diff --git a/ggml/src/CMakeLists.txt b/ggml/src/CMakeLists.txt
index 08b71d410d82e..8d96a04b57beb 100644
--- a/ggml/src/CMakeLists.txt
+++ b/ggml/src/CMakeLists.txt
@@ -490,7 +490,7 @@ if (GGML_SYCL)
         set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -fsycl-targets=nvptx64-nvidia-cuda")
         add_compile_definitions(GGML_SYCL_WARP_SIZE=32)
     else()
-        add_compile_definitions(GGML_SYCL_WARP_SIZE=32)
+        add_compile_definitions(GGML_SYCL_WARP_SIZE=16)
     endif()
 
     file(GLOB   GGML_HEADERS_SYCL "ggml-sycl/*.hpp")
diff --git a/ggml/src/ggml-sycl.cpp b/ggml/src/ggml-sycl.cpp
index 5d2cfdb71a5a2..77d41ddeee1de 100644
--- a/ggml/src/ggml-sycl.cpp
+++ b/ggml/src/ggml-sycl.cpp
@@ -906,6 +906,10 @@ static void soft_max_f32(const float * x, const float * mask, float * dst, const
 
     const int warp_id = item_ct1.get_local_id(2) / WARP_SIZE;
     const int lane_id = item_ct1.get_local_id(2) % WARP_SIZE;
+    const int nthreads = block_size;
+    const int nwarps = nthreads / WARP_SIZE;
+    int nreduce = nwarps / WARP_SIZE;
+
 
     float slope = 1.0f;
 
@@ -919,7 +923,7 @@ static void soft_max_f32(const float * x, const float * mask, float * dst, const
         slope = sycl::pow(base, float(exp));
     }
 
-    float * vals = vals_smem ? buf + WARP_SIZE : dst + rowx*ncols;
+    float *vals = vals_smem ? buf + std::max(nwarps, WARP_SIZE) : dst + rowx * ncols;
     float max_val = -INFINITY;
 
     for (int col0 = 0; col0 < ncols; col0 += block_size) {
@@ -943,6 +947,9 @@ static void soft_max_f32(const float * x, const float * mask, float * dst, const
     if (block_size > WARP_SIZE) {
         if (warp_id == 0) {
             buf[lane_id] = -INFINITY;
+            for (size_t i = 1; i < nreduce; i += 1)
+                buf[lane_id + i * WARP_SIZE] = -INFINITY;
+
         }
         item_ct1.barrier(sycl::access::fence_space::local_space);
 
@@ -952,6 +959,11 @@ static void soft_max_f32(const float * x, const float * mask, float * dst, const
         item_ct1.barrier(sycl::access::fence_space::local_space);
 
         max_val = buf[lane_id];
+        for (size_t i = 1; i < nreduce; i += 1)
+        {
+            max_val = std::max(max_val, buf[lane_id + i * WARP_SIZE]);
+        }
+
         max_val = warp_reduce_max(max_val, item_ct1);
     }
 
@@ -975,6 +987,9 @@ static void soft_max_f32(const float * x, const float * mask, float * dst, const
         item_ct1.barrier(sycl::access::fence_space::local_space);
         if (warp_id == 0) {
             buf[lane_id] = 0.f;
+            for (size_t i = 1; i < nreduce; i += 1)
+                buf[lane_id + i * WARP_SIZE] = 0.f;
+
         }
         item_ct1.barrier(sycl::access::fence_space::local_space);
 
@@ -984,6 +999,10 @@ static void soft_max_f32(const float * x, const float * mask, float * dst, const
         item_ct1.barrier(sycl::access::fence_space::local_space);
 
         tmp = buf[lane_id];
+        for (size_t i = 1; i < nreduce; i += 1)
+        {
+            tmp += buf[lane_id + i * WARP_SIZE];
+        }
         tmp = warp_reduce_sum(tmp, item_ct1);
     }
 
diff --git a/ggml/src/ggml-sycl/common.cpp b/ggml/src/ggml-sycl/common.cpp
index c0214329998b8..ad530689b0099 100644
--- a/ggml/src/ggml-sycl/common.cpp
+++ b/ggml/src/ggml-sycl/common.cpp
@@ -314,6 +314,7 @@ void sycl_device_mgr::detect_all_sycl_device_list() try {
         dpct::get_device_info(prop, device);
         work_group_sizes.push_back(prop.get_max_work_group_size());
         max_compute_units.push_back(prop.get_max_compute_units());
+        hw_familys.push_back(get_device_family(&device));
     }
     return;
 } catch (sycl::exception const &exc) {
@@ -498,4 +499,8 @@ int ggml_sycl_device_info::get_device_id(int device_index) {
     }
 }
 
+int ggml_sycl_device_info::hw_family(int device_id) {
+    return device_mgr->hw_familys[device_id];
+}
+
 //--ggml_sycl_device_info--
diff --git a/ggml/src/ggml-sycl/common.hpp b/ggml/src/ggml-sycl/common.hpp
index 5a2f1664dc9aa..8494f7f356051 100644
--- a/ggml/src/ggml-sycl/common.hpp
+++ b/ggml/src/ggml-sycl/common.hpp
@@ -20,6 +20,7 @@
 #include "dpct/helper.hpp"
 #include "ggml-sycl.h"
 #include "presets.hpp"
+#include "sycl_hw.hpp"
 
 #define GGML_COMMON_DECL_SYCL
 #define GGML_COMMON_IMPL_SYCL
@@ -188,6 +189,8 @@ class sycl_device_mgr {
     std::vector<sycl::device> devices;
     std::vector<int> max_compute_units;
     std::vector<int> work_group_sizes;
+    std::vector<int> hw_familys;
+
     sycl::queue *first_queue;
     std::vector<sycl::queue> _queues;
     std::vector<sycl::context> ctxs;
@@ -236,6 +239,7 @@ struct ggml_sycl_device_info {
     bool is_allowed_device(int device_id);
     const char* devices_list();
     int get_device_id(int device_index);
+    int hw_family(int device_id);
 };
 
 struct ggml_sycl_pool {
diff --git a/ggml/src/ggml-sycl/dmmv.cpp b/ggml/src/ggml-sycl/dmmv.cpp
index 927819281fd0a..663c83a2e7455 100644
--- a/ggml/src/ggml-sycl/dmmv.cpp
+++ b/ggml/src/ggml-sycl/dmmv.cpp
@@ -20,8 +20,10 @@ static void convert_f32(const void * vx, const int ib, const int iqs, dfloat2 &
 }
 
 template <int qk, int qr, dequantize_kernel_t dequantize_kernel>
-static void dequantize_mul_mat_vec(const void * __restrict__ vx, const dfloat * __restrict__ y, float * __restrict__ dst, const int ncols, const int nrows,
+static void dequantize_mul_mat_vec(const void * __restrict__ vx, const dfloat * __restrict__ y, float * __restrict__ dst,
+                                   const int ncols, const int nrows, const int warp_size,
                                    const sycl::nd_item<3> &item_ct1) {
+
     // qk = quantized weights per x block
     // qr = number of quantized weights per data value in x block
     const int row = item_ct1.get_group(2) * item_ct1.get_local_range(1) +
@@ -34,7 +36,7 @@ static void dequantize_mul_mat_vec(const void * __restrict__ vx, const dfloat *
     const int tid = item_ct1.get_local_id(2);
 
     const int iter_stride = 2*GGML_SYCL_DMMV_X;
-    const int vals_per_iter = iter_stride / WARP_SIZE; // num quantized vals per thread and i iter
+    const int vals_per_iter = iter_stride / warp_size; // num quantized vals per thread and i iter
     const int y_offset = qr == 1 ? 1 : qk/2;
 
 // partial sum for each thread
@@ -76,7 +78,7 @@ static void dequantize_mul_mat_vec(const void * __restrict__ vx, const dfloat *
 
     // sum up partial sums and write back result
 #pragma unroll
-    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
+    for (int mask = warp_size / 2; mask > 0; mask >>= 1) {
         tmp +=
             dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
     }
@@ -93,21 +95,32 @@ static void dequantize_mul_mat_vec(const void * __restrict__ vx, const dfloat *
 static void convert_mul_mat_vec_f16_sycl(const void *vx, const dfloat *y,
                                          float *dst, const int ncols,
                                          const int nrows,
-                                         dpct::queue_ptr stream) {
+                                         dpct::queue_ptr stream,
+                                         int device_id) {
     GGML_ASSERT(ncols % GGML_SYCL_DMMV_X == 0);
+    dpct::has_capability_or_fail(stream->get_device(), {sycl::aspect::fp16});
+
     const int block_num_y = (nrows + GGML_SYCL_MMV_Y - 1) / GGML_SYCL_MMV_Y;
     const sycl::range<3> block_nums(1, 1, block_num_y);
-    const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, WARP_SIZE);
-    {
-        dpct::has_capability_or_fail(stream->get_device(),
-                                     {sycl::aspect::fp16});
 
+    if (ggml_sycl_info().hw_family(device_id) == SYCL_HW_FAMILY_INTEL_IGPU) {
+        const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, WARP_32_SIZE);
         stream->parallel_for(
             sycl::nd_range<3>(block_nums * block_dims, block_dims),
-            [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
-                dequantize_mul_mat_vec<1, 1, convert_f16>(vx, y, dst, ncols,
-                                                          nrows, item_ct1);
-            });
+            [=](sycl::nd_item<3> item_ct1)
+                [[intel::reqd_sub_group_size(WARP_32_SIZE)]] {
+                    dequantize_mul_mat_vec<1, 1, convert_f16>(
+                        vx, y, dst, ncols, nrows, WARP_32_SIZE, item_ct1);
+                });
+    } else {
+        const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, WARP_SIZE);
+        stream->parallel_for(
+            sycl::nd_range<3>(block_nums * block_dims, block_dims),
+            [=](sycl::nd_item<3> item_ct1)
+                [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+                    dequantize_mul_mat_vec<1, 1, convert_f16>(
+                        vx, y, dst, ncols, nrows, WARP_SIZE, item_ct1);
+                });
     }
 }
 
@@ -227,7 +240,7 @@ static void dequantize_mul_mat_vec_q2_k(const void *__restrict__ vx,
 
     // sum up partial sums and write back result
 #pragma unroll
-    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
+    for (int mask = WARP_32_SIZE / 2; mask > 0; mask >>= 1) {
         tmp +=
             dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
     }
@@ -346,7 +359,7 @@ static void dequantize_mul_mat_vec_q3_k(const void *__restrict__ vx,
 
     // sum up partial sums and write back result
 #pragma unroll
-    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
+    for (int mask = WARP_32_SIZE / 2; mask > 0; mask >>= 1) {
         tmp +=
             dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
     }
@@ -499,7 +512,7 @@ static void dequantize_mul_mat_vec_q4_k(const void *__restrict__ vx,
 
     // sum up partial sums and write back result
 #pragma unroll
-    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
+    for (int mask = WARP_32_SIZE / 2; mask > 0; mask >>= 1) {
         tmp +=
             dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
     }
@@ -633,7 +646,7 @@ static void dequantize_mul_mat_vec_q5_k(const void *__restrict__ vx,
 
     // sum up partial sums and write back result
 #pragma unroll
-    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
+    for (int mask = WARP_32_SIZE / 2; mask > 0; mask >>= 1) {
         tmp +=
             dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
     }
@@ -748,7 +761,7 @@ static void dequantize_mul_mat_vec_q6_k(const void * __restrict__ vx, const floa
 
     // sum up partial sums and write back result
 #pragma unroll
-    for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
+    for (int mask = WARP_32_SIZE / 2; mask > 0; mask >>= 1) {
         tmp +=
             dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
     }
@@ -762,21 +775,31 @@ static void dequantize_mul_mat_vec_q6_k(const void * __restrict__ vx, const floa
 static void dequantize_mul_mat_vec_q4_0_sycl(const void *vx, const dfloat *y,
                                              float *dst, const int ncols,
                                              const int nrows,
-                                             dpct::queue_ptr stream) {
+                                             dpct::queue_ptr stream, int device_id) {
     GGML_ASSERT(ncols % GGML_SYCL_DMMV_X == 0);
     const int block_num_y = (nrows + GGML_SYCL_MMV_Y - 1) / GGML_SYCL_MMV_Y;
     // the number of rows may exceed maximum grid size in the y or z dimensions, use the x dimension instead
     const sycl::range<3> block_nums(1, 1, block_num_y);
-    const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, WARP_SIZE);
-    {
-        dpct::has_capability_or_fail(stream->get_device(),
-                                     {sycl::aspect::fp16});
+    dpct::has_capability_or_fail(stream->get_device(), {sycl::aspect::fp16});
+
+    if (ggml_sycl_info().hw_family(device_id) == SYCL_HW_FAMILY_INTEL_IGPU) {
+        // printf("dequantize_mul_mat_vec_q4_0_sycl warp_size=%d\n", WARP_32_SIZE);
+        const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, WARP_32_SIZE);
+        stream->parallel_for(
+            sycl::nd_range<3>(block_nums * block_dims, block_dims),
+            [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_32_SIZE)]] {
+                dequantize_mul_mat_vec<QK4_0, QR4_0, dequantize_q4_0>(
+                    vx, y, dst, ncols, nrows, WARP_32_SIZE, item_ct1);
+            });
 
+    } else {
+        // printf("dequantize_mul_mat_vec_q4_0_sycl warp_size=%d\n", WARP_SIZE);
+        const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, WARP_SIZE);
         stream->parallel_for(
             sycl::nd_range<3>(block_nums * block_dims, block_dims),
             [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                 dequantize_mul_mat_vec<QK4_0, QR4_0, dequantize_q4_0>(
-                    vx, y, dst, ncols, nrows, item_ct1);
+                    vx, y, dst, ncols, nrows, WARP_SIZE, item_ct1);
             });
     }
 }
@@ -784,20 +807,27 @@ static void dequantize_mul_mat_vec_q4_0_sycl(const void *vx, const dfloat *y,
 static void dequantize_mul_mat_vec_q4_1_sycl(const void *vx, const dfloat *y,
                                              float *dst, const int ncols,
                                              const int nrows,
-                                             dpct::queue_ptr stream) {
+                                             dpct::queue_ptr stream, int device_id) {
     GGML_ASSERT(ncols % GGML_SYCL_DMMV_X == 0);
     const int block_num_y = (nrows + GGML_SYCL_MMV_Y - 1) / GGML_SYCL_MMV_Y;
     const sycl::range<3> block_nums(1, 1, block_num_y);
-    const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, WARP_SIZE);
-    {
-        dpct::has_capability_or_fail(stream->get_device(),
-                                     {sycl::aspect::fp16});
+    dpct::has_capability_or_fail(stream->get_device(), {sycl::aspect::fp16});
 
+    if (ggml_sycl_info().hw_family(device_id) == SYCL_HW_FAMILY_INTEL_IGPU) {
+        const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, WARP_32_SIZE);
+        stream->parallel_for(
+            sycl::nd_range<3>(block_nums * block_dims, block_dims),
+            [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_32_SIZE)]] {
+                dequantize_mul_mat_vec<QK4_1, QR4_1, dequantize_q4_1>(
+                    vx, y, dst, ncols, nrows, WARP_32_SIZE, item_ct1);
+            });
+    } else {
+        const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, WARP_SIZE);
         stream->parallel_for(
             sycl::nd_range<3>(block_nums * block_dims, block_dims),
             [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                 dequantize_mul_mat_vec<QK4_1, QR4_1, dequantize_q4_1>(
-                    vx, y, dst, ncols, nrows, item_ct1);
+                    vx, y, dst, ncols, nrows, WARP_SIZE, item_ct1);
             });
     }
 }
@@ -805,20 +835,27 @@ static void dequantize_mul_mat_vec_q4_1_sycl(const void *vx, const dfloat *y,
 static void dequantize_mul_mat_vec_q5_0_sycl(const void *vx, const dfloat *y,
                                              float *dst, const int ncols,
                                              const int nrows,
-                                             dpct::queue_ptr stream) {
+                                             dpct::queue_ptr stream, int device_id) {
     GGML_ASSERT(ncols % GGML_SYCL_DMMV_X == 0);
     const int block_num_y = (nrows + GGML_SYCL_MMV_Y - 1) / GGML_SYCL_MMV_Y;
     const sycl::range<3> block_nums(1, 1, block_num_y);
-    const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, WARP_SIZE);
-    {
-        dpct::has_capability_or_fail(stream->get_device(),
-                                     {sycl::aspect::fp16});
+    dpct::has_capability_or_fail(stream->get_device(), {sycl::aspect::fp16});
 
+    if (ggml_sycl_info().hw_family(device_id) == SYCL_HW_FAMILY_INTEL_IGPU) {
+        const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, WARP_32_SIZE);
+        stream->parallel_for(
+            sycl::nd_range<3>(block_nums * block_dims, block_dims),
+            [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_32_SIZE)]] {
+                dequantize_mul_mat_vec<QK5_0, QR5_0, dequantize_q5_0>(
+                    vx, y, dst, ncols, nrows, WARP_32_SIZE, item_ct1);
+            });
+    } else {
+        const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, WARP_SIZE);
         stream->parallel_for(
             sycl::nd_range<3>(block_nums * block_dims, block_dims),
             [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                 dequantize_mul_mat_vec<QK5_0, QR5_0, dequantize_q5_0>(
-                    vx, y, dst, ncols, nrows, item_ct1);
+                    vx, y, dst, ncols, nrows, WARP_SIZE, item_ct1);
             });
     }
 }
@@ -826,20 +863,27 @@ static void dequantize_mul_mat_vec_q5_0_sycl(const void *vx, const dfloat *y,
 static void dequantize_mul_mat_vec_q5_1_sycl(const void *vx, const dfloat *y,
                                              float *dst, const int ncols,
                                              const int nrows,
-                                             dpct::queue_ptr stream) {
+                                             dpct::queue_ptr stream, int device_id) {
     GGML_ASSERT(ncols % GGML_SYCL_DMMV_X == 0);
     const int block_num_y = (nrows + GGML_SYCL_MMV_Y - 1) / GGML_SYCL_MMV_Y;
     const sycl::range<3> block_nums(1, 1, block_num_y);
-    const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, WARP_SIZE);
-    {
-        dpct::has_capability_or_fail(stream->get_device(),
-                                     {sycl::aspect::fp16});
+    dpct::has_capability_or_fail(stream->get_device(), {sycl::aspect::fp16});
 
+    if (ggml_sycl_info().hw_family(device_id) == SYCL_HW_FAMILY_INTEL_IGPU) {
+        const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, WARP_32_SIZE);
+        stream->parallel_for(
+            sycl::nd_range<3>(block_nums * block_dims, block_dims),
+            [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_32_SIZE)]] {
+                dequantize_mul_mat_vec<QK5_1, QR5_1, dequantize_q5_1>(
+                    vx, y, dst, ncols, nrows, WARP_32_SIZE, item_ct1);
+            });
+    } else {
+        const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, WARP_SIZE);
         stream->parallel_for(
             sycl::nd_range<3>(block_nums * block_dims, block_dims),
             [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                 dequantize_mul_mat_vec<QK5_1, QR5_1, dequantize_q5_1>(
-                    vx, y, dst, ncols, nrows, item_ct1);
+                    vx, y, dst, ncols, nrows, WARP_SIZE, item_ct1);
             });
     }
 }
@@ -847,20 +891,27 @@ static void dequantize_mul_mat_vec_q5_1_sycl(const void *vx, const dfloat *y,
 static void dequantize_mul_mat_vec_q8_0_sycl(const void *vx, const dfloat *y,
                                              float *dst, const int ncols,
                                              const int nrows,
-                                             dpct::queue_ptr stream) {
+                                             dpct::queue_ptr stream, int device_id) {
     GGML_ASSERT(ncols % GGML_SYCL_DMMV_X == 0);
     const int block_num_y = (nrows + GGML_SYCL_MMV_Y - 1) / GGML_SYCL_MMV_Y;
     const sycl::range<3> block_nums(1, 1, block_num_y);
-    const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, WARP_SIZE);
-    {
-        dpct::has_capability_or_fail(stream->get_device(),
-                                     {sycl::aspect::fp16});
+    dpct::has_capability_or_fail(stream->get_device(), {sycl::aspect::fp16});
 
+    if (ggml_sycl_info().hw_family(device_id) == SYCL_HW_FAMILY_INTEL_IGPU) {
+        const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, WARP_32_SIZE);
+        stream->parallel_for(
+            sycl::nd_range<3>(block_nums * block_dims, block_dims),
+            [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_32_SIZE)]] {
+                dequantize_mul_mat_vec<QK8_0, QR8_0, dequantize_q8_0>(
+                    vx, y, dst, ncols, nrows, WARP_32_SIZE, item_ct1);
+            });
+    } else {
+        const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, WARP_SIZE);
         stream->parallel_for(
             sycl::nd_range<3>(block_nums * block_dims, block_dims),
             [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                 dequantize_mul_mat_vec<QK8_0, QR8_0, dequantize_q8_0>(
-                    vx, y, dst, ncols, nrows, item_ct1);
+                    vx, y, dst, ncols, nrows, WARP_SIZE, item_ct1);
             });
     }
 }
@@ -873,10 +924,10 @@ static void dequantize_mul_mat_vec_q2_K_sycl(const void *vx, const float *y,
     const int ny = 2; // very slightly faster than 1 even when K_QUANTS_PER_ITERATION = 2
     const int block_num_y = (nrows + ny - 1) / ny;
     const sycl::range<3> block_nums(1, 1, block_num_y);
-    const sycl::range<3> block_dims(1, ny, WARP_SIZE);
+    const sycl::range<3> block_dims(1, ny, WARP_32_SIZE);
     stream->parallel_for(
         sycl::nd_range<3>(block_nums * block_dims, block_dims),
-        [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+        [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_32_SIZE)]] {
             dequantize_mul_mat_vec_q2_k(vx, y, dst, ncols, nrows, item_ct1);
         });
 }
@@ -889,10 +940,10 @@ static void dequantize_mul_mat_vec_q3_K_sycl(const void *vx, const float *y,
     const int ny = 2 / K_QUANTS_PER_ITERATION;
     const int block_num_y = (nrows + ny - 1) / ny;
     const sycl::range<3> block_nums(1, 1, block_num_y);
-    const sycl::range<3> block_dims(1, ny, WARP_SIZE);
+    const sycl::range<3> block_dims(1, ny, WARP_32_SIZE);
     stream->parallel_for(
         sycl::nd_range<3>(block_nums * block_dims, block_dims),
-        [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+        [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_32_SIZE)]] {
             dequantize_mul_mat_vec_q3_k(vx, y, dst, ncols, nrows, item_ct1);
         });
 }
@@ -905,10 +956,10 @@ static void dequantize_mul_mat_vec_q4_K_sycl(const void *vx, const float *y,
     const int ny = 2 / K_QUANTS_PER_ITERATION;
     const int block_num_y = (nrows + ny - 1) / ny;
     const sycl::range<3> block_nums(1, 1, block_num_y);
-    const sycl::range<3> block_dims(1, ny, WARP_SIZE);
+    const sycl::range<3> block_dims(1, ny, WARP_32_SIZE);
     stream->parallel_for(
         sycl::nd_range<3>(block_nums * block_dims, block_dims),
-        [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+        [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_32_SIZE)]] {
             dequantize_mul_mat_vec_q4_k(vx, y, dst, ncols, nrows, item_ct1);
         });
 }
@@ -918,10 +969,10 @@ static void dequantize_mul_mat_vec_q5_K_sycl(const void *vx, const float *y,
                                              const int nrows,
                                              dpct::queue_ptr stream) {
     GGML_ASSERT(ncols % QK_K == 0);
-    const sycl::range<3> block_dims(1, 1, WARP_SIZE);
+    const sycl::range<3> block_dims(1, 1, WARP_32_SIZE);
     stream->parallel_for(
         sycl::nd_range<3>(sycl::range<3>(1, 1, nrows) * block_dims, block_dims),
-        [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+        [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_32_SIZE)]] {
             dequantize_mul_mat_vec_q5_k(vx, y, dst, ncols, item_ct1);
         });
 }
@@ -934,10 +985,10 @@ static void dequantize_mul_mat_vec_q6_K_sycl(const void *vx, const float *y,
     const int ny = 2 / K_QUANTS_PER_ITERATION;
     const int block_num_y = (nrows + ny - 1) / ny;
     const sycl::range<3> block_nums(1, 1, block_num_y);
-    const sycl::range<3> block_dims(1, ny, WARP_SIZE);
+    const sycl::range<3> block_dims(1, ny, WARP_32_SIZE);
     stream->parallel_for(
         sycl::nd_range<3>(block_nums * block_dims, block_dims),
-        [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+        [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(WARP_32_SIZE)]] {
             dequantize_mul_mat_vec_q6_k(vx, y, dst, ncols, nrows, item_ct1);
         });
 }
@@ -976,19 +1027,19 @@ void ggml_sycl_op_dequantize_mul_mat_vec(
 
     switch (src0->type) {
         case GGML_TYPE_Q4_0:
-            dequantize_mul_mat_vec_q4_0_sycl(src0_dd_i, src1_dfloat, dst_dd_i, ne00, row_diff, stream);
+            dequantize_mul_mat_vec_q4_0_sycl(src0_dd_i, src1_dfloat, dst_dd_i, ne00, row_diff, stream, ctx.device);
             break;
         case GGML_TYPE_Q4_1:
-            dequantize_mul_mat_vec_q4_1_sycl(src0_dd_i, src1_dfloat, dst_dd_i, ne00, row_diff, stream);
+            dequantize_mul_mat_vec_q4_1_sycl(src0_dd_i, src1_dfloat, dst_dd_i, ne00, row_diff, stream, ctx.device);
             break;
         case GGML_TYPE_Q5_0:
-            dequantize_mul_mat_vec_q5_0_sycl(src0_dd_i, src1_dfloat, dst_dd_i, ne00, row_diff, stream);
+            dequantize_mul_mat_vec_q5_0_sycl(src0_dd_i, src1_dfloat, dst_dd_i, ne00, row_diff, stream, ctx.device);
             break;
         case GGML_TYPE_Q5_1:
-            dequantize_mul_mat_vec_q5_1_sycl(src0_dd_i, src1_dfloat, dst_dd_i, ne00, row_diff, stream);
+            dequantize_mul_mat_vec_q5_1_sycl(src0_dd_i, src1_dfloat, dst_dd_i, ne00, row_diff, stream, ctx.device);
             break;
         case GGML_TYPE_Q8_0:
-            dequantize_mul_mat_vec_q8_0_sycl(src0_dd_i, src1_dfloat, dst_dd_i, ne00, row_diff, stream);
+            dequantize_mul_mat_vec_q8_0_sycl(src0_dd_i, src1_dfloat, dst_dd_i, ne00, row_diff, stream, ctx.device);
             break;
         case GGML_TYPE_Q2_K:
             dequantize_mul_mat_vec_q2_K_sycl(src0_dd_i, src1_ddf_i, dst_dd_i, ne00, row_diff, stream);
@@ -1006,7 +1057,7 @@ void ggml_sycl_op_dequantize_mul_mat_vec(
             dequantize_mul_mat_vec_q6_K_sycl(src0_dd_i, src1_ddf_i, dst_dd_i, ne00, row_diff, stream);
             break;
         case GGML_TYPE_F16:
-            convert_mul_mat_vec_f16_sycl(src0_dd_i, src1_dfloat, dst_dd_i, ne00, row_diff, stream);
+            convert_mul_mat_vec_f16_sycl(src0_dd_i, src1_dfloat, dst_dd_i, ne00, row_diff, stream, ctx.device);
             break;
         default:
             printf("ggml_sycl_op_dequantize_mul_mat_vec unsupported GGML_TYPE %d\n", src0->type);
diff --git a/ggml/src/ggml-sycl/norm.cpp b/ggml/src/ggml-sycl/norm.cpp
index 3ad1131d6bacc..ee632ac3b69c6 100644
--- a/ggml/src/ggml-sycl/norm.cpp
+++ b/ggml/src/ggml-sycl/norm.cpp
@@ -57,6 +57,7 @@ static void group_norm_f32(const float* x, float* dst, const int group_size, con
     const int nwarps = nthreads / WARP_SIZE;
     assert(nwarps % WARP_SIZE == 0);
     start += item_ct1.get_local_id(2);
+    int nreduce = nwarps / WARP_SIZE;
 
     if (end >= ne_elements) {
         end = ne_elements;
@@ -87,7 +88,6 @@ static void group_norm_f32(const float* x, float* dst, const int group_size, con
         */
         item_ct1.barrier();
         tmp = 0.f;
-        int nreduce = nwarps / WARP_SIZE;
         for (size_t i = 0; i < nreduce; i += 1)
         {
             tmp += s_sum[lane_id + i * WARP_SIZE];
@@ -122,7 +122,11 @@ static void group_norm_f32(const float* x, float* dst, const int group_size, con
         better performance if there is no access to global memory.
         */
         item_ct1.barrier();
-        tmp = s_sum[lane_id];
+        tmp = 0.f;
+        for (size_t i = 0; i < nreduce; i += 1)
+        {
+            tmp += s_sum[lane_id + i * WARP_SIZE];
+        }
         tmp = warp_reduce_sum(tmp, item_ct1);
     }
 
@@ -186,13 +190,15 @@ static void norm_f32_sycl(const float* x, float* dst, const int ncols,
     if (ncols < 1024) {
         const sycl::range<3> block_dims(1, 1, WARP_SIZE);
         stream->submit([&](sycl::handler& cgh) {
+            sycl::local_accessor<sycl::float2, 1> s_sum_acc_ct1(
+                sycl::range<1>(32), cgh);
             cgh.parallel_for(
                 sycl::nd_range<3>(sycl::range<3>(1, 1, nrows) * block_dims,
                     block_dims),
                 [=](sycl::nd_item<3> item_ct1)
                 [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                     norm_f32(x, dst, ncols, eps, item_ct1,
-                        nullptr, WARP_SIZE);
+                        s_sum_acc_ct1.get_pointer(), WARP_SIZE);
                 });
             });
     }
@@ -227,6 +233,8 @@ static void group_norm_f32_sycl(const float* x, float* dst,
     if (group_size < 1024) {
         const sycl::range<3> block_dims(1, 1, WARP_SIZE);
         stream->submit([&](sycl::handler& cgh) {
+            sycl::local_accessor<float, 1> s_sum_acc_ct1(sycl::range<1>(32),
+                                                         cgh);
             const float eps_ct4 = eps;
             cgh.parallel_for(
                 sycl::nd_range<3>(sycl::range<3>(1, 1, num_groups) * block_dims,
@@ -235,7 +243,7 @@ static void group_norm_f32_sycl(const float* x, float* dst,
                 [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                     group_norm_f32(
                         x, dst, group_size, ne_elements, eps_ct4, item_ct1,
-                        nullptr, WARP_SIZE);
+                        s_sum_acc_ct1.get_pointer(), WARP_SIZE);
                 });
             });
     }
@@ -275,13 +283,15 @@ static void rms_norm_f32_sycl(const float* x, float* dst, const int ncols,
     if (ncols < 1024) {
         const sycl::range<3> block_dims(1, 1, WARP_SIZE);
         stream->submit([&](sycl::handler& cgh) {
+            sycl::local_accessor<float, 1> s_sum_acc_ct1(sycl::range<1>(32),
+                                                         cgh);
             cgh.parallel_for(
                 sycl::nd_range<3>(sycl::range<3>(1, 1, nrows) * block_dims,
                     block_dims),
                 [=](sycl::nd_item<3> item_ct1)
                 [[intel::reqd_sub_group_size(WARP_SIZE)]] {
                     rms_norm_f32(x, dst, ncols, eps, item_ct1,
-                        nullptr, WARP_SIZE);
+                        s_sum_acc_ct1.get_pointer(), WARP_SIZE);
                 });
             });
     }
diff --git a/ggml/src/ggml-sycl/presets.hpp b/ggml/src/ggml-sycl/presets.hpp
index c09c75dc7c73c..ca335d78a260e 100644
--- a/ggml/src/ggml-sycl/presets.hpp
+++ b/ggml/src/ggml-sycl/presets.hpp
@@ -17,6 +17,8 @@
 #define GGML_SYCL_MAX_BUFFERS       256
 
 #define WARP_SIZE GGML_SYCL_WARP_SIZE
+#define WARP_32_SIZE 32
+
 #define MATRIX_ROW_PADDING 512 // last row of quant. matrices is a multiple of this to avoid out-of-bounds memory accesses
 
 #define SYCL_GELU_BLOCK_SIZE 256
@@ -62,4 +64,5 @@ static_assert(K_QUANTS_PER_ITERATION == 1 || K_QUANTS_PER_ITERATION == 2, "K_QUA
 
 #define MUL_MAT_SRC1_COL_STRIDE 128
 
+
 #endif // GGML_SYCL_PRESETS_HPP
diff --git a/ggml/src/ggml-sycl/sycl_hw.cpp b/ggml/src/ggml-sycl/sycl_hw.cpp
new file mode 100644
index 0000000000000..21e0c2af90191
--- /dev/null
+++ b/ggml/src/ggml-sycl/sycl_hw.cpp
@@ -0,0 +1,17 @@
+#include "sycl_hw.hpp"
+
+bool is_in_vector(const std::vector<int> &vec, int item) {
+  return std::find(vec.begin(), vec.end(), item) != vec.end();
+}
+
+SYCL_HW_FAMILY get_device_family(sycl::device *device_ptr) {
+  auto id = device_ptr->get_info<sycl::ext::intel::info::device::device_id>();
+  auto id_prefix = id & 0xff00;
+
+  if (is_in_vector(Xe_Iris_IDs, id_prefix) or is_in_vector(UHD_IDs, id_prefix)) {
+    return SYCL_HW_FAMILY_INTEL_IGPU;
+  } else {
+    std::cerr << "No support PCI_ID: " << std::hex << id << std::endl;
+    return SYCL_HW_FAMILY_UNKNOWN;
+  }
+}
diff --git a/ggml/src/ggml-sycl/sycl_hw.hpp b/ggml/src/ggml-sycl/sycl_hw.hpp
new file mode 100644
index 0000000000000..81944475663a4
--- /dev/null
+++ b/ggml/src/ggml-sycl/sycl_hw.hpp
@@ -0,0 +1,24 @@
+#ifndef SYCL_HW_HPP
+#define SYCL_HW_HPP
+
+#include <algorithm>
+#include <stdio.h>
+#include <vector>
+
+
+#include <sycl/sycl.hpp>
+
+// const int Xe_ARC[] = {0x5600, 0x4f};
+const std::vector<int> Xe_Iris_IDs = {0x4900, 0xa700};
+const std::vector<int> UHD_IDs = {0x4600};
+
+enum SYCL_HW_FAMILY {
+  SYCL_HW_FAMILY_UNKNOWN = -1,
+  SYCL_HW_FAMILY_INTEL_IGPU = 0
+};
+
+bool is_in_vector(std::vector<int> &vec, int item);
+
+SYCL_HW_FAMILY get_device_family(sycl::device *device_ptr);
+
+#endif // SYCL_HW_HPP