
void ggml_print_backtrace(void) {
// platform not supported
}
#endif
/*#define GGML_PERF*/
#define GGML_DEBUG 0
#define GGML_GELU_FP16
#define GGML_GELU_QUICK_FP16
#define GGML_SILU_FP16
// #define GGML_CROSS_ENTROPY_EXP_FP16
// #define GGML_FLASH_ATTN_EXP_FP16
#define GGML_SOFT_MAX_UNROLL 4
#define GGML_VEC_DOT_UNROLL 2
#define GGML_VEC_MAD_UNROLL 32
//
// logging
//
#if (GGML_DEBUG >= 1)
#define GGML_PRINT_DEBUG(...) printf(__VA_ARGS__)
#else
#define GGML_PRINT_DEBUG(...)
#endif
#if (GGML_DEBUG >= 5)
#define GGML_PRINT_DEBUG_5(...) printf(__VA_ARGS__)
#else
#define GGML_PRINT_DEBUG_5(...)
#endif
#if (GGML_DEBUG >= 10)
#define GGML_PRINT_DEBUG_10(...) printf(__VA_ARGS__)
#else
#define GGML_PRINT_DEBUG_10(...)
#endif
#define GGML_PRINT(...) printf(__VA_ARGS__)
//
// end of logging block
//
#ifdef GGML_USE_ACCELERATE
// uncomment to use vDSP for soft max computation
// note: not sure if it is actually faster
//#define GGML_SOFT_MAX_ACCELERATE
#endif
#if defined(_MSC_VER) || defined(__MINGW32__)
#define GGML_ALIGNED_MALLOC(size) _aligned_malloc(size, GGML_MEM_ALIGN)
#define GGML_ALIGNED_FREE(ptr) _aligned_free(ptr)
#else
inline static void * ggml_aligned_malloc(size_t size) {
if (size == 0) {
GGML_PRINT("WARNING: Behavior may be unexpected when allocating 0 bytes for ggml_aligned_malloc!\n");
return NULL;
}
void * aligned_memory = NULL;
#ifdef GGML_USE_CPU_HBM
int result = hbw_posix_memalign(&aligned_memory, 16, size);
#elif GGML_USE_METAL
int result = posix_memalign(&aligned_memory, sysconf(_SC_PAGESIZE), size);
#else
int result = posix_memalign(&aligned_memory, GGML_MEM_ALIGN, size);
#endif
if (result != 0) {
// Handle allocation failure
const char *error_desc = "unknown allocation error";
switch (result) {
case EINVAL:
error_desc = "invalid alignment value";
break;
case ENOMEM:
error_desc = "insufficient memory";
break;
}
GGML_PRINT("%s: %s (attempted to allocate %6.2f MB)\n", __func__, error_desc, size/(1024.0*1024.0));
return NULL;
}
return aligned_memory;
}
#define GGML_ALIGNED_MALLOC(size) ggml_aligned_malloc(size)
#ifdef GGML_USE_CPU_HBM
#define GGML_ALIGNED_FREE(ptr) if(NULL != ptr) hbw_free(ptr)
#else
#define GGML_ALIGNED_FREE(ptr) free(ptr)
#endif
#endif
#define UNUSED GGML_UNUSED
#define SWAP(x, y, T) do { T SWAP = x; x = y; y = SWAP; } while (0)
//
// tensor access macros
//
#define GGML_TENSOR_UNARY_OP_LOCALS \
GGML_TENSOR_LOCALS(int64_t, ne0, src0, ne) \
GGML_TENSOR_LOCALS(size_t, nb0, src0, nb) \
GGML_TENSOR_LOCALS(int64_t, ne, dst, ne) \
GGML_TENSOR_LOCALS(size_t, nb, dst, nb)
#define GGML_TENSOR_BINARY_OP_LOCALS \
GGML_TENSOR_LOCALS(int64_t, ne0, src0, ne) \
GGML_TENSOR_LOCALS(size_t, nb0, src0, nb) \
GGML_TENSOR_LOCALS(int64_t, ne1, src1, ne) \
GGML_TENSOR_LOCALS(size_t, nb1, src1, nb) \
GGML_TENSOR_LOCALS(int64_t, ne, dst, ne) \
GGML_TENSOR_LOCALS(size_t, nb, dst, nb)
#if defined(GGML_USE_ACCELERATE)
#include <Accelerate/Accelerate.h>
#if defined(GGML_USE_CLBLAST) // allow usage of CLBlast alongside Accelerate functions
#include "ggml-opencl.h"
#endif
#elif defined(GGML_USE_OPENBLAS)
#if defined(GGML_BLAS_USE_MKL)
#include <mkl.h>
#else
#include <cblas.h>
#endif
#elif defined(GGML_USE_CUBLAS)
#include "ggml-cuda.h"
#elif defined(GGML_USE_CLBLAST)
#include "ggml-opencl.h"
#endif
// floating point type used to accumulate sums
typedef double ggml_float;
#undef MIN
#undef MAX
#define MIN(a, b) ((a) < (b) ? (a) : (b))
#define MAX(a, b) ((a) > (b) ? (a) : (b))
//
// global data
//
// precomputed gelu table for f16 (128 KB)
static ggml_fp16_t ggml_table_gelu_f16[1 << 16];
// precomputed quick gelu table for f16 (128 KB)
static ggml_fp16_t ggml_table_gelu_quick_f16[1 << 16];
// precomputed silu table for f16 (128 KB)
static ggml_fp16_t ggml_table_silu_f16[1 << 16];
// precomputed exp table for f16 (128 KB)
static ggml_fp16_t ggml_table_exp_f16[1 << 16];
// precomputed f32 table for f16 (256 KB) (ggml-impl.h)
float ggml_table_f32_f16[1 << 16];
// note: do not use these inside ggml.c
// these are meant to be used via the ggml.h API
float ggml_fp16_to_fp32(ggml_fp16_t x) {
return (float) GGML_FP16_TO_FP32(x);
}
ggml_fp16_t ggml_fp32_to_fp16(float x) {
return GGML_FP32_TO_FP16(x);
}
void ggml_fp16_to_fp32_row(const ggml_fp16_t * x, float * y, int n) {
for (int i = 0; i < n; i++) {
y[i] = GGML_FP16_TO_FP32(x[i]);
}
}
void ggml_fp32_to_fp16_row(const float * x, ggml_fp16_t * y, int n) {
int i = 0;
#if defined(__F16C__)
for (; i + 7 < n; i += 8) {
__m256 x_vec = _mm256_loadu_ps(x + i);
__m128i y_vec = _mm256_cvtps_ph(x_vec, _MM_FROUND_TO_NEAREST_INT);
_mm_storeu_si128((__m128i *)(y + i), y_vec);
}
for(; i + 3 < n; i += 4) {
__m128 x_vec = _mm_loadu_ps(x + i);
__m128i y_vec = _mm_cvtps_ph(x_vec, _MM_FROUND_TO_NEAREST_INT);
_mm_storel_epi64((__m128i *)(y + i), y_vec);
}
#endif
for (; i < n; i++) {
y[i] = GGML_FP32_TO_FP16(x[i]);
}
}
//
// timing
//
#if defined(_MSC_VER) || defined(__MINGW32__)
static int64_t timer_freq, timer_start;
void ggml_time_init(void) {
LARGE_INTEGER t;
QueryPerformanceFrequency(&t);
timer_freq = t.QuadPart;
// The multiplication by 1000 or 1000000 below can cause an overflow if timer_freq
// and the uptime is high enough.
// We subtract the program start time to reduce the likelihood of that happening.
QueryPerformanceCounter(&t);
timer_start = t.QuadPart;
}
int64_t ggml_time_ms(void) {
LARGE_INTEGER t;
QueryPerformanceCounter(&t);
return ((t.QuadPart-timer_start) * 1000) / timer_freq;
}
int64_t ggml_time_us(void) {
LARGE_INTEGER t;
QueryPerformanceCounter(&t);
return ((t.QuadPart-timer_start) * 1000000) / timer_freq;
}
#else
void ggml_time_init(void) {}
int64_t ggml_time_ms(void) {
struct timespec ts;
clock_gettime(CLOCK_THREAD_CPUTIME_ID, &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_THREAD_CPUTIME_ID, &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
#if defined(__POWER9_VECTOR__)
#define CACHE_LINE_SIZE 128
#else
#define CACHE_LINE_SIZE 64
#endif
#endif
static const size_t CACHE_LINE_SIZE_F32 = CACHE_LINE_SIZE/sizeof(float);
static void ggml_vec_dot_f32(const int n, float * restrict s, const float * restrict x, const float * restrict y);
static void ggml_vec_dot_f16(const int n, float * restrict s, ggml_fp16_t * restrict x, ggml_fp16_t * restrict y);
static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = {
[GGML_TYPE_I8] = {
.type_name = "i8",
.blck_size = 1,
.type_size = sizeof(int8_t),
.is_quantized = false,
},
[GGML_TYPE_I16] = {
.type_name = "i16",
.blck_size = 1,
.type_size = sizeof(int16_t),
.is_quantized = false,
},
[GGML_TYPE_I32] = {
.type_name = "i32",
.blck_size = 1,
.type_size = sizeof(int32_t),
.is_quantized = false,
},
[GGML_TYPE_F32] = {
.type_name = "f32",
.blck_size = 1,
.type_size = sizeof(float),
.is_quantized = false,
.vec_dot = (ggml_vec_dot_t) ggml_vec_dot_f32,
.vec_dot_type = GGML_TYPE_F32,
},
[GGML_TYPE_F16] = {
.type_name = "f16",
.blck_size = 1,
.type_size = sizeof(ggml_fp16_t),
.is_quantized = false,
.to_float = (ggml_to_float_t) ggml_fp16_to_fp32_row,
.from_float = (ggml_from_float_t) ggml_fp32_to_fp16_row,
.from_float_reference = (ggml_from_float_t) ggml_fp32_to_fp16_row,
.vec_dot = (ggml_vec_dot_t) ggml_vec_dot_f16,
.vec_dot_type = GGML_TYPE_F16,
},
[GGML_TYPE_Q4_0] = {
.type_name = "q4_0",
.blck_size = QK4_0,
.type_size = sizeof(block_q4_0),
.is_quantized = true,
.to_float = (ggml_to_float_t) dequantize_row_q4_0,
.from_float = quantize_row_q4_0,
.from_float_reference = (ggml_from_float_t) quantize_row_q4_0_reference,
.vec_dot = ggml_vec_dot_q4_0_q8_0,
.vec_dot_type = GGML_TYPE_Q8_0,
},
[GGML_TYPE_Q4_1] = {
.type_name = "q4_1",
.blck_size = QK4_1,
.type_size = sizeof(block_q4_1),
.is_quantized = true,
.to_float = (ggml_to_float_t) dequantize_row_q4_1,
.from_float = quantize_row_q4_1,
.from_float_reference = (ggml_from_float_t) quantize_row_q4_1_reference,
.vec_dot = ggml_vec_dot_q4_1_q8_1,
.vec_dot_type = GGML_TYPE_Q8_1,
},
[4] = { // GGML_TYPE_Q4_2
.type_name = "DEPRECATED",
.blck_size = 0,
.type_size = 0,
.is_quantized = false,
.to_float = NULL,
.from_float = NULL,
.from_float_reference = NULL,
.vec_dot = NULL,
.vec_dot_type = GGML_TYPE_COUNT,
},
[5] = { // GGML_TYPE_Q4_3
.type_name = "DEPRECATED",
.blck_size = 0,
.type_size = 0,
.is_quantized = false,
.to_float = NULL,
.from_float = NULL,
.from_float_reference = NULL,
.vec_dot = NULL,
.vec_dot_type = GGML_TYPE_COUNT,
},
[GGML_TYPE_Q5_0] = {
.type_name = "q5_0",
.blck_size = QK5_0,
.type_size = sizeof(block_q5_0),
.is_quantized = true,
.to_float = (ggml_to_float_t) dequantize_row_q5_0,
.from_float = quantize_row_q5_0,
.from_float_reference = (ggml_from_float_t) quantize_row_q5_0_reference,
.vec_dot = ggml_vec_dot_q5_0_q8_0,
.vec_dot_type = GGML_TYPE_Q8_0,
},
[GGML_TYPE_Q5_1] = {
.type_name = "q5_1",
.blck_size = QK5_1,
.type_size = sizeof(block_q5_1),
.is_quantized = true,
.to_float = (ggml_to_float_t) dequantize_row_q5_1,
.from_float = quantize_row_q5_1,
.from_float_reference = (ggml_from_float_t) quantize_row_q5_1_reference,
.vec_dot = ggml_vec_dot_q5_1_q8_1,
.vec_dot_type = GGML_TYPE_Q8_1,
},
[GGML_TYPE_Q8_0] = {
.type_name = "q8_0",
.blck_size = QK8_0,
.type_size = sizeof(block_q8_0),
.is_quantized = true,
.to_float = (ggml_to_float_t) dequantize_row_q8_0,
.from_float = quantize_row_q8_0,
.from_float_reference = (ggml_from_float_t) quantize_row_q8_0_reference,
.vec_dot = ggml_vec_dot_q8_0_q8_0,
.vec_dot_type = GGML_TYPE_Q8_0,
},
[GGML_TYPE_Q8_1] = {
.type_name = "q8_1",
.blck_size = QK8_1,
.type_size = sizeof(block_q8_1),
.is_quantized = true,
.from_float = quantize_row_q8_1,
.from_float_reference = (ggml_from_float_t) quantize_row_q8_1_reference,
.vec_dot_type = GGML_TYPE_Q8_1,
},
[GGML_TYPE_Q2_K] = {
.type_name = "q2_K",
.blck_size = QK_K,
.type_size = sizeof(block_q2_K),
.is_quantized = true,
.to_float = (ggml_to_float_t) dequantize_row_q2_K,
.from_float = quantize_row_q2_K,
.from_float_reference = (ggml_from_float_t) quantize_row_q2_K_reference,
.vec_dot = ggml_vec_dot_q2_K_q8_K,
.vec_dot_type = GGML_TYPE_Q8_K,
},
[GGML_TYPE_Q3_K] = {
.type_name = "q3_K",
.blck_size = QK_K,
.type_size = sizeof(block_q3_K),
.is_quantized = true,
.to_float = (ggml_to_float_t) dequantize_row_q3_K,
.from_float = quantize_row_q3_K,
.from_float_reference = (ggml_from_float_t) quantize_row_q3_K_reference,
.vec_dot = ggml_vec_dot_q3_K_q8_K,
.vec_dot_type = GGML_TYPE_Q8_K,
},
[GGML_TYPE_Q4_K] = {
.type_name = "q4_K",
.blck_size = QK_K,
.type_size = sizeof(block_q4_K),
.is_quantized = true,
.to_float = (ggml_to_float_t) dequantize_row_q4_K,
.from_float = quantize_row_q4_K,
.from_float_reference = (ggml_from_float_t) quantize_row_q4_K_reference,
.vec_dot = ggml_vec_dot_q4_K_q8_K,
.vec_dot_type = GGML_TYPE_Q8_K,
},
[GGML_TYPE_Q5_K] = {
.type_name = "q5_K",
.blck_size = QK_K,
.type_size = sizeof(block_q5_K),
.is_quantized = true,
.to_float = (ggml_to_float_t) dequantize_row_q5_K,
.from_float = quantize_row_q5_K,
.from_float_reference = (ggml_from_float_t) quantize_row_q5_K_reference,
.vec_dot = ggml_vec_dot_q5_K_q8_K,
.vec_dot_type = GGML_TYPE_Q8_K,
},
[GGML_TYPE_Q6_K] = {
.type_name = "q6_K",
.blck_size = QK_K,
.type_size = sizeof(block_q6_K),
.is_quantized = true,
.to_float = (ggml_to_float_t) dequantize_row_q6_K,
.from_float = quantize_row_q6_K,
.from_float_reference = (ggml_from_float_t) quantize_row_q6_K_reference,
.vec_dot = ggml_vec_dot_q6_K_q8_K,
.vec_dot_type = GGML_TYPE_Q8_K,
},
[GGML_TYPE_Q8_K] = {
.type_name = "q8_K",
.blck_size = QK_K,
.type_size = sizeof(block_q8_K),
.is_quantized = true,
.from_float = quantize_row_q8_K,
}
};
// For internal test use
ggml_type_traits_t ggml_internal_get_type_traits(enum ggml_type type) {
GGML_ASSERT(type < GGML_TYPE_COUNT);
return type_traits[type];
}
//
// simd mappings
//
#if defined(__ARM_NEON)
#if !defined(__aarch64__)
// 64-bit compatibility
inline static float vaddvq_f32(float32x4_t v) {
return vgetq_lane_f32(v, 0) + vgetq_lane_f32(v, 1) + vgetq_lane_f32(v, 2) + vgetq_lane_f32(v, 3);
}
#endif
#endif
// 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
#define GGML_F32x4_REDUCE_ONE(x) vaddvq_f32(x)
#define GGML_F32x4_REDUCE(res, x) \
{ \
int offset = GGML_F32_ARR >> 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = vaddq_f32(x[i], x[offset+i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = vaddq_f32(x[i], x[offset+i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = vaddq_f32(x[i], x[offset+i]); \
} \
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) \
do { \
int offset = GGML_F16_ARR >> 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = vaddq_f16(x[i], x[offset+i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = vaddq_f16(x[i], x[offset+i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = vaddq_f16(x[i], x[offset+i]); \
} \
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 = (ggml_float) vaddvq_f32(vaddq_f32(t0, t1)); \
} while (0)
#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(p, i) GGML_F16x8_LOAD(p)
#define GGML_F16_VEC_STORE(p, r, i) GGML_F16x8_STORE(p, r[i])
#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(p, i) GGML_F32Cx4_LOAD(p)
#define GGML_F16_VEC_STORE(p, r, i) GGML_F32Cx4_STORE(p, r[i])
#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) \
do { \
int offset = GGML_F32_ARR >> 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = _mm256_add_ps(x[i], x[offset+i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = _mm256_add_ps(x[i], x[offset+i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = _mm256_add_ps(x[i], x[offset+i]); \
} \
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)); \
} while (0)
// 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
#define GGML_F32Cx8 __m256
#define GGML_F32Cx8_ZERO _mm256_setzero_ps()
#define GGML_F32Cx8_SET1(x) _mm256_set1_ps(x)
#if defined(__F16C__)
// the _mm256_cvt intrinsics require F16C
#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))
#else
static inline __m256 __avx_f32cx8_load(ggml_fp16_t *x) {
float tmp[8];
for (int i = 0; i < 8; i++) {
tmp[i] = GGML_FP16_TO_FP32(x[i]);
}
return _mm256_loadu_ps(tmp);
}
static inline void __avx_f32cx8_store(ggml_fp16_t *x, __m256 y) {
float arr[8];
_mm256_storeu_ps(arr, y);
for (int i = 0; i < 8; i++)
x[i] = GGML_FP32_TO_FP16(arr[i]);
}
#define GGML_F32Cx8_LOAD(x) __avx_f32cx8_load(x)
#define GGML_F32Cx8_STORE(x, y) __avx_f32cx8_store(x, y)
#endif
#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(p, i) GGML_F32Cx8_LOAD(p)
#define GGML_F16_VEC_STORE(p, r, i) GGML_F32Cx8_STORE(p, r[i])
#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__)
#define GGML_SIMD
// F32 POWER9
#define GGML_F32_STEP 32
#define GGML_F32_EPR 4
#define GGML_F32x4 vector float
#define GGML_F32x4_ZERO 0.0f
#define GGML_F32x4_SET1 vec_splats
#define GGML_F32x4_LOAD(p) vec_xl(0, p)
#define GGML_F32x4_STORE(p, r) vec_xst(r, 0, p)
#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) \
{ \
int offset = GGML_F32_ARR >> 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = vec_add(x[i], x[offset+i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = vec_add(x[i], x[offset+i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = vec_add(x[i], x[offset+i]); \
} \
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
#define GGML_F16_STEP GGML_F32_STEP
#define GGML_F16_EPR GGML_F32_EPR
#define GGML_F16_VEC GGML_F32x4
#define GGML_F16_VEC_ZERO GGML_F32x4_ZERO
#define GGML_F16_VEC_SET1 GGML_F32x4_SET1
#define GGML_F16_VEC_FMA GGML_F32x4_FMA
#define GGML_F16_VEC_REDUCE GGML_F32x4_REDUCE
// Use vec_xl, not vec_ld, in case the load address is not aligned.
#define GGML_F16_VEC_LOAD(p, i) (i & 0x1) ? \
vec_extract_fp32_from_shorth(vec_xl(0, p - GGML_F16_EPR)) : \
vec_extract_fp32_from_shortl(vec_xl(0, p))
#define GGML_ENDIAN_BYTE(i) ((unsigned char *)&(uint16_t){1})[i]
#define GGML_F16_VEC_STORE(p, r, i) \
if (i & 0x1) \
vec_xst(vec_pack_to_short_fp32(r[i - GGML_ENDIAN_BYTE(1)], \
r[i - GGML_ENDIAN_BYTE(0)]), \
0, p - GGML_F16_EPR)
#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) \
{ \
int offset = GGML_F32_ARR >> 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = wasm_f32x4_add(x[i], x[offset+i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = wasm_f32x4_add(x[i], x[offset+i]); \
} \
offset >>= 1; \
for (int i = 0; i < offset; ++i) { \
x[i] = wasm_f32x4_add(x[i], x[offset+i]); \
} \
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