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Merged
pull merged 4 commits into from
Apr 13, 2026
Merged

[pull] master from ggml-org:master #1072

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9f5e1ed
CUDA: Limit DeviceSegmentedSort to immediate mode (#21718)
ORippler Apr 13, 2026
ce8fd4b
server: Expose build_info in router mode (#21835)
gaspardpetit Apr 13, 2026
aa00911
common : add download cancellation and temp file cleanup (#21813)
angt Apr 13, 2026
75f3bc9
vulkan: Flash Attention DP4A shader for quantized KV cache (#20797)
0cc4m Apr 13, 2026
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12 changes: 12 additions & 0 deletions common/download.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -258,6 +258,9 @@ static bool common_pull_file(httplib::Client & cli,
if (progress_step >= p.total / 1000 || p.downloaded == p.total) {
if (callback) {
callback->on_update(p);
if (callback->is_cancelled()) {
return false;
}
}
progress_step = 0;
}
Expand Down Expand Up @@ -373,6 +376,9 @@ static int common_download_file_single_online(const std::string & url,
}

for (int i = 0; i < max_attempts; ++i) {
if (opts.callback && opts.callback->is_cancelled()) {
break;
}
if (i) {
LOG_WRN("%s: retrying after %d seconds...\n", __func__, delay);
std::this_thread::sleep_for(std::chrono::seconds(delay));
Expand Down Expand Up @@ -412,6 +418,12 @@ static int common_download_file_single_online(const std::string & url,
if (opts.callback) {
opts.callback->on_done(p, success);
}
if (opts.callback && opts.callback->is_cancelled() &&
std::filesystem::exists(path_temporary)) {
if (remove(path_temporary.c_str()) != 0) {
LOG_ERR("%s: unable to delete temporary file: %s\n", __func__, path_temporary.c_str());
}
}
if (!success) {
LOG_ERR("%s: download failed after %d attempts\n", __func__, max_attempts);
return -1; // max attempts reached
Expand Down
1 change: 1 addition & 0 deletions common/download.h
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Original file line number Diff line number Diff line change
Expand Up @@ -21,6 +21,7 @@ class common_download_callback {
virtual void on_start(const common_download_progress & p) = 0;
virtual void on_update(const common_download_progress & p) = 0;
virtual void on_done(const common_download_progress & p, bool ok) = 0;
virtual bool is_cancelled() const { return false; }
};

struct common_remote_params {
Expand Down
79 changes: 56 additions & 23 deletions ggml/src/ggml-cuda/argsort.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -58,26 +58,48 @@ void argsort_f32_i32_cuda_cub(ggml_cuda_pool & pool,

size_t temp_storage_bytes = 0;

bool is_capturing = false;
#ifdef USE_CUDA_GRAPH
// Currently (confirmed for CCCL <= 3.2) DeviceSegmentedSort does not support stream capture, while DeviceSegmentedRadixSort does.
// See https://github.com/NVIDIA/cccl/issues/5661#issuecomment-3229037149
// TODO: constrain this to the CCCL versions that have this issue once it's resolved in a future CCCL release.
cudaStreamCaptureStatus capture_status;
CUDA_CHECK(cudaStreamIsCapturing(stream, &capture_status));
is_capturing = (capture_status != cudaStreamCaptureStatusNone);
#endif // USE_CUDA_GRAPH

if (order == GGML_SORT_ORDER_ASC) {
if (nrows == 1) {
CUDA_CHECK(DeviceRadixSort::SortPairs(nullptr, temp_storage_bytes, temp_keys, temp_keys, // keys (in-place)
temp_indices, dst, // values (indices)
ncols, 0, sizeof(float) * 8, stream));
temp_indices, dst, // values (indices)
ncols, 0, sizeof(float) * 8, stream));
} else if (is_capturing) {
CUDA_CHECK(DeviceSegmentedRadixSort::SortPairs(
nullptr, temp_storage_bytes, temp_keys, temp_keys, // keys (in-place)
temp_indices, dst, // values (indices)
ncols * nrows, nrows, // num items, num segments
offset_iterator, offset_iterator + 1, 0, sizeof(float) * 8, stream));
} else {
CUDA_CHECK(DeviceSegmentedSort::SortPairs(nullptr, temp_storage_bytes, temp_keys, temp_keys, // keys (in-place)
temp_indices, dst, // values (indices)
ncols * nrows, nrows, // num items, num segments
offset_iterator, offset_iterator + 1, stream));
CUDA_CHECK(DeviceSegmentedSort::SortPairs(nullptr, temp_storage_bytes, temp_keys,
temp_keys, // keys (in-place)
temp_indices, dst, // values (indices)
ncols * nrows, nrows, // num items, num segments
offset_iterator, offset_iterator + 1, stream));
}
} else {
if (nrows == 1) {
CUDA_CHECK(DeviceRadixSort::SortPairsDescending(nullptr, temp_storage_bytes, temp_keys, temp_keys, // keys (in-place)
temp_indices, dst, // values (indices)
ncols, 0, sizeof(float) * 8, stream));
CUDA_CHECK(DeviceRadixSort::SortPairsDescending(nullptr, temp_storage_bytes, temp_keys,
temp_keys, // keys (in-place)
temp_indices, dst, // values (indices)
ncols, 0, sizeof(float) * 8, stream));
} else if (is_capturing) {
CUDA_CHECK(DeviceSegmentedRadixSort::SortPairsDescending(
nullptr, temp_storage_bytes, temp_keys, temp_keys, temp_indices, dst, ncols * nrows, nrows,
offset_iterator, offset_iterator + 1, 0, sizeof(float) * 8, stream));
} else {
CUDA_CHECK(DeviceSegmentedSort::SortPairsDescending(nullptr, temp_storage_bytes, temp_keys, temp_keys, temp_indices,
dst, ncols * nrows, nrows, offset_iterator, offset_iterator + 1,
stream));
CUDA_CHECK(DeviceSegmentedSort::SortPairsDescending(nullptr, temp_storage_bytes, temp_keys, temp_keys,
temp_indices, dst, ncols * nrows, nrows,
offset_iterator, offset_iterator + 1, stream));
}
}

Expand All @@ -86,22 +108,33 @@ void argsort_f32_i32_cuda_cub(ggml_cuda_pool & pool,

if (order == GGML_SORT_ORDER_ASC) {
if (nrows == 1) {
CUDA_CHECK(DeviceRadixSort::SortPairs(d_temp_storage, temp_storage_bytes, temp_keys, temp_keys, // keys (in-place)
temp_indices, dst, // values (indices)
ncols, 0, sizeof(float) * 8, stream));
CUDA_CHECK(DeviceRadixSort::SortPairs(d_temp_storage, temp_storage_bytes, temp_keys,
temp_keys, // keys (in-place)
temp_indices, dst, // values (indices)
ncols, 0, sizeof(float) * 8, stream));
} else if (is_capturing) {
CUDA_CHECK(DeviceSegmentedRadixSort::SortPairs(d_temp_storage, temp_storage_bytes, temp_keys, temp_keys,
temp_indices, dst, ncols * nrows, nrows, offset_iterator,
offset_iterator + 1, 0, sizeof(float) * 8, stream));
} else {
CUDA_CHECK(DeviceSegmentedSort::SortPairs(d_temp_storage, temp_storage_bytes, temp_keys, temp_keys, temp_indices, dst,
ncols * nrows, nrows, offset_iterator, offset_iterator + 1, stream));
CUDA_CHECK(DeviceSegmentedSort::SortPairs(d_temp_storage, temp_storage_bytes, temp_keys, temp_keys,
temp_indices, dst, ncols * nrows, nrows, offset_iterator,
offset_iterator + 1, stream));
}
} else {
if (nrows == 1) {
CUDA_CHECK(DeviceRadixSort::SortPairsDescending(d_temp_storage, temp_storage_bytes, temp_keys, temp_keys, // keys (in-place)
temp_indices, dst, // values (indices)
ncols, 0, sizeof(float) * 8, stream));
CUDA_CHECK(DeviceRadixSort::SortPairsDescending(d_temp_storage, temp_storage_bytes, temp_keys,
temp_keys, // keys (in-place)
temp_indices, dst, // values (indices)
ncols, 0, sizeof(float) * 8, stream));
} else if (is_capturing) {
CUDA_CHECK(DeviceSegmentedRadixSort::SortPairsDescending(
d_temp_storage, temp_storage_bytes, temp_keys, temp_keys, temp_indices, dst, ncols * nrows, nrows,
offset_iterator, offset_iterator + 1, 0, sizeof(float) * 8, stream));
} else {
CUDA_CHECK(DeviceSegmentedSort::SortPairsDescending(d_temp_storage, temp_storage_bytes, temp_keys, temp_keys,
temp_indices, dst, ncols * nrows, nrows, offset_iterator,
offset_iterator + 1, stream));
CUDA_CHECK(DeviceSegmentedSort::SortPairsDescending(d_temp_storage, temp_storage_bytes, temp_keys,
temp_keys, temp_indices, dst, ncols * nrows, nrows,
offset_iterator, offset_iterator + 1, stream));
}
}
}
Expand Down
97 changes: 76 additions & 21 deletions ggml/src/ggml-vulkan/ggml-vulkan.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -2858,11 +2858,10 @@ struct vk_fa_tuning_params {
}
};

static bool ggml_vk_flash_attn_scalar_shmem_support(const vk_device& device, const vk_fa_tuning_params& params, uint32_t hsk, uint32_t hsv, bool f32acc);
static bool ggml_vk_flash_attn_scalar_shmem_support(const vk_device& device, const vk_fa_tuning_params& params, uint32_t hsk, uint32_t hsv, bool f32acc, ggml_type kv_type);
static bool ggml_vk_flash_attn_coopmat_shmem_support(const vk_device& device, const vk_fa_tuning_params& params, uint32_t hsk, uint32_t hsv, bool f32acc);

static vk_fa_tuning_params get_fa_tuning_params_scalar(const vk_device& device, uint32_t hsk, uint32_t hsv, uint32_t n_rows, uint32_t n_kv, ggml_type kv_type, bool f32acc) {
GGML_UNUSED(kv_type);

vk_fa_tuning_params result{};
result.path = FA_SCALAR;
Expand Down Expand Up @@ -2914,7 +2913,7 @@ static vk_fa_tuning_params get_fa_tuning_params_scalar(const vk_device& device,

result.shmem_staging = (device->vendor_id == VK_VENDOR_ID_NVIDIA && hsk < 256 && hsv < 256) ? 1 : 0;

if (!reduce_block_rows && !ggml_vk_flash_attn_scalar_shmem_support(device, result, hsk, hsv, f32acc)) {
if (!reduce_block_rows && !ggml_vk_flash_attn_scalar_shmem_support(device, result, hsk, hsv, f32acc, kv_type)) {
result.block_rows /= 2;
}

Expand Down Expand Up @@ -3445,21 +3444,47 @@ static void ggml_vk_load_shaders(vk_device& device) {
if (device->fp16) {
CREATE_FA(GGML_TYPE_F32, f32, FA_SCALAR, )
CREATE_FA(GGML_TYPE_F16, f16, FA_SCALAR, )
CREATE_FA(GGML_TYPE_Q4_0, q4_0, FA_SCALAR, )
CREATE_FA(GGML_TYPE_Q8_0, q8_0, FA_SCALAR, )
CREATE_FA(GGML_TYPE_Q4_1, q4_1, FA_SCALAR, )
CREATE_FA(GGML_TYPE_Q5_0, q5_0, FA_SCALAR, )
CREATE_FA(GGML_TYPE_Q5_1, q5_1, FA_SCALAR, )
CREATE_FA(GGML_TYPE_IQ4_NL, iq4_nl, FA_SCALAR, )

#if defined(GGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT)
if (device->integer_dot_product && device->subgroup_clustered) {
CREATE_FA(GGML_TYPE_Q4_0, q4_0, FA_SCALAR, _int8)
CREATE_FA(GGML_TYPE_Q8_0, q8_0, FA_SCALAR, _int8)
CREATE_FA(GGML_TYPE_Q4_1, q4_1, FA_SCALAR, _int8)
CREATE_FA(GGML_TYPE_Q5_0, q5_0, FA_SCALAR, _int8)
CREATE_FA(GGML_TYPE_Q5_1, q5_1, FA_SCALAR, _int8)
CREATE_FA(GGML_TYPE_IQ4_NL, iq4_nl, FA_SCALAR, _int8)
} else
#endif
{
CREATE_FA(GGML_TYPE_Q4_0, q4_0, FA_SCALAR, )
CREATE_FA(GGML_TYPE_Q8_0, q8_0, FA_SCALAR, )
CREATE_FA(GGML_TYPE_Q4_1, q4_1, FA_SCALAR, )
CREATE_FA(GGML_TYPE_Q5_0, q5_0, FA_SCALAR, )
CREATE_FA(GGML_TYPE_Q5_1, q5_1, FA_SCALAR, )
CREATE_FA(GGML_TYPE_IQ4_NL, iq4_nl, FA_SCALAR, )
}
} else {
CREATE_FA(GGML_TYPE_F32, f32, FA_SCALAR, _fp32)
CREATE_FA(GGML_TYPE_F16, f16, FA_SCALAR, _fp32)
CREATE_FA(GGML_TYPE_Q4_0, q4_0, FA_SCALAR, _fp32)
CREATE_FA(GGML_TYPE_Q8_0, q8_0, FA_SCALAR, _fp32)
CREATE_FA(GGML_TYPE_Q4_1, q4_1, FA_SCALAR, _fp32)
CREATE_FA(GGML_TYPE_Q5_0, q5_0, FA_SCALAR, _fp32)
CREATE_FA(GGML_TYPE_Q5_1, q5_1, FA_SCALAR, _fp32)
CREATE_FA(GGML_TYPE_IQ4_NL, iq4_nl, FA_SCALAR, _fp32)

#if defined(GGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT)
if (device->integer_dot_product && device->subgroup_clustered) {
CREATE_FA(GGML_TYPE_Q4_0, q4_0, FA_SCALAR, _fp32_int8)
CREATE_FA(GGML_TYPE_Q8_0, q8_0, FA_SCALAR, _fp32_int8)
CREATE_FA(GGML_TYPE_Q4_1, q4_1, FA_SCALAR, _fp32_int8)
CREATE_FA(GGML_TYPE_Q5_0, q5_0, FA_SCALAR, _fp32_int8)
CREATE_FA(GGML_TYPE_Q5_1, q5_1, FA_SCALAR, _fp32_int8)
CREATE_FA(GGML_TYPE_IQ4_NL, iq4_nl, FA_SCALAR, _fp32_int8)
} else
#endif
{
CREATE_FA(GGML_TYPE_Q4_0, q4_0, FA_SCALAR, _fp32)
CREATE_FA(GGML_TYPE_Q8_0, q8_0, FA_SCALAR, _fp32)
CREATE_FA(GGML_TYPE_Q4_1, q4_1, FA_SCALAR, _fp32)
CREATE_FA(GGML_TYPE_Q5_0, q5_0, FA_SCALAR, _fp32)
CREATE_FA(GGML_TYPE_Q5_1, q5_1, FA_SCALAR, _fp32)
CREATE_FA(GGML_TYPE_IQ4_NL, iq4_nl, FA_SCALAR, _fp32)
}
}
#if defined(VK_KHR_cooperative_matrix) && defined(GGML_VULKAN_COOPMAT_GLSLC_SUPPORT)
if (device->coopmat1_fa_support) {
Expand Down Expand Up @@ -8780,7 +8805,7 @@ static void ggml_vk_mul_mat_id(ggml_backend_vk_context * ctx, vk_context& subctx
}
}

static bool ggml_vk_flash_attn_scalar_shmem_support(const vk_device& device, const vk_fa_tuning_params& params, uint32_t hsk, uint32_t hsv, bool f32acc) {
static bool ggml_vk_flash_attn_scalar_shmem_support(const vk_device& device, const vk_fa_tuning_params& params, uint32_t hsk, uint32_t hsv, bool f32acc, ggml_type kv_type) {
GGML_UNUSED(f32acc);
// Needs to be kept up to date on shader changes
const uint32_t wg_size = params.workgroup_size;
Expand All @@ -8789,21 +8814,51 @@ static bool ggml_vk_flash_attn_scalar_shmem_support(const vk_device& device, con

const uint32_t float_type_size = device->fp16 ? sizeof(ggml_fp16_t) : sizeof(float);

const bool mmq = device->integer_dot_product && device->subgroup_clustered &&
(kv_type == GGML_TYPE_Q4_0 || kv_type == GGML_TYPE_Q4_1 ||
kv_type == GGML_TYPE_Q5_0 || kv_type == GGML_TYPE_Q5_1 ||
kv_type == GGML_TYPE_Q8_0 || kv_type == GGML_TYPE_IQ4_NL);

// tmpsh is overestimated slightly
const uint32_t tmpsh = wg_size * sizeof(float);
const uint32_t tmpshv4 = wg_size * 4 * float_type_size;

const uint32_t masksh = Bc * (Br + 1) * float_type_size;

const uint32_t Qf = Br * (hsk / 4 + 1) * 4 * float_type_size;
uint32_t Qf, kvsh, kblocksh_size;
if (mmq) {
// block_b_cache: int32_t qs[8] + FLOAT_TYPEV2 ds
const uint32_t block_b_size = 8 * sizeof(int32_t) + 2 * float_type_size;
Qf = Br * (hsk / 32) * block_b_size;

// kvsh uses D = HSV (K goes through kblocksh instead)
kvsh = params.shmem_staging ? Bc * (hsv / 4 + 1) * 4 * float_type_size : 4 * float_type_size;

// block_a_cache size depends on quant type
uint32_t block_a_size;
switch (kv_type) {
case GGML_TYPE_Q4_0: block_a_size = 4 * sizeof(uint32_t) + float_type_size; break;
case GGML_TYPE_Q4_1: block_a_size = 4 * sizeof(uint32_t) + 2 * float_type_size; break;
case GGML_TYPE_Q5_0: block_a_size = 4 * sizeof(uint32_t) + sizeof(uint32_t) + float_type_size; break;
case GGML_TYPE_Q5_1: block_a_size = 4 * sizeof(uint32_t) + sizeof(uint32_t) + 2 * float_type_size; break;
case GGML_TYPE_Q8_0:
case GGML_TYPE_IQ4_NL: block_a_size = 8 * sizeof(int32_t) + float_type_size; break;
default: block_a_size = 0; break;
}
kblocksh_size = params.shmem_staging ? Bc * (hsk / 32) * block_a_size : block_a_size;
} else {
Qf = Br * (hsk / 4 + 1) * 4 * float_type_size;

const uint32_t D = std::max(hsk, hsv);
kvsh = params.shmem_staging ? Bc * (D / 4 + 1) * 4 * float_type_size : 4 * float_type_size;

const uint32_t D = std::max(hsk, hsv);
const uint32_t kvsh = params.shmem_staging ? Bc * (D / 4 + 1) * 4 * float_type_size : 4 * float_type_size;
kblocksh_size = 0;
}

const uint32_t total_size = tmpsh + tmpshv4 + masksh + Qf + kvsh;
const uint32_t total_size = tmpsh + tmpshv4 + masksh + Qf + kvsh + kblocksh_size;
const bool supported = total_size <= device->properties.limits.maxComputeSharedMemorySize;

VK_LOG_DEBUG("ggml_vk_flash_attn_scalar_shmem_support(HSK=" << hsk << ", HSV=" << hsv << ", total_size=" << total_size << ", supported=" << supported);
VK_LOG_DEBUG("ggml_vk_flash_attn_scalar_shmem_support(HSK=" << hsk << ", HSV=" << hsv << ", mmq=" << mmq << ", total_size=" << total_size << ", supported=" << supported);

return supported;
}
Expand Down
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