mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-11-11 21:39:52 +00:00
8cc91dc63c
This change upstreams llamafile's cpu matrix multiplication kernels which improve image and prompt evaluation speed. For starters, Q4_0 and Q8_0 weights should go ~40% faster on CPU. The biggest benefits are with data types like f16 / f32, which process prompts 2x faster thus making them faster than quantized data types for prompt evals. This change also introduces bona fide AVX512 support since tinyBLAS is able to exploit the larger register file. For example, on my CPU llama.cpp llava-cli processes an image prompt at 305 tokens/second, using the Q4_K and Q4_0 types, which has always been faster than if we used f16 LLaVA weights, which at HEAD go 188 tokens/second. With this change, f16 LLaVA performance leap frogs to 464 tokens/second. On Intel Core i9-14900K this change improves F16 prompt perf by 5x. For example, using llama.cpp at HEAD with Mistral 7b f16 to process a 215 token prompt will go 13 tok/sec. This change has fixes making it go 52 tok/sec. It's mostly thanks to my vectorized outer product kernels but also because I added support for correctly counting the number of cores on Alderlake, so the default thread count discounts Intel's new efficiency cores. Only Linux right now can count cores. This work was sponsored by Mozilla who's given permission to change the license of this code from Apache 2.0 to MIT. To read more about what's improved, and how it works, see: https://justine.lol/matmul/
266 lines
7.9 KiB
C
266 lines
7.9 KiB
C
#pragma once
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#include "ggml.h"
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// GGML internal header
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#include <assert.h>
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#include <stdlib.h> // load `stdlib.h` before other headers to work around MinGW bug: https://sourceforge.net/p/mingw-w64/bugs/192/
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#include <stddef.h>
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#include <stdbool.h>
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#include <string.h> // memcpy
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#include <math.h> // fabsf
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#ifdef __cplusplus
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extern "C" {
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#endif
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// static_assert should be a #define, but if it's not,
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// fall back to the _Static_assert C11 keyword.
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// if C99 - static_assert is noop
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// ref: https://stackoverflow.com/a/53923785/4039976
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#ifndef __cplusplus
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#ifndef static_assert
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#if defined(__STDC_VERSION__) && (__STDC_VERSION__ >= 201100L)
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#define static_assert(cond, msg) _Static_assert(cond, msg)
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#else
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#define static_assert(cond, msg) struct global_scope_noop_trick
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#endif
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#endif
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#endif
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// __FMA__ and __F16C__ are not defined in MSVC, however they are implied with AVX2/AVX512
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#if defined(_MSC_VER) && (defined(__AVX2__) || defined(__AVX512F__))
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#ifndef __FMA__
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#define __FMA__
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#endif
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#ifndef __F16C__
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#define __F16C__
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#endif
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#ifndef __SSE3__
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#define __SSE3__
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#endif
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#endif
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// 16-bit float
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// on Arm, we use __fp16
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// on x86, we use uint16_t
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#if defined(__ARM_NEON) && !defined(_MSC_VER)
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// if YCM cannot find <arm_neon.h>, make a symbolic link to it, for example:
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//
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// $ ln -sfn /Library/Developer/CommandLineTools/usr/lib/clang/13.1.6/include/arm_neon.h ./src/
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//
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#include <arm_neon.h>
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typedef __fp16 ggml_fp16_internal_t;
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#define GGML_COMPUTE_FP16_TO_FP32(x) ggml_compute_fp16_to_fp32(x)
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#define GGML_COMPUTE_FP32_TO_FP16(x) ggml_compute_fp32_to_fp16(x)
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#define GGML_FP16_TO_FP32(x) ggml_compute_fp16_to_fp32(x)
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static inline float ggml_compute_fp16_to_fp32(ggml_fp16_t h) {
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ggml_fp16_internal_t tmp;
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memcpy(&tmp, &h, sizeof(ggml_fp16_t));
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return (float)tmp;
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}
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static inline ggml_fp16_t ggml_compute_fp32_to_fp16(float f) {
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ggml_fp16_t res;
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ggml_fp16_internal_t tmp = f;
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memcpy(&res, &tmp, sizeof(ggml_fp16_t));
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return res;
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}
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#else
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typedef uint16_t ggml_fp16_internal_t;
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#ifdef __wasm_simd128__
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#include <wasm_simd128.h>
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#else
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#ifdef __POWER9_VECTOR__
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#include <altivec.h>
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#undef bool
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#define bool _Bool
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#else
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#if defined(_MSC_VER) || defined(__MINGW32__)
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#include <intrin.h>
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#else
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#if defined(__AVX__) || defined(__AVX2__) || defined(__AVX512F__) || defined(__SSSE3__) || defined(__SSE3__) || defined(__SSE__)
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#if !defined(__riscv)
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#include <immintrin.h>
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#endif
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#endif
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#endif
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#endif
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#endif
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#ifdef __riscv_v_intrinsic
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#include <riscv_vector.h>
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#endif
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#ifdef __F16C__
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#ifdef _MSC_VER
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#define GGML_COMPUTE_FP16_TO_FP32(x) _mm_cvtss_f32(_mm_cvtph_ps(_mm_cvtsi32_si128(x)))
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#define GGML_COMPUTE_FP32_TO_FP16(x) _mm_extract_epi16(_mm_cvtps_ph(_mm_set_ss(x), 0), 0)
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#else
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#define GGML_COMPUTE_FP16_TO_FP32(x) _cvtsh_ss(x)
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#define GGML_COMPUTE_FP32_TO_FP16(x) _cvtss_sh(x, 0)
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#endif
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#elif defined(__POWER9_VECTOR__)
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#define GGML_COMPUTE_FP16_TO_FP32(x) ggml_compute_fp16_to_fp32(x)
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#define GGML_COMPUTE_FP32_TO_FP16(x) ggml_compute_fp32_to_fp16(x)
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/* the inline asm below is about 12% faster than the lookup method */
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#define GGML_FP16_TO_FP32(x) GGML_COMPUTE_FP16_TO_FP32(x)
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#define GGML_FP32_TO_FP16(x) GGML_COMPUTE_FP32_TO_FP16(x)
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static inline float ggml_compute_fp16_to_fp32(ggml_fp16_t h) {
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register float f;
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register double d;
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__asm__(
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"mtfprd %0,%2\n"
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"xscvhpdp %0,%0\n"
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"frsp %1,%0\n" :
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/* temp */ "=d"(d),
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/* out */ "=f"(f):
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/* in */ "r"(h));
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return f;
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}
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static inline ggml_fp16_t ggml_compute_fp32_to_fp16(float f) {
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register double d;
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register ggml_fp16_t r;
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__asm__( /* xscvdphp can work on double or single precision */
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"xscvdphp %0,%2\n"
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"mffprd %1,%0\n" :
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/* temp */ "=d"(d),
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/* out */ "=r"(r):
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/* in */ "f"(f));
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return r;
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}
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#else
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// FP16 <-> FP32
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// ref: https://github.com/Maratyszcza/FP16
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static inline float fp32_from_bits(uint32_t w) {
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union {
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uint32_t as_bits;
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float as_value;
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} fp32;
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fp32.as_bits = w;
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return fp32.as_value;
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}
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static inline uint32_t fp32_to_bits(float f) {
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union {
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float as_value;
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uint32_t as_bits;
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} fp32;
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fp32.as_value = f;
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return fp32.as_bits;
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}
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static inline float ggml_compute_fp16_to_fp32(ggml_fp16_t h) {
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const uint32_t w = (uint32_t) h << 16;
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const uint32_t sign = w & UINT32_C(0x80000000);
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const uint32_t two_w = w + w;
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const uint32_t exp_offset = UINT32_C(0xE0) << 23;
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#if defined(__STDC_VERSION__) && (__STDC_VERSION__ >= 199901L) || defined(__GNUC__) && !defined(__STRICT_ANSI__)
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const float exp_scale = 0x1.0p-112f;
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#else
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const float exp_scale = fp32_from_bits(UINT32_C(0x7800000));
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#endif
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const float normalized_value = fp32_from_bits((two_w >> 4) + exp_offset) * exp_scale;
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const uint32_t magic_mask = UINT32_C(126) << 23;
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const float magic_bias = 0.5f;
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const float denormalized_value = fp32_from_bits((two_w >> 17) | magic_mask) - magic_bias;
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const uint32_t denormalized_cutoff = UINT32_C(1) << 27;
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const uint32_t result = sign |
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(two_w < denormalized_cutoff ? fp32_to_bits(denormalized_value) : fp32_to_bits(normalized_value));
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return fp32_from_bits(result);
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}
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static inline ggml_fp16_t ggml_compute_fp32_to_fp16(float f) {
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#if defined(__STDC_VERSION__) && (__STDC_VERSION__ >= 199901L) || defined(__GNUC__) && !defined(__STRICT_ANSI__)
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const float scale_to_inf = 0x1.0p+112f;
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const float scale_to_zero = 0x1.0p-110f;
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#else
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const float scale_to_inf = fp32_from_bits(UINT32_C(0x77800000));
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const float scale_to_zero = fp32_from_bits(UINT32_C(0x08800000));
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#endif
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float base = (fabsf(f) * scale_to_inf) * scale_to_zero;
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const uint32_t w = fp32_to_bits(f);
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const uint32_t shl1_w = w + w;
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const uint32_t sign = w & UINT32_C(0x80000000);
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uint32_t bias = shl1_w & UINT32_C(0xFF000000);
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if (bias < UINT32_C(0x71000000)) {
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bias = UINT32_C(0x71000000);
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}
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base = fp32_from_bits((bias >> 1) + UINT32_C(0x07800000)) + base;
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const uint32_t bits = fp32_to_bits(base);
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const uint32_t exp_bits = (bits >> 13) & UINT32_C(0x00007C00);
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const uint32_t mantissa_bits = bits & UINT32_C(0x00000FFF);
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const uint32_t nonsign = exp_bits + mantissa_bits;
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return (sign >> 16) | (shl1_w > UINT32_C(0xFF000000) ? UINT16_C(0x7E00) : nonsign);
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}
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#define GGML_COMPUTE_FP16_TO_FP32(x) ggml_compute_fp16_to_fp32(x)
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#define GGML_COMPUTE_FP32_TO_FP16(x) ggml_compute_fp32_to_fp16(x)
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#endif // __F16C__
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#endif // __ARM_NEON
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// precomputed f32 table for f16 (256 KB)
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// defined in ggml.c, initialized in ggml_init()
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extern float ggml_table_f32_f16[1 << 16];
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// On ARM NEON, it's quicker to directly convert x -> x instead of calling into ggml_lookup_fp16_to_fp32,
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// so we define GGML_FP16_TO_FP32 and GGML_FP32_TO_FP16 elsewhere for NEON.
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// This is also true for POWER9.
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#if !defined(GGML_FP16_TO_FP32)
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inline static float ggml_lookup_fp16_to_fp32(ggml_fp16_t f) {
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uint16_t s;
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memcpy(&s, &f, sizeof(uint16_t));
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return ggml_table_f32_f16[s];
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}
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#define GGML_FP16_TO_FP32(x) ggml_lookup_fp16_to_fp32(x)
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#endif
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#if !defined(GGML_FP32_TO_FP16)
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#define GGML_FP32_TO_FP16(x) GGML_COMPUTE_FP32_TO_FP16(x)
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#endif
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#define GGML_HASHTABLE_FULL ((size_t)-1)
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#define GGML_HASHTABLE_ALREADY_EXISTS ((size_t)-2)
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struct ggml_hash_set ggml_hash_set_new(size_t size);
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bool ggml_hash_contains (const struct ggml_hash_set hash_set, struct ggml_tensor * key);
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// returns GGML_HASHTABLE_FULL if table is full, otherwise the current index of the key or where it should be inserted
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size_t ggml_hash_find (const struct ggml_hash_set hash_set, struct ggml_tensor * key);
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// returns GGML_HASHTABLE_ALREADY_EXISTS if key already exists, index otherwise, asserts if table is full
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size_t ggml_hash_insert ( struct ggml_hash_set hash_set, struct ggml_tensor * key);
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// return index, asserts if table is full
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size_t ggml_hash_find_or_insert( struct ggml_hash_set hash_set, struct ggml_tensor * key);
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#ifdef __cplusplus
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}
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#endif
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