EngineX-Ascend/enginex-ascend-910-llama.cpp
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opencl: split ggml-opencl.cl into multiple files and cleanup (#12886)

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* opencl: refactor - split the kernel files

---------

Co-authored-by: Shangqing Gu <quic_shawngu@quicinc.com>

* opencl: split more kernels into separate files

* opencl: specify subgroup size instead of querying it

* opencl: refine Adreno cl compiler version parsing

* opencl: skip some kernels not used by Adreno on old compilers

* opencl: refine logic for selecting Adreno kernels

* opencl: refine Adreno cl compiler version

* opencl: cleanup preprocessor for kernels

* opencl: consider Adreno CL compiler on Windows

* opencl: add final newline for `mul_mv_f16_f16.cl`

---------

Co-authored-by: Shangqing Gu <quic_shawngu@quicinc.com>
This commit is contained in:
lhez
2025-04-15 12:26:00 -07:00
committed by GitHub
parent f8f820cc4d
commit 80f19b4186
43 changed files with 5021 additions and 4996 deletions
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96
ggml/src/ggml-opencl/kernels/rms_norm.cl Normal file
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#pragma OPENCL EXTENSION cl_khr_fp16 : enable
#ifdef cl_intel_subgroups
#pragma OPENCL EXTENSION cl_intel_subgroups : enable
#else
#pragma OPENCL EXTENSION cl_khr_subgroups : enable
#endif
#ifdef cl_intel_required_subgroup_size
#pragma OPENCL EXTENSION cl_intel_required_subgroup_size : enable
#define INTEL_GPU 1
#define REQD_SUBGROUP_SIZE_16 __attribute__((intel_reqd_sub_group_size(16)))
#define REQD_SUBGROUP_SIZE_32 __attribute__((intel_reqd_sub_group_size(32)))
#elif defined(cl_qcom_reqd_sub_group_size)
#pragma OPENCL EXTENSION cl_qcom_reqd_sub_group_size : enable
#define ADRENO_GPU 1
#define REQD_SUBGROUP_SIZE_64 __attribute__((qcom_reqd_sub_group_size("half")))
#define REQD_SUBGROUP_SIZE_128 __attribute__((qcom_reqd_sub_group_size("full")))
#endif
//------------------------------------------------------------------------------
// rms_norm
//------------------------------------------------------------------------------
// This kernel depends on subgroup size.
#ifdef INTEL_GPU
REQD_SUBGROUP_SIZE_32
#elif defined (ADRENO_GPU)
REQD_SUBGROUP_SIZE_64
#endif
kernel void kernel_rms_norm(
global void * src0,
ulong offset0,
global float * dst,
ulong offsetd,
int ne00,
int ne01,
int ne02,
int ne03,
ulong nb01,
ulong nb02,
ulong nb03,
float eps,
local float * sum // Note, the size depends on number of subgroups
) {
src0 = (global void*)((global char*)src0 + offset0);
dst = (global float*)((global char*)dst + offsetd);
int i03 = get_group_id(2);
int i02 = get_group_id(1);
int i01 = get_group_id(0);
global float4 * x = (global float4 *) ((global char *) src0 + i03*nb03 + i02*nb02 + i01*nb01);
global float * x_scalar = (global float *) x;
float4 sumf = 0;
float all_sum = 0;
// parallel sum
for (int i00 = get_local_id(0); i00 < ne00/4; i00 += get_local_size(0)) {
sumf += x[i00] * x[i00];
}
all_sum = sumf.s0 + sumf.s1 + sumf.s2 + sumf.s3;
all_sum = sub_group_reduce_add(all_sum);
if (get_sub_group_local_id() == 0) {
sum[get_sub_group_id()] = all_sum;
}
barrier(CLK_LOCAL_MEM_FENCE);
// broadcast
for (uint i = get_local_size(0) / get_max_sub_group_size() / 2; i > 0; i /= 2) {
if (get_local_id(0) < i) {
sum[get_local_id(0)] += sum[get_local_id(0) + i];
}
}
if (get_local_id(0) == 0) {
for (int i = 4 * (ne00 / 4); i < ne00; i++) {
sum[0] += x_scalar[i];
}
sum[0] /= ne00;
}
barrier(CLK_LOCAL_MEM_FENCE);
const float mean = sum[0];
const float scale = 1.0f/sqrt(mean + eps);
global float4 * y = (global float4 *) (dst + i03*ne02*ne01*ne00 + i02*ne01*ne00 + i01*ne00);
global float * y_scalar = (global float *) y;
for (int i00 = get_local_id(0); i00 < ne00/4; i00 += get_local_size(0)) {
y[i00] = x[i00] * scale;
}
if (get_local_id(0) == 0) {
for (int i00 = 4 * (ne00 / 4); i00 < ne00; i00++) {
y_scalar[i00] = x_scalar[i00] * scale;
}
}
}