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llama.cpp / ggml /src /ggml-hexagon /htp /repeat-ops.c
dlxj
todo: 基于 CUDA 13.0 编译
2517be1
#pragma clang diagnostic ignored "-Wunused-variable"
#pragma clang diagnostic ignored "-Wunused-function"
#pragma clang diagnostic ignored "-Wunused-but-set-variable"
#include <HAP_farf.h>
#include <HAP_perf.h>
#include <string.h>
#include "hvx-utils.h"
#define GGML_COMMON_DECL_C
#include "ggml-common.h"
#include "htp-ctx.h"
#include "htp-msg.h"
#include "htp-ops.h"
struct htp_repeat_context {
struct htp_ops_context * octx;
uint32_t nr0;
uint32_t nr1;
uint32_t nr2;
uint32_t nr3;
uint32_t nrows_per_thread;
uint32_t total_dst_rows; // ne1 * ne2 * ne3
size_t type_size;
};
static void repeat_job_per_thread(unsigned int nth, unsigned int ith, void * data) {
const struct htp_repeat_context * rctx = (const struct htp_repeat_context *) data;
struct htp_ops_context * octx = rctx->octx;
const struct htp_tensor * src = &octx->src0;
const struct htp_tensor * dst = &octx->dst;
const uint32_t ne00 = src->ne[0];
const uint32_t ne01 = src->ne[1];
const uint32_t ne02 = src->ne[2];
const uint32_t ne03 = src->ne[3];
const uint32_t nb00 = src->nb[0];
const uint32_t nb01 = src->nb[1];
const uint32_t nb02 = src->nb[2];
const uint32_t nb03 = src->nb[3];
const uint32_t ne0 = dst->ne[0];
const uint32_t ne1 = dst->ne[1];
const uint32_t ne2 = dst->ne[2];
const uint32_t ne3 = dst->ne[3];
const uint32_t nb0 = dst->nb[0];
const uint32_t nb1 = dst->nb[1];
const uint32_t nb2 = dst->nb[2];
const uint32_t nb3 = dst->nb[3];
const uint32_t nr0 = rctx->nr0;
const uint32_t nr1 = rctx->nr1;
const uint32_t nr2 = rctx->nr2;
const uint32_t nr3 = rctx->nr3;
const size_t row_bytes = ne00 * rctx->type_size;
const uint32_t row_start = rctx->nrows_per_thread * ith;
const uint32_t row_end = MIN(row_start + rctx->nrows_per_thread, rctx->total_dst_rows);
uint64_t t1, t2;
t1 = HAP_perf_get_qtimer_count();
for (uint32_t dst_row = row_start; dst_row < row_end; dst_row++) {
// Decompose flat dst row index into (i1, i2, i3)
const uint32_t i1 = dst_row % ne1;
const uint32_t i2 = (dst_row / ne1) % ne2;
const uint32_t i3 = dst_row / (ne1 * ne2);
// Map to source indices (tiling)
const uint32_t k1 = i1 % ne01;
const uint32_t k2 = i2 % ne02;
const uint32_t k3 = i3 % ne03;
const uint8_t * src_row = (const uint8_t *) src->data + k1 * nb01 + k2 * nb02 + k3 * nb03;
uint8_t * dst_base = (uint8_t *) dst->data + i1 * nb1 + i2 * nb2 + i3 * nb3;
// Tile along dimension 0
for (uint32_t i0 = 0; i0 < nr0; i0++) {
uint8_t * dst_ptr = dst_base + i0 * ne00 * nb0;
memcpy(dst_ptr, src_row, row_bytes);
}
}
t2 = HAP_perf_get_qtimer_count();
FARF(HIGH, "repeat %d/%d: (%ux%ux%ux%u) -> (%ux%ux%ux%u) rows %u:%u usec %u\n",
ith, nth, src->ne[0], src->ne[1], src->ne[2], src->ne[3],
dst->ne[0], dst->ne[1], dst->ne[2], dst->ne[3],
row_start, row_end, (unsigned) HAP_perf_qtimer_count_to_us(t2 - t1));
}
int op_repeat(struct htp_ops_context * octx) {
const struct htp_tensor * src0 = &octx->src0;
struct htp_tensor * dst = &octx->dst;
// Validate that dst dims are multiples of src dims
if (dst->ne[0] % src0->ne[0] != 0 ||
dst->ne[1] % src0->ne[1] != 0 ||
dst->ne[2] % src0->ne[2] != 0 ||
dst->ne[3] % src0->ne[3] != 0) {
FARF(ERROR, "repeat: dst dims must be multiples of src dims\n");
return HTP_STATUS_INVAL_PARAMS;
}
size_t type_size;
switch (src0->type) {
case HTP_TYPE_F32: type_size = 4; break;
case HTP_TYPE_F16: type_size = 2; break;
default:
FARF(ERROR, "repeat: unsupported type %u\n", src0->type);
return HTP_STATUS_NO_SUPPORT;
}
const uint32_t total_dst_rows = dst->ne[1] * dst->ne[2] * dst->ne[3];
const uint32_t n_threads = MIN(octx->n_threads, total_dst_rows);
if (octx->flags & HTP_OPFLAGS_SKIP_COMPUTE) {
return HTP_STATUS_OK;
}
struct htp_repeat_context rctx = {
.octx = octx,
.nr0 = dst->ne[0] / src0->ne[0],
.nr1 = dst->ne[1] / src0->ne[1],
.nr2 = dst->ne[2] / src0->ne[2],
.nr3 = dst->ne[3] / src0->ne[3],
.nrows_per_thread = (total_dst_rows + n_threads - 1) / n_threads,
.total_dst_rows = total_dst_rows,
.type_size = type_size,
};
FARF(HIGH, "repeat: (%ux%ux%ux%u) -> (%ux%ux%ux%u) nr=(%u,%u,%u,%u)\n",
src0->ne[0], src0->ne[1], src0->ne[2], src0->ne[3],
dst->ne[0], dst->ne[1], dst->ne[2], dst->ne[3],
rctx.nr0, rctx.nr1, rctx.nr2, rctx.nr3);
worker_pool_run_func(octx->ctx->worker_pool, repeat_job_per_thread, &rctx, n_threads);
return HTP_STATUS_OK;
}