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ggml.c
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ggml.c
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#include "ggml.h"
#include <assert.h>
#include <time.h>
#include <math.h>
#include <stdlib.h>
#include <string.h>
#include <stdint.h>
#include <stdio.h>
#include <stdatomic.h>
#include <pthread.h>
#define GGML_DEBUG 0
#define GGML_MEM_ALIGN 16
#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>
#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;
}
#else
#include <immintrin.h>
static inline float fp32_from_bits(uint32_t w) {
union {
uint32_t as_bits;
float as_value;
} fp32 = { w };
return fp32.as_value;
}
static inline uint32_t fp32_to_bits(float f) {
union {
float as_value;
uint32_t as_bits;
} fp32 = { 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);
}
#endif
//
// 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
//
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;
}
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)
const size_t CACHE_LINE_SIZE = hardware_destructive_interference_size;
#else
const size_t CACHE_LINE_SIZE = 64;
#endif
const size_t CACHE_LINE_SIZE_F32 = CACHE_LINE_SIZE/sizeof(float);
//
// 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 __ARM_NEON
// NEON 128-bit
const int n16 = (n & ~15);
float32x4_t sum0 = vdupq_n_f32(0);
float32x4_t sum1 = vdupq_n_f32(0);
float32x4_t sum2 = vdupq_n_f32(0);
float32x4_t sum3 = vdupq_n_f32(0);
float32x4_t x0, x1, x2, x3;
float32x4_t y0, y1, y2, y3;
for (int i = 0; i < n16; i += 16) {
x0 = vld1q_f32(x + i + 0);
x1 = vld1q_f32(x + i + 4);
x2 = vld1q_f32(x + i + 8);
x3 = vld1q_f32(x + i + 12);
y0 = vld1q_f32(y + i + 0);
y1 = vld1q_f32(y + i + 4);
y2 = vld1q_f32(y + i + 8);
y3 = vld1q_f32(y + i + 12);
sum0 = vfmaq_f32(sum0, x0, y0);
sum1 = vfmaq_f32(sum1, x1, y1);
sum2 = vfmaq_f32(sum2, x2, y2);
sum3 = vfmaq_f32(sum3, x3, y3);
}
// reduce sum0..sum3 to sum0
sum0 = vaddq_f32(sum0, sum1);
sum2 = vaddq_f32(sum2, sum3);
sum0 = vaddq_f32(sum0, sum2);
float32x2_t sumf32 = vadd_f32(vget_low_f32(sum0), vget_high_f32(sum0));
sumf = vget_lane_f32(sumf32, 0) + vget_lane_f32(sumf32, 1);
// leftovers
for (int i = n16; i < n; ++i) {
sumf += x[i]*y[i];
}
#elif defined(__AVX2__)
// AVX 256-bit (unroll 4)
const int n32 = (n & ~31);
__m256 sum0 = _mm256_setzero_ps();
__m256 sum1 = _mm256_setzero_ps();
__m256 sum2 = _mm256_setzero_ps();
__m256 sum3 = _mm256_setzero_ps();
__m256 x0, x1, x2, x3;
__m256 y0, y1, y2, y3;
for (int i = 0; i < n32; i += 32) {
x0 = _mm256_loadu_ps(x + i + 0);
x1 = _mm256_loadu_ps(x + i + 8);
x2 = _mm256_loadu_ps(x + i + 16);
x3 = _mm256_loadu_ps(x + i + 24);
y0 = _mm256_loadu_ps(y + i + 0);
y1 = _mm256_loadu_ps(y + i + 8);
y2 = _mm256_loadu_ps(y + i + 16);
y3 = _mm256_loadu_ps(y + i + 24);
sum0 = _mm256_fmadd_ps(x0, y0, sum0);
sum1 = _mm256_fmadd_ps(x1, y1, sum1);
sum2 = _mm256_fmadd_ps(x2, y2, sum2);
sum3 = _mm256_fmadd_ps(x3, y3, sum3);
}
sum0 = _mm256_add_ps(sum0, sum1);
sum2 = _mm256_add_ps(sum2, sum3);
sum0 = _mm256_add_ps(sum0, sum2);
const __m128 r4 = _mm_add_ps(_mm256_castps256_ps128(sum0), _mm256_extractf128_ps(sum0, 1));
const __m128 r2 = _mm_add_ps(r4, _mm_movehl_ps(r4, r4));
const __m128 r1 = _mm_add_ss(r2, _mm_movehdup_ps(r2));
sumf = _mm_cvtss_f32(r1);
// leftovers
for (int i = n32; 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;
#ifdef __ARM_NEON
const int n32 = (n & ~31);
float16x8_t sum0 = vdupq_n_f16(0);
float16x8_t sum1 = vdupq_n_f16(0);
float16x8_t sum2 = vdupq_n_f16(0);
float16x8_t sum3 = vdupq_n_f16(0);
float16x8_t x0, x1, x2, x3;
float16x8_t y0, y1, y2, y3;
for (int i = 0; i < n32; i += 32) {
x0 = vld1q_f16(x + i + 0 );
x1 = vld1q_f16(x + i + 8 );
x2 = vld1q_f16(x + i + 16);
x3 = vld1q_f16(x + i + 24);
y0 = vld1q_f16(y + i + 0 );
y1 = vld1q_f16(y + i + 8 );
y2 = vld1q_f16(y + i + 16);
y3 = vld1q_f16(y + i + 24);
sum0 = vfmaq_f16(sum0, x0, y0);
sum1 = vfmaq_f16(sum1, x1, y1);
sum2 = vfmaq_f16(sum2, x2, y2);
sum3 = vfmaq_f16(sum3, x3, y3);
}
// reduce sum0..sum3 to sum0
sum0 = vaddq_f16(sum0, sum1);
sum2 = vaddq_f16(sum2, sum3);
sum0 = vaddq_f16(sum0, sum2);
// load sum0 into 2 float32x4_t
float32x4_t sum0f32 = vcvt_f32_f16(vget_low_f16(sum0));
float32x4_t sum1f32 = vcvt_f32_f16(vget_high_f16(sum0));
// reduce sum0f32 and sum1f32 to sumf
sum0f32 = vaddq_f32(sum0f32, sum1f32);
float32x2_t sumf32 = vadd_f32(vget_low_f32(sum0f32), vget_high_f32(sum0f32));
sumf = vget_lane_f32(sumf32, 0) + vget_lane_f32(sumf32, 1);
// leftovers
for (int i = n32; i < n; ++i) {
sumf += ggml_fp16_to_fp32(x[i])*ggml_fp16_to_fp32(y[i]);
}
#elif defined(__AVX2__)
// AVX 256-bit (unroll 4)
const int n32 = (n & ~31);
__m256 sum0 = _mm256_setzero_ps();
__m256 sum1 = _mm256_setzero_ps();
__m256 sum2 = _mm256_setzero_ps();
__m256 sum3 = _mm256_setzero_ps();
__m256 x0, x1, x2, x3;
__m256 y0, y1, y2, y3;
for (int i = 0; i < n32; i += 32) {
x0 = _mm256_cvtph_ps(_mm_loadu_si128((__m128i*)(x + i + 0 )));
x1 = _mm256_cvtph_ps(_mm_loadu_si128((__m128i*)(x + i + 8 )));
x2 = _mm256_cvtph_ps(_mm_loadu_si128((__m128i*)(x + i + 16)));
x3 = _mm256_cvtph_ps(_mm_loadu_si128((__m128i*)(x + i + 24)));
y0 = _mm256_cvtph_ps(_mm_loadu_si128((__m128i*)(y + i + 0 )));
y1 = _mm256_cvtph_ps(_mm_loadu_si128((__m128i*)(y + i + 8 )));
y2 = _mm256_cvtph_ps(_mm_loadu_si128((__m128i*)(y + i + 16)));
y3 = _mm256_cvtph_ps(_mm_loadu_si128((__m128i*)(y + i + 24)));
sum0 = _mm256_fmadd_ps(x0, y0, sum0);
sum1 = _mm256_fmadd_ps(x1, y1, sum1);
sum2 = _mm256_fmadd_ps(x2, y2, sum2);
sum3 = _mm256_fmadd_ps(x3, y3, sum3);
}
const __m256 sum01 = _mm256_add_ps(sum0, sum1);
const __m256 sum23 = _mm256_add_ps(sum2, sum3);
const __m256 sum0123 = _mm256_add_ps(sum01, sum23);
const __m128 r4 = _mm_add_ps(_mm256_castps256_ps128(sum0123), _mm256_extractf128_ps(sum0123, 1));
const __m128 r2 = _mm_add_ps(r4, _mm_movehl_ps(r4, r4));
const __m128 r1 = _mm_add_ss(r2, _mm_movehdup_ps(r2));
sumf = _mm_cvtss_f32(r1);
// leftovers
for (int i = n32; i < n; ++i) {
//GGML_ASSERT(false);
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) {
#ifdef __ARM_NEON
// NEON 128-bit
const int n16 = (n & ~15);
const float32x4_t v4 = vdupq_n_f32(v);
float32x4_t x0, x1, x2, x3;
float32x4_t y0, y1, y2, y3;
for (int i = 0; i < n16; i += 16) {
x0 = vld1q_f32(x + i + 0);
x1 = vld1q_f32(x + i + 4);
x2 = vld1q_f32(x + i + 8);
x3 = vld1q_f32(x + i + 12);
y0 = vld1q_f32(y + i + 0);
y1 = vld1q_f32(y + i + 4);
y2 = vld1q_f32(y + i + 8);
y3 = vld1q_f32(y + i + 12);
y0 = vfmaq_f32(y0, x0, v4);
y1 = vfmaq_f32(y1, x1, v4);
y2 = vfmaq_f32(y2, x2, v4);
y3 = vfmaq_f32(y3, x3, v4);
vst1q_f32(y + i + 0, y0);
vst1q_f32(y + i + 4, y1);
vst1q_f32(y + i + 8, y2);
vst1q_f32(y + i + 12, y3);
}
// leftovers
for (int i = n16; i < n; ++i) {
y[i] += x[i]*v;
}
#elif defined(__AVX2__)
// AVX 256-bit (unroll 4)
const int n32 = (n & ~31);
const __m256 v4 = _mm256_set1_ps(v);
__m256 x0, x1, x2, x3;
__m256 y0, y1, y2, y3;
for (int i = 0; i < n32; i += 32) {
x0 = _mm256_loadu_ps(x + i + 0);
x1 = _mm256_loadu_ps(x + i + 8);
x2 = _mm256_loadu_ps(x + i + 16);
x3 = _mm256_loadu_ps(x + i + 24);
y0 = _mm256_loadu_ps(y + i + 0);
y1 = _mm256_loadu_ps(y + i + 8);
y2 = _mm256_loadu_ps(y + i + 16);
y3 = _mm256_loadu_ps(y + i + 24);
y0 = _mm256_fmadd_ps(x0, v4, y0);
y1 = _mm256_fmadd_ps(x1, v4, y1);
y2 = _mm256_fmadd_ps(x2, v4, y2);
y3 = _mm256_fmadd_ps(x3, v4, y3);
_mm256_storeu_ps(y + i + 0, y0);
_mm256_storeu_ps(y + i + 8, y1);
_mm256_storeu_ps(y + i + 16, y2);
_mm256_storeu_ps(y + i + 24, y3);
}
// leftovers
for (int i = n32; 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) {
#ifdef __ARM_NEON
// NEON 128-bit
const int n32 = (n & ~31);
const float16x8_t v8 = vdupq_n_f16(v);
float16x8_t x0, x1, x2, x3;
float16x8_t y0, y1, y2, y3;
for (int i = 0; i < n32; i += 32) {
y0 = vld1q_f16(y + i + 0 );
y1 = vld1q_f16(y + i + 8 );
y2 = vld1q_f16(y + i + 16);
y3 = vld1q_f16(y + i + 24);
x0 = vld1q_f16(x + i + 0 );
x1 = vld1q_f16(x + i + 8 );
x2 = vld1q_f16(x + i + 16);
x3 = vld1q_f16(x + i + 24);
y0 = vfmaq_f16(y0, x0, v8);
y1 = vfmaq_f16(y1, x1, v8);
y2 = vfmaq_f16(y2, x2, v8);
y3 = vfmaq_f16(y3, x3, v8);
vst1q_f16(y + i + 0 , y0);
vst1q_f16(y + i + 8 , y1);
vst1q_f16(y + i + 16, y2);
vst1q_f16(y + i + 24, y3);
}
// leftovers
for (int i = n32; 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(__AVX2__)
// AVX 256-bit
const int n32 = (n & ~31);
const __m256 v8 = _mm256_set1_ps(v);
__m256 x0, x1, x2, x3;
__m256 y0, y1, y2, y3;
for (int i = 0; i < n32; i += 32) {
y0 = _mm256_cvtph_ps(_mm_loadu_si128((__m128i*)(y + i + 0 )));
y1 = _mm256_cvtph_ps(_mm_loadu_si128((__m128i*)(y + i + 8 )));
y2 = _mm256_cvtph_ps(_mm_loadu_si128((__m128i*)(y + i + 16)));
y3 = _mm256_cvtph_ps(_mm_loadu_si128((__m128i*)(y + i + 24)));
x0 = _mm256_cvtph_ps(_mm_loadu_si128((__m128i*)(x + i + 0 )));
x1 = _mm256_cvtph_ps(_mm_loadu_si128((__m128i*)(x + i + 8 )));
x2 = _mm256_cvtph_ps(_mm_loadu_si128((__m128i*)(x + i + 16)));
x3 = _mm256_cvtph_ps(_mm_loadu_si128((__m128i*)(x + i + 24)));
y0 = _mm256_fmadd_ps(x0, v8, y0);
y1 = _mm256_fmadd_ps(x1, v8, y1);
y2 = _mm256_fmadd_ps(x2, v8, y2);
y3 = _mm256_fmadd_ps(x3, v8, y3);
_mm_storeu_si128((__m128i*)(y + i + 0 ), _mm256_cvtps_ph(y0, 0));
_mm_storeu_si128((__m128i*)(y + i + 8 ), _mm256_cvtps_ph(y1, 0));
_mm_storeu_si128((__m128i*)(y + i + 16), _mm256_cvtps_ph(y2, 0));
_mm_storeu_si128((__m128i*)(y + i + 24), _mm256_cvtps_ph(y3, 0));
}
// leftovers
for (int i = n32; 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);
}
#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_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; }
const ggml_float GELU_COEF_A = 0.044715;
const ggml_float SQRT_2_OVER_PI = 0.79788456080286535587989211986876;
inline static float ggml_gelu_f32(float x) {
return 0.5*x*(1.0 + tanh(SQRT_2_OVER_PI*x*(1.0 + GELU_COEF_A*x*x)));
}
inline static void ggml_vec_gelu_f32(const int n, float * y, const float * x) {
for (int i = 0; i < n; ++i) {
y[i] = ggml_gelu_f32(x[i]);
}
}
inline static void ggml_vec_gelu_f16(const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
const uint16_t * i16 = (const uint16_t *) x;
for (int i = 0; i < n; ++i) {
y[i] = table_gelu_f16[i16[i]];
}
}
inline static void ggml_vec_sum_f32 (const int n, float * s, const float * x) { ggml_float sum = 0.0; for (int i = 0; i < n; ++i) sum += x[i]; *s += sum; }
inline static void ggml_vec_norm_inv_f32(const int n, float * s, const float * x) { ggml_vec_norm_f32(n, s, x); *s = 1./(*s); }
//
// 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__)
//
// data types
//
const size_t GGML_TYPE_SIZE[GGML_TYPE_COUNT] = {
sizeof(int8_t ),
sizeof(int16_t),
sizeof(int32_t),
sizeof(ggml_fp16_t),
sizeof(float ),
};
const char * GGML_OP_LABEL[GGML_OP_COUNT] = {
"NONE",
"DUP",
"ADD",
"SUB",
"MUL",
"DIV",
"SQR",
"SQRT",
"SUM",
"MEAN",
"REPEAT",
"ABS",
"SGN",
"NEG",
"STEP",
"RELU",
"GELU",
"NORM",
"MUL_MAT",
"SCALE",
"CPY",
"RESHAPE",
"VIEW",
"PERMUTE",
"TRANSPOSE",
"GET_ROWS",
"DIAG_MASK_INF",
"SOFT_MAX",
"ROPE",
"CONV_1D_1S",
"CONV_1D_2S",
"FLASH_ATTN",
"FLASH_FF",
};
const char * GGML_OP_SYMBOL[GGML_OP_COUNT] = {
"none",
"x",
"x+y",
"x-y",
"x*y",
"x/y",
"x^2",
"√x",
"Σx",
"Σx/n",
"repeat(x)",
"abs(x)",
"sgn(x)",
"-x",
"step(x)",
"relu(x)",
"gelu(x)",
"norm(x)",
"X*Y",
"x*v",
"x-\\>y",
"reshape(x)",
"view(x)",
"permute(x)",
"transpose(x)",
"get_rows(x)",
"diag_mask_inf(x)",
"soft_max(x)",
"rope(x)",
"conv_1d_1s(x)",
"conv_1d_2s(x)",
"flash_attn(x)",
"flash_ff(x)",
};
//
// ggml object
//
struct ggml_object {
size_t offset;
size_t size;
struct ggml_object * next;
char padding[8];
};
const size_t GGML_OBJECT_SIZE = sizeof(struct ggml_object);
static_assert(sizeof(struct ggml_object)%GGML_MEM_ALIGN == 0, "ggml_object size must be a multiple of GGML_MEM_ALIGN");
static_assert(sizeof(struct ggml_tensor)%GGML_MEM_ALIGN == 0, "ggml_tensor size must be a multiple of GGML_MEM_ALIGN");
//
// ggml context
//
struct ggml_context {
size_t mem_size;
void * mem_buffer;
bool mem_buffer_owned;
int n_objects;
struct ggml_object * objects_begin;
struct ggml_object * objects_end;
};
struct ggml_context_container {
bool used;
struct ggml_context context;
};
//
// compute types
//
enum ggml_task_type {
GGML_TASK_INIT = 0,
GGML_TASK_COMPUTE,
GGML_TASK_FINALIZE,
};
struct ggml_compute_params {
enum ggml_task_type type;
int ith, nth;
// work buffer for all threads
size_t wsize;
void * wdata;
};
//
// ggml state
//
struct ggml_state {
struct ggml_context_container contexts[GGML_MAX_CONTEXTS];
};
// global state
struct ggml_state g_state;
////////////////////////////////////////////////////////////////////////////////
void ggml_print_object(const struct ggml_object * obj) {
GGML_PRINT(" - ggml_object: offset = %zu, size = %zu, next = %p\n",
obj->offset, obj->size, (const void *) obj->next);
}
void ggml_print_objects(const struct ggml_context * ctx) {
struct ggml_object * obj = ctx->objects_begin;
GGML_PRINT("%s: objects in context %p:\n", __func__, (const void *) ctx);
while (obj != NULL) {
ggml_print_object(obj);
obj = obj->next;
}
GGML_PRINT("%s: --- end ---\n", __func__);
}
int ggml_nelements(const struct ggml_tensor * tensor) {
static_assert(GGML_MAX_DIMS == 4, "GGML_MAX_DIMS is not 4 - update this function");
return tensor->ne[0]*tensor->ne[1]*tensor->ne[2]*tensor->ne[3];
}
int ggml_nrows(const struct ggml_tensor * tensor) {
static_assert(GGML_MAX_DIMS == 4, "GGML_MAX_DIMS is not 4 - update this function");
return tensor->ne[1]*tensor->ne[2]*tensor->ne[3];
}
size_t ggml_nbytes(const struct ggml_tensor * tensor) {
static_assert(GGML_MAX_DIMS == 4, "GGML_MAX_DIMS is not 4 - update this function");
return ggml_nelements(tensor)*GGML_TYPE_SIZE[tensor->type];
}
size_t ggml_type_size(enum ggml_type type) {
return GGML_TYPE_SIZE[type];
}
size_t ggml_element_size(const struct ggml_tensor * tensor) {
return GGML_TYPE_SIZE[tensor->type];
}
bool ggml_is_scalar(const struct ggml_tensor * tensor) {
static_assert(GGML_MAX_DIMS == 4, "GGML_MAX_DIMS is not 4 - update this function");
return tensor->ne[0] == 1 && tensor->ne[1] == 1 && tensor->ne[2] == 1 && tensor->ne[3] == 1;
}
bool ggml_is_vector(const struct ggml_tensor * tensor) {
static_assert(GGML_MAX_DIMS == 4, "GGML_MAX_DIMS is not 4 - update this function");
return tensor->ne[1] == 1 && tensor->ne[2] == 1 && tensor->ne[3] == 1;
}
bool ggml_is_matrix(const struct ggml_tensor * tensor) {
static_assert(GGML_MAX_DIMS == 4, "GGML_MAX_DIMS is not 4 - update this function");
return tensor->ne[2] == 1 && tensor->ne[3] == 1;
}
bool ggml_can_mul_mat(const struct ggml_tensor * t0, const struct ggml_tensor * t1) {
static_assert(GGML_MAX_DIMS == 4, "GGML_MAX_DIMS is not 4 - update this function");
return
(t0->ne[0] == t1->ne[0]) &&
(t0->ne[2] == t1->ne[2]) &&
(t0->ne[3] == t1->ne[3]);
}
bool ggml_is_contiguous(const struct ggml_tensor * tensor) {
static_assert(GGML_MAX_DIMS == 4, "GGML_MAX_DIMS is not 4 - update this function");
return
tensor->nb[0] == GGML_TYPE_SIZE[tensor->type] &&
tensor->nb[1] == tensor->nb[0]*tensor->ne[0] &&
tensor->nb[2] == tensor->nb[1]*tensor->ne[1] &&
tensor->nb[3] == tensor->nb[2]*tensor->ne[2];
}
bool ggml_is_padded_1d(const struct ggml_tensor * tensor) {
static_assert(GGML_MAX_DIMS == 4, "GGML_MAX_DIMS is not 4 - update this function");
return
tensor->nb[0] == GGML_TYPE_SIZE[tensor->type] &&
tensor->nb[2] == tensor->nb[1]*tensor->ne[1] &&
tensor->nb[3] == tensor->nb[2]*tensor->ne[2];;
}
bool ggml_are_same_shape(const struct ggml_tensor * t0, const struct ggml_tensor * t1) {
static_assert(GGML_MAX_DIMS == 4, "GGML_MAX_DIMS is not 4 - update this function");
return
(t0->ne[0] == t1->ne[0] ) &&
(t0->ne[1] == t1->ne[1] ) &&
(t0->ne[2] == t1->ne[2] ) &&
(t0->ne[3] == t1->ne[3] );
}
// check if t1 can be represented as a repeatition of t0
bool ggml_can_repeat(const struct ggml_tensor * t0, const struct ggml_tensor * t1) {
static_assert(GGML_MAX_DIMS == 4, "GGML_MAX_DIMS is not 4 - update this function");
return
(t1->ne[0]%t0->ne[0] == 0) &&
(t1->ne[1]%t0->ne[1] == 0) &&
(t1->ne[2]%t0->ne[2] == 0) &&
(t1->ne[3]%t0->ne[3] == 0);
}
int ggml_up32(int n) {
return (n + 31) & ~31;
}
int ggml_up64(int n) {
return (n + 63) & ~63;
}
// assert that pointer is aligned to GGML_MEM_ALIGN
#define ggml_assert_aligned(ptr) \
assert(((uintptr_t) (ptr))%GGML_MEM_ALIGN == 0)
////////////////////////////////////////////////////////////////////////////////
struct ggml_context * ggml_init(struct ggml_init_params params) {
static bool is_first_call = true;
if (is_first_call) {
const uint64_t t_start = ggml_time_us(); UNUSED(t_start);
for (int i = 0; i < (1 << 16); ++i) {
uint16_t ii = (uint16_t) i;
const float f = ggml_fp16_to_fp32(*(ggml_fp16_t *)(&ii));
table_gelu_f16[i] = ggml_fp32_to_fp16(ggml_gelu_f32(f));
table_exp_f16[i] = ggml_fp32_to_fp16(exp(f));
}
const uint64_t t_end = ggml_time_us(); UNUSED(t_end);
GGML_PRINT_DEBUG("%s: GELU table initialized in %f ms\n", __func__, (t_end - t_start)/1000.0f);
is_first_call = false;
}
// find non-used context in g_state
struct ggml_context * ctx = NULL;
static bool first_time = true;
if (first_time) {
for (int i = 0; i < GGML_MAX_CONTEXTS; i++) {
g_state.contexts[i].used = false;
}
first_time = false;
}
for (int i = 0; i < GGML_MAX_CONTEXTS; i++) {
if (!g_state.contexts[i].used) {
g_state.contexts[i].used = true;
ctx = &g_state.contexts[i].context;
GGML_PRINT_DEBUG("%s: found unused context %d\n", __func__, i);
break;
}
}
if (ctx == NULL) {
GGML_PRINT_DEBUG("%s: no unused context found\n", __func__);
return NULL;
}
*ctx = (struct ggml_context) {
.mem_size = params.mem_size,
.mem_buffer = params.mem_buffer ? params.mem_buffer : malloc(params.mem_size),
.mem_buffer_owned = params.mem_buffer ? false : true,
.n_objects = 0,
.objects_begin = NULL,
.objects_end = NULL,
};
ggml_assert_aligned(ctx->mem_buffer);
return ctx;
}
void ggml_free(struct ggml_context * ctx) {
for (int i = 0; i < GGML_MAX_CONTEXTS; i++) {
if (&g_state.contexts[i].context == ctx) {
g_state.contexts[i].used = false;
GGML_PRINT_DEBUG("%s: context %d with %d objects has been freed. memory used = %zu\n",
__func__, i, ctx->n_objects, ctx->objects_end->offset + ctx->objects_end->size);
if (ctx->mem_buffer_owned) {
free(ctx->mem_buffer);
}
return;
}
}
GGML_PRINT_DEBUG("%s: context not found\n", __func__);
}
size_t ggml_used_mem(const struct ggml_context * ctx) {
return ctx->objects_end->offset + ctx->objects_end->size;
}
////////////////////////////////////////////////////////////////////////////////
struct ggml_tensor * ggml_new_tensor_impl(
struct ggml_context * ctx,
enum ggml_type type,
int n_dims,
const int* ne,
void* data) {
// always insert objects at the end of the context's memory pool
struct ggml_object * obj_cur = ctx->objects_end;