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sycl: FWHT for widths above 512 and Kronecker sizes (port of upstream #28254, #29243) #302

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bri-prism merged 2 commits into from
Oct 2, 2026
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sycl: FWHT for widths above 512 and Kronecker sizes (port of upstream #28254, #29243) #302

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8739beb
sycl : fix test-backend-ops CI break && restore Kronecker product FWH…
philip-jingxin Sep 5, 2026
c69d674
sycl: FWHT kernels for block widths above 512 (#29243)
bri-prism Sep 27, 2026
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285 changes: 285 additions & 0 deletions ggml/src/ggml-sycl/fwht.cpp
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Original file line number Diff line number Diff line change
@@ -1,6 +1,50 @@
#include "fwht.hpp"

#include <cmath>
#define P 1.0f
#define N -1.0f

// constant Hadamard matrix via Paley I construction
static constexpr float H12[12][12] = {
{ P, P, P, P, P, P, P, P, P, P, P, P },
{ P, N, P, N, P, P, P, N, N, N, P, N },
{ P, N, N, P, N, P, P, P, N, N, N, P },
{ P, P, N, N, P, N, P, P, P, N, N, N },
{ P, N, P, N, N, P, N, P, P, P, N, N },
{ P, N, N, P, N, N, P, N, P, P, P, N },
{ P, N, N, N, P, N, N, P, N, P, P, P },
{ P, P, N, N, N, P, N, N, P, N, P, P },
{ P, P, P, N, N, N, P, N, N, P, N, P },
{ P, P, P, P, N, N, N, P, N, N, P, N },
{ P, N, P, P, P, N, N, N, P, N, N, P },
{ P, P, N, P, P, P, N, N, N, P, N, N }
};

static constexpr float H20[20][20] = {
{ P, P, P, P, P, P, P, P, P, P, P, P, P, P, P, P, P, P, P, P },
{ P, N, P, N, N, P, P, P, P, N, P, N, P, N, N, N, N, P, P, N },
{ P, N, N, P, N, N, P, P, P, P, N, P, N, P, N, N, N, N, P, P },
{ P, P, N, N, P, N, N, P, P, P, P, N, P, N, P, N, N, N, N, P },
{ P, P, P, N, N, P, N, N, P, P, P, P, N, P, N, P, N, N, N, N },
{ P, N, P, P, N, N, P, N, N, P, P, P, P, N, P, N, P, N, N, N },
{ P, N, N, P, P, N, N, P, N, N, P, P, P, P, N, P, N, P, N, N },
{ P, N, N, N, P, P, N, N, P, N, N, P, P, P, P, N, P, N, P, N },
{ P, N, N, N, N, P, P, N, N, P, N, N, P, P, P, P, N, P, N, P },
{ P, P, N, N, N, N, P, P, N, N, P, N, N, P, P, P, P, N, P, N },
{ P, N, P, N, N, N, N, P, P, N, N, P, N, N, P, P, P, P, N, P },
{ P, P, N, P, N, N, N, N, P, P, N, N, P, N, N, P, P, P, P, N },
{ P, N, P, N, P, N, N, N, N, P, P, N, N, P, N, N, P, P, P, P },
{ P, P, N, P, N, P, N, N, N, N, P, P, N, N, P, N, N, P, P, P },
{ P, P, P, N, P, N, P, N, N, N, N, P, P, N, N, P, N, N, P, P },
{ P, P, P, P, N, P, N, P, N, N, N, N, P, P, N, N, P, N, N, P },
{ P, P, P, P, P, N, P, N, P, N, N, N, N, P, P, N, N, P, N, N },
{ P, N, P, P, P, P, N, P, N, P, N, N, N, N, P, P, N, N, P, N },
{ P, N, N, P, P, P, P, N, P, N, P, N, N, N, N, P, P, N, N, P },
{ P, P, N, N, P, P, P, P, N, P, N, P, N, N, N, N, P, P, N, N }
};

#undef P
#undef N

template <int N>
static void fwht_kernel(const float * __restrict__ src, float * __restrict__ dst, const int64_t n_rows,
Expand Down Expand Up @@ -80,6 +124,223 @@ static void launch_fwht(const float * src, float * dst, const int64_t n_rows, co
});
}

// Wide blocks: one row per work-group instead of per sub-group, so each work-item
// keeps N/NT values rather than N/WARP_SIZE. Butterflies below the sub-group width
// still shuffle; those up to NT go through work-group local memory; the rest stay
// in registers.
template <int N, int NT>
static void fwht_kernel_wide(const float * __restrict__ src,
float * __restrict__ dst,
const int64_t n_rows,
const float scale,
const sycl::nd_item<2> & item,
float * smem) {
const int64_t r = item.get_global_id(0);
if (r >= n_rows) {
return;
}

src += r * N;
dst += r * N;

constexpr int el_w = N / NT;
static_assert(el_w >= 1 && N % NT == 0, "row must be a whole number of work-group widths");

const int tid = item.get_local_id(1);

float reg[el_w];
#pragma unroll
for (int i = 0; i < el_w; ++i) {
reg[i] = src[i * NT + tid] * scale;
}

const sycl::sub_group sg = item.get_sub_group();
const int lane = sg.get_local_linear_id();

// Butterflies inside the sub-group, same pattern as the narrow kernel.
#pragma unroll
for (int h = 1; h < WARP_SIZE; h *= 2) {
#pragma unroll
for (int j = 0; j < el_w; ++j) {
const float val = reg[j];
const float val2 = dpct::permute_sub_group_by_xor(sg, val, h, WARP_SIZE);

reg[j] = (lane & h) == 0 ? val + val2 : val2 - val;
}
}

// Butterflies from the sub-group width up to NT: the partner lane is outside
// this sub-group, so it goes through work-group local memory instead of a shuffle.
for (int h = WARP_SIZE; h < NT; h *= 2) {
#pragma unroll
for (int j = 0; j < el_w; ++j) {
smem[j * NT + tid] = reg[j];
}
item.barrier(sycl::access::fence_space::local_space);
#pragma unroll
for (int j = 0; j < el_w; ++j) {
const float val = reg[j];
const float val2 = smem[j * NT + (tid ^ h)];
reg[j] = (tid & h) == 0 ? val + val2 : val2 - val;
}
item.barrier(sycl::access::fence_space::local_space);
}

// Butterflies across registers: h is a multiple of NT, so the partner of element
// i*NT + tid lives in reg[i + h/NT] on the same work-item.
for (int h = NT; h < N; h *= 2) {
const int step = h / NT;
for (int j = 0; j < el_w; j += 2 * step) {
for (int k = 0; k < step; ++k) {
const float x = reg[j + k];
const float y = reg[j + k + step];

reg[j + k] = x + y;
reg[j + k + step] = x - y;
}
}
}

#pragma unroll
for (int i = 0; i < el_w; ++i) {
dst[i * NT + tid] = reg[i];
}
}

template <int N, int NT>
static void launch_fwht_wide(const float * src,
float * dst,
const int64_t n_rows,
const float scale,
dpct::queue_ptr stream) {
const sycl::range<2> global(n_rows, NT);
const sycl::range<2> local(1, NT);

stream->submit([&](sycl::handler & cgh) {
sycl::local_accessor<float, 1> smem(sycl::range<1>(N), cgh);
cgh.parallel_for(sycl::nd_range<2>(global, local),
[=](sycl::nd_item<2> item) [[sycl::reqd_sub_group_size(WARP_SIZE)]] {
fwht_kernel_wide<N, NT>(src, dst, n_rows, scale, item, get_pointer(smem));
});
});
}

template <int N, int m>
static void kronecker_kernel(const float * __restrict__ src,
float * __restrict__ dst,
const int64_t n_rows,
const float scale,
const sycl::nd_item<2> & item) {
static_assert(m == 12 || m == 20, "block size has to be 12 or 20.");

const sycl::sub_group sg = item.get_sub_group();

const int64_t r = item.get_global_id(0);
if (r >= n_rows) {
return;
}

src += r * N;
dst += r * N;

constexpr int blocks_per_group = N / m;
constexpr int el_w = blocks_per_group / WARP_SIZE;
static_assert(el_w >= 1 && blocks_per_group % WARP_SIZE == 0, "blocks_per_group must be a multiple of WARP_SIZE");
float reg[el_w * m];
const int lane = sg.get_local_linear_id();

#pragma unroll
for (int i = 0; i < el_w; ++i) {
const int b_idx = i * WARP_SIZE + lane;

#pragma unroll
for (int j = 0; j < m; ++j) {
reg[i * m + j] = src[b_idx * m + j] * scale;
}
}

#pragma unroll
for (int b = 0; b < el_w; ++b) {
float z[m] = { 0.0f };

#pragma unroll
for (int i = 0; i < m; ++i) {
#pragma unroll
for (int j = 0; j < m; ++j) {
const float h = (m == 12 ? H12[j][i] : H20[j][i]);
z[i] += reg[b * m + j] * h;
}
}

#pragma unroll
for (int i = 0; i < m; ++i) {
reg[b * m + i] = z[i];
}
}

#pragma unroll
for (int h = 1; h < WARP_SIZE; h *= 2) {
#pragma unroll
for (int j = 0; j < el_w; ++j) {
#pragma unroll
for (int k = 0; k < m; ++k) {
const float val = reg[j * m + k];
const float val2 = dpct::permute_sub_group_by_xor(sg, val, h, WARP_SIZE);

reg[j * m + k] = (lane & h) == 0 ? val + val2 : val2 - val;
}
}
}

#pragma unroll
for (int h = WARP_SIZE; h < blocks_per_group; h *= 2) {
const int step = h / WARP_SIZE;
#pragma unroll
for (int j = 0; j < el_w; j += 2 * step) {
#pragma unroll
for (int s = 0; s < step; ++s) {
#pragma unroll
for (int k = 0; k < m; ++k) {
const float x = reg[(j + s) * m + k];
const float y = reg[(j + s + step) * m + k];

reg[(j + s) * m + k] = x + y;
reg[(j + s + step) * m + k] = x - y;
}
}
}
}

#pragma unroll
for (int i = 0; i < el_w; ++i) {
const int b_idx = i * WARP_SIZE + lane;
#pragma unroll
for (int k = 0; k < m; ++k) {
dst[b_idx * m + k] = reg[i * m + k];
}
}
}

template <int N, int m>
static void launch_kronecker(const float * src,
float * dst,
const int64_t n_rows,
const float scale,
dpct::queue_ptr stream) {
constexpr int rows_per_block = 4;

const int64_t num_blocks = (n_rows + rows_per_block - 1) / rows_per_block;

// dim 1 is the fastest-varying, so a sub-group is exactly one row's WARP_SIZE lanes.
const sycl::range<2> global(num_blocks * rows_per_block, WARP_SIZE);
const sycl::range<2> local(rows_per_block, WARP_SIZE);

stream->parallel_for(sycl::nd_range<2>(global, local),
[=](sycl::nd_item<2> item) [[sycl::reqd_sub_group_size(WARP_SIZE)]] {
kronecker_kernel<N, m>(src, dst, n_rows, scale, item);
});
}

bool ggml_sycl_op_fwht(ggml_backend_sycl_context & ctx, const ggml_tensor * src, ggml_tensor * dst) {
if (src->type != GGML_TYPE_F32 || dst->type != GGML_TYPE_F32) {
return false;
Expand Down Expand Up @@ -113,6 +374,30 @@ bool ggml_sycl_op_fwht(ggml_backend_sycl_context & ctx, const ggml_tensor * src,
case 512:
launch_fwht<512>(src_d, dst_d, rows, scale, stream);
return true;
case 384:
launch_kronecker<384, 12>(src_d, dst_d, rows, scale, stream);
return true;
case 768:
launch_kronecker<768, 12>(src_d, dst_d, rows, scale, stream);
return true;
case 640:
launch_kronecker<640, 20>(src_d, dst_d, rows, scale, stream);
return true;
case 1280:
launch_kronecker<1280, 20>(src_d, dst_d, rows, scale, stream);
return true;
case 1024:
launch_fwht_wide<1024, 256>(src_d, dst_d, rows, scale, stream);
return true;
case 2048:
launch_fwht_wide<2048, 256>(src_d, dst_d, rows, scale, stream);
return true;
case 4096:
launch_fwht_wide<4096, 256>(src_d, dst_d, rows, scale, stream);
return true;
case 8192:
launch_fwht_wide<8192, 256>(src_d, dst_d, rows, scale, stream);
return true;
default:
return false;
}
Expand Down
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