cff777f226
* 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
251 lines
8.8 KiB
C
251 lines
8.8 KiB
C
#pragma clang diagnostic ignored "-Wunused-variable"
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#pragma clang diagnostic ignored "-Wunused-function"
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#pragma clang diagnostic ignored "-Wunused-but-set-variable"
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#include <HAP_farf.h>
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#include <HAP_perf.h>
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#include <math.h>
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#include <string.h>
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#define GGML_COMMON_DECL_C
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#include "ggml-common.h"
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#include "htp-ctx.h"
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#include "htp-msg.h"
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#include "htp-ops.h"
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#include "hvx-utils.h"
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struct htp_copy_context {
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struct htp_ops_context * octx;
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uint32_t src0_type_size;
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uint32_t src0_block_size;
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uint32_t dst_type_size;
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uint32_t dst_block_size;
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uint32_t src0_blocks_per_row;
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uint32_t dst_blocks_per_row;
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uint32_t src0_nrows_per_thread;
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void (*copy)(struct htp_copy_context * ct, struct htp_ops_context * octx, int nth, int ith);
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};
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#define cpy_preamble \
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struct htp_tensor *src0 = &octx->src0; \
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struct htp_tensor *dst = &octx->dst; \
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\
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const uint32_t ne00 = src0->ne[0]; \
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const uint32_t ne01 = src0->ne[1]; \
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const uint32_t ne02 = src0->ne[2]; \
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const uint32_t ne03 = src0->ne[3]; \
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\
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const uint32_t nb00 = src0->nb[0]; \
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const uint32_t nb01 = src0->nb[1]; \
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const uint32_t nb02 = src0->nb[2]; \
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const uint32_t nb03 = src0->nb[3]; \
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\
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const uint32_t ne0 = dst->ne[0]; \
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const uint32_t ne1 = dst->ne[1]; \
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const uint32_t ne2 = dst->ne[2]; \
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const uint32_t ne3 = dst->ne[3]; \
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\
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const uint32_t nb0 = dst->nb[0]; \
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const uint32_t nb1 = dst->nb[1]; \
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const uint32_t nb2 = dst->nb[2]; \
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const uint32_t nb3 = dst->nb[3]; \
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\
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const uint32_t nr = ne01;
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static void cpy_thread_sametype_sameshape(struct htp_copy_context * ct, struct htp_ops_context * octx, const int nth, const int ith) {
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cpy_preamble;
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// parallelize by src0 rows
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const uint32_t dr = ct->src0_nrows_per_thread;
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const uint32_t ir0 = dr * ith;
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const uint32_t ir1 = (ir0 + dr) < nr ? (ir0 + dr) : nr;
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// copy by rows
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for (uint32_t i03 = 0; i03 < ne03; i03++) {
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for (uint32_t i02 = 0; i02 < ne02; i02++) {
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#pragma unroll(2)
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for (uint32_t i01 = ir0; i01 < ir1; i01++) {
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uint8_t* dst_ptr = (uint8_t*) dst->data + i01*nb1 + i02*nb2 + i03*nb3;
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uint8_t* src0_ptr = (uint8_t*) src0->data + i01*nb01 + i02*nb02 + i03*nb03;
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hex_l2fetch(src0_ptr, ne00 * ct->src0_type_size, nb01, 2);
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hvx_copy_uu(dst_ptr, src0_ptr, ne00, ct->src0_type_size);
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}
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}
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}
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}
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static void cpy_thread_sametype_reshape(struct htp_copy_context * ct, struct htp_ops_context * octx, int nth, int ith) {
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cpy_preamble;
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// parallelize by src0 rows
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const uint32_t dr = ct->src0_nrows_per_thread;
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const uint32_t ir0 = dr * ith;
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const uint32_t ir1 = (ir0 + dr) < nr ? (ir0 + dr) : nr;
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// dst counters
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int64_t k10 = 0;
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int64_t i11 = 0;
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int64_t i12 = 0;
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int64_t i13 = 0;
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// number of blocks in a row
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const int64_t nk00 = ct->src0_blocks_per_row;
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const int64_t nk0 = ct->dst_blocks_per_row;
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for (int64_t i03 = 0; i03 < ne03; i03++) {
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for (int64_t i02 = 0; i02 < ne02; i02++) {
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k10 += nk00 * ir0;
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while (k10 >= nk0) {
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k10 -= nk0;
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if (++i11 == ne1) {
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i11 = 0;
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if (++i12 == ne2) {
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i12 = 0;
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if (++i13 == ne3) {
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i13 = 0;
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}
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}
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}
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}
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for (int64_t i01 = ir0; i01 < ir1; i01++) {
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for (int64_t k00 = 0; k00 < nk00; k00++) {
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const char * src0_ptr = ((char *) src0->data + k00*nb00 + i01*nb01 + i02*nb02 + i03*nb03);
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char * dst_ptr = ((char *) dst->data + k10*nb0 + i11*nb1 + i12*nb2 + i13*nb3);
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memcpy(dst_ptr, src0_ptr, ct->dst_type_size);
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if (++k10 == nk0) {
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k10 = 0;
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if (++i11 == ne1) {
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i11 = 0;
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if (++i12 == ne2) {
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i12 = 0;
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if (++i13 == ne3) {
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i13 = 0;
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}
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}
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}
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}
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}
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}
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k10 += nk00 * (ne01 - ir1);
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while (k10 >= nk0) {
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k10 -= nk0;
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if (++i11 == ne1) {
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i11 = 0;
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if (++i12 == ne2) {
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i12 = 0;
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if (++i13 == ne3) {
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i13 = 0;
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}
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}
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}
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}
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}
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}
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}
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static void cpy_thread_f16_f32_sameshape(struct htp_copy_context * ct, struct htp_ops_context * octx, const int nth, const int ith) {
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cpy_preamble;
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// parallelize by src0 rows
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const uint32_t dr = ct->src0_nrows_per_thread;
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const uint32_t ir0 = dr * ith;
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const uint32_t ir1 = (ir0 + dr) < nr ? (ir0 + dr) : nr;
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// copy by rows
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for (uint32_t i03 = 0; i03 < ne03; i03++) {
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for (uint32_t i02 = 0; i02 < ne02; i02++) {
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#pragma unroll(2)
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for (uint32_t i01 = ir0; i01 < ir1; i01++) {
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uint8_t* dst_ptr = (uint8_t*) dst->data + i01*nb1 + i02*nb2 + i03*nb3;
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uint8_t* src0_ptr = (uint8_t*) src0->data + i01*nb01 + i02*nb02 + i03*nb03;
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hex_l2fetch(src0_ptr, ne00 * sizeof(float), nb01, 2);
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hvx_copy_f16_f32_uu(dst_ptr, src0_ptr, ne00);
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}
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}
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}
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}
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static void cpy_thread_f32_f16_sameshape(struct htp_copy_context * ct, struct htp_ops_context * octx, const int nth, const int ith) {
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cpy_preamble;
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// parallelize by src0 rows
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const uint32_t dr = ct->src0_nrows_per_thread;
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const uint32_t ir0 = dr * ith;
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const uint32_t ir1 = (ir0 + dr) < nr ? (ir0 + dr) : nr;
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// copy by rows
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for (uint32_t i03 = 0; i03 < ne03; i03++) {
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for (uint32_t i02 = 0; i02 < ne02; i02++) {
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#pragma unroll(2)
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for (uint32_t i01 = ir0; i01 < ir1; i01++) {
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uint8_t* dst_ptr = (uint8_t*) dst->data + i01*nb1 + i02*nb2 + i03*nb3;
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uint8_t* src0_ptr = (uint8_t*) src0->data + i01*nb01 + i02*nb02 + i03*nb03;
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hex_l2fetch(src0_ptr, ne00 * sizeof(__fp16), nb01, 2);
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hvx_copy_f32_f16_uu(dst_ptr, src0_ptr, ne00);
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}
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}
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}
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}
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static void cpy_work_func(unsigned int n, unsigned int i, void *data) {
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struct htp_copy_context *ct = (struct htp_copy_context *) data;
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ct->copy(ct, ct->octx, n, i);
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}
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int op_cpy(struct htp_ops_context * octx) {
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cpy_preamble;
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struct htp_copy_context ct;
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ct.octx = octx;
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switch (src0->type) {
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case HTP_TYPE_F32: ct.src0_type_size = 4; ct.src0_block_size = 1; ct.src0_blocks_per_row = ne00 / 1; break;
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case HTP_TYPE_F16: ct.src0_type_size = 2; ct.src0_block_size = 1; ct.src0_blocks_per_row = ne00 / 1; break;
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default:
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return HTP_STATUS_NO_SUPPORT;
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}
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switch (dst->type) {
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case HTP_TYPE_F32: ct.dst_type_size = 4; ct.dst_block_size = 1; ct.dst_blocks_per_row = ne0 / 1; break;
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case HTP_TYPE_F16: ct.dst_type_size = 2; ct.dst_block_size = 1; ct.dst_blocks_per_row = ne0 / 1; break;
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default:
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return HTP_STATUS_NO_SUPPORT;
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}
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if (octx->flags & HTP_OPFLAGS_SKIP_COMPUTE) {
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return HTP_STATUS_OK;
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}
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const bool sametype = (src0->type == dst->type);
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const bool transposed = (nb00 > nb01) || (nb0 > nb1);
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const bool sameshape = !transposed && (ne00 == ne0 && ne01 == ne1 && ne02 == ne2 && ne03 == ne3);
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const uint32_t n_jobs = MIN(nr, octx->n_threads);
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ct.src0_nrows_per_thread = (nr + n_jobs - 1) / n_jobs;
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if (sametype && sameshape) {
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ct.copy = cpy_thread_sametype_sameshape;
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} else if (sameshape) {
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/**/ if (dst->type == HTP_TYPE_F16 && src0->type == HTP_TYPE_F32)
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ct.copy = cpy_thread_f16_f32_sameshape;
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else if (dst->type == HTP_TYPE_F32 && src0->type == HTP_TYPE_F16)
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ct.copy = cpy_thread_f32_f16_sameshape;
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else
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return HTP_STATUS_NO_SUPPORT;
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} else if (sametype) {
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ct.copy = cpy_thread_sametype_reshape;
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} else {
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return HTP_STATUS_NO_SUPPORT;
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}
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worker_pool_run_func(octx->ctx->worker_pool, cpy_work_func, &ct, n_jobs);
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return HTP_STATUS_OK;
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}
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