Files
llama.cpp-mtp-turboquant/ggml/src/ggml-hexagon/htp/hvx-scale.h
T
Max Krasnyansky cff777f226 hexagon: support for OP_CPY, host buffers now optional, hvx-utils refactoring and optimizations (#18822)
* hexagon: disable repack buffers if host buffers are disabled, improved handling of env vars

* hexagon: add support for OP_CPY fp16/fp32 -> fp16/fp32

Factore out all hvx_copy functions into hvx-copy.h header and reduced code duplication.
Update HTP ops infra to support OP_CPY

* hexagon: cleanup and refactor hex/hvx/htp headers and helper libs

hex is basically all scalar/core platform stuff (L2, DMA, basic utils)
hvx is all hvx related utils, helpers, etc
htp is higher level stuff like Ops, etc

hvx-utils library got a nice round of cleanup and refactoring to reduce duplication

use hvx_vec_store_a where possible

* hexagon: refactor HVX sigmoid functions to hvx-sigmoid.h

Moved sigmoid and tanh vector functions from hvx-utils.h to a new header
hvx-sigmoid.h. Implemented aligned and unaligned variants for sigmoid
array processing using a macro pattern similar to hvx-copy.h. Updated
act-ops.c to use the new aligned variant hvx_sigmoid_f32_aa. Removed
unused hvx-sigmoid.c.

* hexagon: factor out hvx-sqrt.h

* hexagon: mintor update to hvx-utils.h

* hexagon: remove spurios log

* hexagon: factor out and optimize hvx_add/sub/mul

* hexagon: remove _opt variants of add/sub/mul as they simply fully aligned versions

* hexagon: refactor reduction functions to hvx-reduce.h

Moved `hvx_self_max_f32` and `hvx_self_sum_f32` from `hvx-utils.h`/`.c` to `hvx-reduce.h`.
Renamed them to `hvx_reduce_max_f32` and `hvx_reduce_sum_f32`.
Added aligned (`_a`) and unaligned (`_u`) variants and used macros to unify logic.
Updated `softmax-ops.c` to use the new functions.

* hexagon: refactor the rest of arithmetic functions to hvx-arith.h

Moved `hvx_sum_of_squares_f32`, `hvx_min_scalar_f32`, and `hvx_clamp_scalar_f32` from `hvx-utils.c/h` to `hvx-arith.h`. Implemented aligned/unaligned variants (`_aa`, `_au`, etc.) and used macros to reduce code duplication. Updated `hvx_min_scalar_f32` and `hvx_clamp_scalar_f32` to use `dst, src, ..., n` argument order. Updated call sites in `act-ops.c`.

Refactor Hexagon HVX arithmetic functions (min, clamp) to hvx-arith.h

Moved `hvx_min_scalar_f32` and `hvx_clamp_scalar_f32` from `hvx-utils.c/h` to `hvx-arith.h`. Implemented aligned/unaligned variants (`_aa`, `_au`, etc.) and used macros to reduce code duplication. Updated these functions to use `dst, src, ..., n` argument order and updated call sites in `act-ops.c`. `hvx_sum_of_squares_f32` remains in `hvx-utils.c` as requested.

* hexagon: refactor hvx_sum_of_squares_f32

- Modify `hvx_sum_of_squares_f32` in `ggml/src/ggml-hexagon/htp/hvx-reduce.h` to use `dst, src` signature.
- Implement `_a` (aligned) and `_u` (unaligned) variants for `hvx_sum_of_squares_f32`.
- Update `hvx_reduce_loop_body` macro to support both returning and storing results via `finalize_op`.
- Update existing reduction functions in `hvx-reduce.h` to use the updated macro.
- Update `rms_norm_htp_f32` in `ggml/src/ggml-hexagon/htp/unary-ops.c` to match the new signature.

* hexagon: use hvx_splat instead of memset

* hexagon: consistent use of f32/f16 in all function names to match the rest of GGML

* hexagon: fix hvx_copy_f16_f32 on v75 and older

* hexagon: update readme to include GGML_HEXAGON_EXPERIMENTAL

* scripts: update snapdragon/adb scripts to enable host param
2026-01-14 21:46:12 -08:00

134 lines
7.2 KiB
C

#ifndef HVX_SCALE_H
#define HVX_SCALE_H
#include <assert.h>
#include <stddef.h>
#include <stdint.h>
#include "hvx-base.h"
#define hvx_scale_f32_loop_body(dst_type, src_type, vec_store) \
do { \
dst_type * restrict vdst = (dst_type *) dst; \
src_type * restrict vsrc = (src_type *) src; \
\
HVX_Vector vs = hvx_vec_splat_f32(scale); \
\
const uint32_t elem_size = sizeof(float); \
const uint32_t epv = 128 / elem_size; \
const uint32_t nvec = n / epv; \
const uint32_t nloe = n % epv; \
\
uint32_t i = 0; \
\
_Pragma("unroll(4)") \
for (; i < nvec; ++i) { \
HVX_Vector v = Q6_Vqf32_vmpy_VsfVsf(vsrc[i], vs); \
vdst[i] = Q6_Vsf_equals_Vqf32(v); \
} \
if (nloe) { \
HVX_Vector v = Q6_Vqf32_vmpy_VsfVsf(vsrc[i], vs); \
vec_store((void *) &vdst[i], nloe * elem_size, Q6_Vsf_equals_Vqf32(v)); \
} \
} while(0)
static inline void hvx_scale_f32_aa(uint8_t * restrict dst, const uint8_t * restrict src, const int n, const float scale) {
assert((size_t) dst % 128 == 0);
assert((size_t) src % 128 == 0);
hvx_scale_f32_loop_body(HVX_Vector, HVX_Vector, hvx_vec_store_a);
}
static inline void hvx_scale_f32_au(uint8_t * restrict dst, const uint8_t * restrict src, const int n, const float scale) {
assert((size_t) dst % 128 == 0);
hvx_scale_f32_loop_body(HVX_Vector, HVX_UVector, hvx_vec_store_a);
}
static inline void hvx_scale_f32_ua(uint8_t * restrict dst, const uint8_t * restrict src, const int n, const float scale) {
assert((size_t) src % 128 == 0);
hvx_scale_f32_loop_body(HVX_UVector, HVX_Vector, hvx_vec_store_u);
}
static inline void hvx_scale_f32_uu(uint8_t * restrict dst, const uint8_t * restrict src, const int n, const float scale) {
hvx_scale_f32_loop_body(HVX_UVector, HVX_UVector, hvx_vec_store_u);
}
static inline void hvx_scale_f32(uint8_t * restrict dst, const uint8_t * restrict src, const int n, const float scale) {
if (((size_t) dst & 127) == 0) {
if (((size_t) src & 127) == 0) {
hvx_scale_f32_aa(dst, src, n, scale);
} else {
hvx_scale_f32_au(dst, src, n, scale);
}
} else {
if (((size_t) src & 127) == 0) {
hvx_scale_f32_ua(dst, src, n, scale);
} else {
hvx_scale_f32_uu(dst, src, n, scale);
}
}
}
#define hvx_scale_offset_f32_loop_body(dst_type, src_type, vec_store) \
do { \
dst_type * restrict vdst = (dst_type *) dst; \
src_type * restrict vsrc = (src_type *) src; \
\
HVX_Vector vs = hvx_vec_splat_f32(scale); \
HVX_Vector vo = hvx_vec_splat_f32(offset); \
\
const uint32_t elem_size = sizeof(float); \
const uint32_t epv = 128 / elem_size; \
const uint32_t nvec = n / epv; \
const uint32_t nloe = n % epv; \
\
uint32_t i = 0; \
\
_Pragma("unroll(4)") \
for (; i < nvec; ++i) { \
HVX_Vector v = Q6_Vqf32_vadd_Vqf32Vsf(Q6_Vqf32_vmpy_VsfVsf(vsrc[i], vs), vo); \
vdst[i] = Q6_Vsf_equals_Vqf32(v); \
} \
if (nloe) { \
HVX_Vector v = Q6_Vqf32_vadd_Vqf32Vsf(Q6_Vqf32_vmpy_VsfVsf(vsrc[i], vs), vo); \
vec_store((void *) &vdst[i], nloe * elem_size, Q6_Vsf_equals_Vqf32(v)); \
} \
} while(0)
static inline void hvx_scale_offset_f32_aa(uint8_t * restrict dst, const uint8_t * restrict src, const int n, const float scale, const float offset) {
assert((size_t) dst % 128 == 0);
assert((size_t) src % 128 == 0);
hvx_scale_offset_f32_loop_body(HVX_Vector, HVX_Vector, hvx_vec_store_a);
}
static inline void hvx_scale_offset_f32_au(uint8_t * restrict dst, const uint8_t * restrict src, const int n, const float scale, const float offset) {
assert((size_t) dst % 128 == 0);
hvx_scale_offset_f32_loop_body(HVX_Vector, HVX_UVector, hvx_vec_store_a);
}
static inline void hvx_scale_offset_f32_ua(uint8_t * restrict dst, const uint8_t * restrict src, const int n, const float scale, const float offset) {
assert((size_t) src % 128 == 0);
hvx_scale_offset_f32_loop_body(HVX_UVector, HVX_Vector, hvx_vec_store_u);
}
static inline void hvx_scale_offset_f32_uu(uint8_t * restrict dst, const uint8_t * restrict src, const int n, const float scale, const float offset) {
hvx_scale_offset_f32_loop_body(HVX_UVector, HVX_UVector, hvx_vec_store_u);
}
static inline void hvx_scale_offset_f32(uint8_t * restrict dst, const uint8_t * restrict src, const int n, const float scale, const float offset) {
if (((size_t) dst & 127) == 0) {
if (((size_t) src & 127) == 0) {
hvx_scale_offset_f32_aa(dst, src, n, scale, offset);
} else {
hvx_scale_offset_f32_au(dst, src, n, scale, offset);
}
} else {
if (((size_t) src & 127) == 0) {
hvx_scale_offset_f32_ua(dst, src, n, scale, offset);
} else {
hvx_scale_offset_f32_uu(dst, src, n, scale, offset);
}
}
}
#endif // HVX_SCALE_H