Files
llama.cpp/ggml/src/ggml-metal/kernels/reduce.metal
T
b615f5b4bd metal: per-op source split + parallel compile (#26561)
* metal : per-op source split + parallel compile (#24021)

* preliminary extract common header

* op source split

* split metallib into 8 libs && load in parallel

* derive kernel->library routing from functionNames

* x-macro lib list + underscore filenames, dedup QK_NL, MRC fixes

* op source split 8 to 20

* improve robustness of source fallback

* clean up

* change bool -> atomic_bool

* only prepend headers that source actually includes

* no semaphore, use GCD global queue

* dedup library compile path, fix NSError lifetime, rename gla

* relocate upstream concat/rope_back/repeat kernel changes into split files

* move ggml-common.h from common.h into dequantize.h to shrink binary size

---------

Co-authored-by: lvyichen <lvyichen@stepfun.com>

* metal: add col2im_1d op (f32/f16/bf16) (#25176)

* metal : add set_rows with src0 f16 (#25434)

* metal : add CONV_2D_DW (depthwise convolution) support (#21565)

* metal : add Q2_0 support (#25419)

* metal: fuse snake activation (mul, sin, sqr, mul, add) (#25459)

* ggml-metal: FWHT kernel for metal backend (#25924)

* metal : port new kernels into the split sources

Move the kernels added on master after the split (lightning indexer,
DSv4 hyper-connections, silu_back, f16 bin ops, TQ2_0, the flash-attn KV
dequantization pass, rope offset/inplace, ssm_scan rollback, packed q8_0
dequantization and the tensor-API mat-mat K clamp) into the corresponding
kernels/*.metal sources. Copied verbatim, no functional change.

---------

Co-authored-by: lvyichen <lvyichen@stepfun.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2026-08-24 19:16:13 +03:00

229 lines
6.3 KiB
Metal

#include "common.h"
kernel void kernel_op_sum_f32(
constant ggml_metal_kargs_sum & args,
device const float * src0,
device float * dst,
threadgroup float * shmem_f32 [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
if (args.np == 0) {
return;
}
// TODO: become function constant
const uint nsg = (ntg.x + 31) / 32;
float sumf = 0;
for (uint64_t i0 = tpitg.x; i0 < args.np; i0 += ntg.x) {
sumf += src0[i0];
}
sumf = simd_sum(sumf);
if (tiisg == 0) {
shmem_f32[sgitg] = sumf;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
float total = 0;
if (sgitg == 0) {
float v = 0;
if (tpitg.x < nsg) {
v = shmem_f32[tpitg.x];
}
total = simd_sum(v);
if (tpitg.x == 0) {
dst[0] = total;
}
}
}
constant short FC_sum_rows_op [[function_constant(FC_SUM_ROWS + 0)]];
template <typename T0, typename T>
kernel void kernel_sum_rows_impl(
constant ggml_metal_kargs_sum_rows & args,
device const char * src0,
device char * dst,
threadgroup char * shmem [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
#define FC_OP FC_sum_rows_op
const int i3 = tgpig.z;
const int i2 = tgpig.y;
const int i1 = tgpig.x;
threadgroup T0 * shmem_t = (threadgroup T0 *) shmem;
if (sgitg == 0) {
shmem_t[tiisg] = 0.0f;
}
device const T0 * src_row = (device const T0 *) (src0 + i1*args.nb01 + i2*args.nb02 + i3*args.nb03);
device T * dst_row = (device T *) (dst + i1*args.nb1 + i2*args.nb2 + i3*args.nb3);
T0 sumf = T0(0.0f);
for (int64_t i0 = tpitg.x; i0 < args.ne00; i0 += ntg.x) {
sumf += src_row[i0];
}
sumf = simd_sum(sumf);
threadgroup_barrier(mem_flags::mem_threadgroup);
if (tiisg == 0) {
shmem_t[sgitg] = sumf;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
sumf = shmem_t[tiisg];
sumf = simd_sum(sumf);
if (tpitg.x == 0) {
if (FC_OP == OP_SUM_ROWS_NUM_MEAN) {
if (is_same<float4, T0>::value) {
dst_row[0] = sum(sumf) / (4*args.ne00);
} else {
dst_row[0] = sum(sumf) / args.ne00;
}
} else {
dst_row[0] = sum(sumf);
}
}
#undef FC_OP
}
typedef decltype(kernel_sum_rows_impl<float, float>) kernel_sum_rows_t;
template [[host_name("kernel_sum_rows_f32_f32")]] kernel kernel_sum_rows_t kernel_sum_rows_impl<float, float>;
template [[host_name("kernel_sum_rows_f32_f32_4")]] kernel kernel_sum_rows_t kernel_sum_rows_impl<float4, float>;
template<typename T>
kernel void kernel_cumsum_blk(
constant ggml_metal_kargs_cumsum_blk & args,
device const char * src0,
device char * tmp,
device char * dst,
threadgroup char * shmem [[threadgroup(0)]],
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
const int ib = tgpig[0]/args.ne01;
const int i00 = ib*ntg.x;
const int i01 = tgpig[0]%args.ne01;
const int i02 = tgpig[1];
const int i03 = tgpig[2];
device const float * src0_row = (device const float *) (src0 +
args.nb01*i01 +
args.nb02*i02 +
args.nb03*i03);
threadgroup float * shmem_f32 = (threadgroup float *) shmem;
float v = 0.0f;
if (i00 + tpitg.x < args.ne00) {
v = src0_row[i00 + tpitg.x];
}
float s = simd_prefix_inclusive_sum(v);
if (tiisg == N_SIMDWIDTH - 1) {
shmem_f32[sgitg] = s;
}
threadgroup_barrier(mem_flags::mem_threadgroup);
if (sgitg == 0) {
shmem_f32[tiisg] = simd_prefix_exclusive_sum(shmem_f32[tiisg]);
}
threadgroup_barrier(mem_flags::mem_threadgroup);
s += shmem_f32[sgitg];
device float * dst_row = (device float *) dst +
args.ne00*i01 +
args.ne00*args.ne01*i02 +
args.ne00*args.ne01*args.ne02*i03;
if (i00 + tpitg.x < args.ne00) {
dst_row[i00 + tpitg.x] = s;
}
if (args.outb && tpitg.x == ntg.x - 1) {
device float * tmp_row = (device float *) tmp +
args.net0*i01 +
args.net0*args.net1*i02 +
args.net0*args.net1*args.net2*i03;
tmp_row[ib] = s;
}
}
typedef decltype(kernel_cumsum_blk<float>) kernel_cumsum_blk_t;
template [[host_name("kernel_cumsum_blk_f32")]] kernel kernel_cumsum_blk_t kernel_cumsum_blk<float>;
template<typename T>
kernel void kernel_cumsum_add(
constant ggml_metal_kargs_cumsum_add & args,
device const char * tmp,
device char * dst,
uint3 tgpig[[threadgroup_position_in_grid]],
ushort3 tpitg[[thread_position_in_threadgroup]],
ushort sgitg[[simdgroup_index_in_threadgroup]],
ushort tiisg[[thread_index_in_simdgroup]],
ushort3 ntg[[threads_per_threadgroup]]) {
const int ib = tgpig[0]/args.ne01;
if (ib == 0) {
return;
}
const int i00 = ib*ntg.x;
const int i01 = tgpig[0]%args.ne01;
const int i02 = tgpig[1];
const int i03 = tgpig[2];
device const float * tmp_row = (device const float *) (tmp +
args.nbt1*i01 +
args.nbt2*i02 +
args.nbt3*i03);
device float * dst_row = (device float *) dst +
args.ne00*i01 +
args.ne00*args.ne01*i02 +
args.ne00*args.ne01*args.ne02*i03;
if (i00 + tpitg.x < args.ne00) {
dst_row[i00 + tpitg.x] += tmp_row[ib - 1];
}
}
typedef decltype(kernel_cumsum_add<float>) kernel_cumsum_add_t;
template [[host_name("kernel_cumsum_add_f32")]] kernel kernel_cumsum_add_t kernel_cumsum_add<float>;