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sycl: set fattn_vec_nthreads to 256 for Battlemage (#25205)

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Currently detects lunarlake + battlemage / xe2 and
sets the value to 256.

Keeps default at 128, Intel's ARC Alchemist's prefered value.
This commit is contained in:
Titaniumtown
2026-07-14 12:00:00 +03:00
committed by GitHub
parent 14d3ba45f3
commit c1063ac9d7
1 changed files with 27 additions and 19 deletions
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ggml/src/ggml-sycl/fattn-vec.hpp
+27 -19
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@@ -15,13 +15,11 @@
namespace syclex = sycl::ext::oneapi::experimental;
static int ggml_sycl_fattn_vec_get_nthreads_host(const int cc) {
return 128;
GGML_UNUSED(cc);
}
static constexpr int ggml_sycl_fattn_vec_get_nthreads_device() {
return 128;
static int ggml_sycl_fattn_vec_get_nthreads_device(gpu_arch arch) {
// Xe2 (Battlemage, Lunar Lake) runs the flash-attention vec kernel best with a 256-thread work group.
return (arch == gpu_arch::intel_gpu_bmg_g21 ||
arch == gpu_arch::intel_gpu_bmg_g31 ||
arch == gpu_arch::intel_gpu_lnl_m) ? 256 : 128;
}
// Currenlty llvm with the amdgcn target dose not support unrolling loops
@@ -36,7 +34,8 @@ template <int D,
int type_K,
int type_V,
bool use_logit_softcap,
int warp_size> // D == head size
int warp_size,
int nthreads> // D == head size
static void flash_attn_ext_vec(const char* __restrict__ Q,
const char* __restrict__ K,
const char* __restrict__ V,
@@ -99,7 +98,6 @@ static void flash_attn_ext_vec(const char* __restrict__ Q,
constexpr int nthreads_KQ_q = (D/4 < warp_size ? D/4 : warp_size);
constexpr int nthreads_V_q = (D/4 < warp_size ? D/4 : warp_size);
constexpr int nthreads = ggml_sycl_fattn_vec_get_nthreads_device();
constexpr int nthreads_KQ = type_K == GGML_TYPE_F16 ? 128 / cpy_nb : nthreads_KQ_q;
constexpr int nthreads_V = type_V == GGML_TYPE_F16 ? 128 / cpy_nb : nthreads_V_q;
@@ -581,24 +579,34 @@ static void flash_attn_ext_vec(const char* __restrict__ Q,
#endif // __clang__
template <int D, int cols_per_block, int type_K, int type_V, bool use_logit_softcap>
void ggml_sycl_flash_attn_ext_vec_case_impl(ggml_backend_sycl_context & ctx, ggml_tensor * dst) {
const int warp_size = WARP_16_SIZE; //better performance than WARP_32_SIZE
const int cc = ggml_sycl_info().devices[ggml_sycl_get_device()].cc;
const int nthreads = ggml_sycl_fattn_vec_get_nthreads_host(cc);
const int nwarps = nthreads / warp_size;
constexpr int warp_size = WARP_16_SIZE; //better performance than WARP_32_SIZE
const bool need_f16_K = type_K == GGML_TYPE_F16;
const bool need_f16_V = type_V == GGML_TYPE_F16;
constexpr size_t nbytes_shared = 0;
launch_fattn<D, cols_per_block, 1,
flash_attn_ext_vec<D, cols_per_block, type_K, type_V,
use_logit_softcap, warp_size>, warp_size>(
ctx, dst, nwarps, nbytes_shared, D, need_f16_K, need_f16_V, false);
const auto arch = ggml_sycl_info().devices[ctx.device].hw_info.arch;
const int nthreads = ggml_sycl_fattn_vec_get_nthreads_device(arch);
// 256 threads would overflow the 64 KB work-group local memory at D == 512, so keep 128 there.
if (D <= 256 && nthreads == 256) {
constexpr int nthreads_hw = 256;
constexpr int nwarps = nthreads_hw / warp_size;
launch_fattn<D, cols_per_block, 1,
flash_attn_ext_vec<D, cols_per_block, type_K, type_V,
use_logit_softcap, warp_size, nthreads_hw>, warp_size>(
ctx, dst, nwarps, nbytes_shared, D, need_f16_K, need_f16_V, false);
} else {
constexpr int nthreads_hw = 128;
constexpr int nwarps = nthreads_hw / warp_size;
launch_fattn<D, cols_per_block, 1,
flash_attn_ext_vec<D, cols_per_block, type_K, type_V,
use_logit_softcap, warp_size, nthreads_hw>, warp_size>(
ctx, dst, nwarps, nbytes_shared, D, need_f16_K, need_f16_V, false);
}
}
template <int D, int type_K, int type_V>