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JohannesGaesslerJohannesGaessler
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CUDA: fix MMQ for non-contiguous src0, add tests
1 parent 873279b commit b87dc5a

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4 files changed

+63
-23
lines changed

4 files changed

+63
-23
lines changed

‎ggml/src/ggml-cuda.cu‎

Lines changed: 11 additions & 7 deletions
Original file line numberDiff line numberDiff line change
@@ -1151,8 +1151,8 @@ static cudaError_t ggml_cuda_cpy_tensor_2d(
11511151
void * dst, const struct ggml_tensor * src, int64_t i3, int64_t i2, int64_t i1_low, int64_t i1_high, cudaStream_t stream) {
11521152

11531153
GGML_ASSERT(ggml_backend_buffer_is_cuda(src->buffer));
1154-
char * src_ptr = (char *) src->data;
1155-
char * dst_ptr = (char *) dst;
1154+
const char * src_ptr = (const char *) src->data;
1155+
char * dst_ptr = (char *) dst;
11561156

11571157
const int64_t ne0 = src->ne[0];
11581158
const int64_t nb0 = src->nb[0];
@@ -1162,7 +1162,7 @@ static cudaError_t ggml_cuda_cpy_tensor_2d(
11621162
const enum ggml_type type = src->type;
11631163
const int64_t ts = ggml_type_size(type);
11641164
const int64_t bs = ggml_blck_size(type);
1165-
int64_t i1_diff = i1_high - i1_low;
1165+
const int64_t i1_diff = i1_high - i1_low;
11661166

11671167
const char * x = src_ptr + i1_low*nb1 + i2*nb2 + i3*nb3;
11681168
if (nb0 == ts && nb1 == ts*ne0/bs) {
@@ -1479,13 +1479,17 @@ static void ggml_cuda_op_mul_mat(
14791479
if (src0_is_contiguous) {
14801480
dev[id].src0_dd = split ? (char *) src0_extra->data_device[id] : (char *) src0->data;
14811481
} else {
1482-
dev[id].src0_dd = dev[id].src0_dd_alloc.alloc(ctx.pool(id), ggml_nbytes(src0));
1482+
// If src0 is not contiguous it will be copied to a temporary buffer, it may then be necessary to clear padding.
1483+
const size_t nbytes_data = ggml_nbytes(src0);
1484+
const size_t nbytes_padding = ggml_row_size(src0->type, MATRIX_ROW_PADDING - ne00 % MATRIX_ROW_PADDING);
1485+
dev[id].src0_dd = dev[id].src0_dd_alloc.alloc(ctx.pool(id), nbytes_data + nbytes_padding);
1486+
CUDA_CHECK(cudaMemsetAsync(dev[id].src0_dd + nbytes_data , 0, nbytes_padding, stream));
14831487
}
14841488

1485-
// If src0 is on a temporary compute buffers (partial offloading) there may be some padding that needs to be cleared:
1489+
// If src0 is on a temporary compute buffer (partial offloading) there may be some padding that needs to be cleared:
14861490
if (ne00 % MATRIX_ROW_PADDING != 0 && ggml_is_quantized(src0->type) && ggml_backend_buffer_get_usage(src0->buffer) == GGML_BACKEND_BUFFER_USAGE_COMPUTE && src0->view_src == nullptr) {
1487-
const int64_t nbytes_data = ggml_row_size(src0->type, (dev[id].row_high - dev[id].row_low)*ne00);
1488-
const int64_t nbytes_padding = ggml_row_size(src0->type, MATRIX_ROW_PADDING - ne00 % MATRIX_ROW_PADDING);
1491+
const size_t nbytes_data = ggml_row_size(src0->type, (dev[id].row_high - dev[id].row_low)*ne00);
1492+
const size_t nbytes_padding = ggml_row_size(src0->type, MATRIX_ROW_PADDING - ne00 % MATRIX_ROW_PADDING);
14891493
CUDA_CHECK(cudaMemsetAsync(dev[id].src0_dd + nbytes_data , 0, nbytes_padding, stream));
14901494
}
14911495

‎ggml/src/ggml-cuda/mmq.cu‎

Lines changed: 1 addition & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -8,16 +8,14 @@ void ggml_cuda_op_mul_mat_q(
88

99
const int64_t ne00 = src0->ne[0];
1010

11-
const int64_t nb01 = src0->nb[1];
12-
1311
const int64_t ne10 = src1->ne[0];
1412
const int64_t ne11 = src1->ne[1];
1513
GGML_ASSERT(ne10 % QK8_1 == 0);
1614

1715
const int64_t ne0 = dst->ne[0];
1816

1917
const int64_t row_diff = row_high - row_low;
20-
const int64_t stride00 = nb01 / ggml_type_size(src0->type);
18+
const int64_t stride00 = ne00 / ggml_blck_size(src0->type);
2119

2220
int id = ggml_cuda_get_device();
2321
const int compute_capability = ggml_cuda_info().devices[id].cc;

‎ggml/src/ggml.c‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -3464,7 +3464,7 @@ int64_t ggml_nrows(const struct ggml_tensor * tensor) {
34643464

34653465
size_t ggml_nbytes(const struct ggml_tensor * tensor) {
34663466
size_t nbytes;
3467-
size_t blck_size = ggml_blck_size(tensor->type);
3467+
const size_t blck_size = ggml_blck_size(tensor->type);
34683468
if (blck_size == 1) {
34693469
nbytes = ggml_type_size(tensor->type);
34703470
for (int i = 0; i < GGML_MAX_DIMS; ++i) {

‎tests/test-backend-ops.cpp‎

Lines changed: 50 additions & 12 deletions
Original file line numberDiff line numberDiff line change
@@ -1650,11 +1650,12 @@ struct test_mul_mat : public test_case {
16501650
const int64_t m;
16511651
const int64_t n;
16521652
const int64_t k;
1653-
const std::array<int64_t, 2> bs; // dims 3 and 4
1654-
const std::array<int64_t, 2> nr; // repeat in dims 3 and 4
1653+
const std::array<int64_t, 2> bs; // dims 3 and 4
1654+
const std::array<int64_t, 2> nr; // repeat in dims 3 and 4
1655+
const std::array<int64_t, 4> per; // permutation of dimensions
16551656

16561657
std::string vars() override {
1657-
return VARS_TO_STR7(type_a, type_b, m, n, k, bs, nr);
1658+
return VARS_TO_STR8(type_a, type_b, m, n, k, bs, nr, per);
16581659
}
16591660

16601661
double max_nmse_err() override {
@@ -1669,8 +1670,9 @@ struct test_mul_mat : public test_case {
16691670
test_mul_mat(ggml_type type_a = GGML_TYPE_F32, ggml_type type_b = GGML_TYPE_F32,
16701671
int64_t m = 32, int64_t n = 32, int64_t k = 32,
16711672
std::array<int64_t, 2> bs = {10, 10},
1672-
std::array<int64_t, 2> nr = {2, 2})
1673-
: type_a(type_a), type_b(type_b), m(m), n(n), k(k), bs(bs), nr(nr) {}
1673+
std::array<int64_t, 2> nr = {2, 2},
1674+
std::array<int64_t, 4> per = {0, 1, 2, 3})
1675+
: type_a(type_a), type_b(type_b), m(m), n(n), k(k), bs(bs), nr(nr), per(per) {}
16741676

16751677
ggml_tensor * build_graph(ggml_context * ctx) override {
16761678
// C^T = A * B^T: (k, m) * (k, n) => (m, n)
@@ -1681,6 +1683,28 @@ struct test_mul_mat : public test_case {
16811683
ggml_set_name(a, "a");
16821684
ggml_set_name(b, "b");
16831685

1686+
// If the permutation is not {0, 1, 2, 3}, replace a and b with views that have the same data in a different order.
1687+
// This test only works correctly if exactly 2 indices != 0 are swapped.
1688+
if (per[0] != 0 || per[1] != 1 || per[2] != 2 || per[3] != 3) {
1689+
GGML_ASSERT(per[0] == 0);
1690+
const size_t rsa = ggml_row_size(a->type, a->ne[0]);
1691+
const size_t rsb = ggml_row_size(b->type, b->ne[0]);
1692+
size_t nba[GGML_MAX_DIMS] = {ggml_type_size(a->type), rsa, rsa, rsa};
1693+
size_t nbb[GGML_MAX_DIMS] = {ggml_type_size(b->type), rsb, rsb, rsb};
1694+
for (int64_t i = 1; i < GGML_MAX_DIMS; ++i) {
1695+
for (int64_t j = 1; j < per[i]; ++j) {
1696+
nba[i] *= a->ne[per[j]];
1697+
nbb[i] *= b->ne[per[j]];
1698+
}
1699+
}
1700+
a = ggml_view_4d(ctx, a, a->ne[0], a->ne[1], a->ne[2], a->ne[3], nba[1], nba[2], nba[3], /*offset =*/ 0);
1701+
b = ggml_view_4d(ctx, b, b->ne[0], b->ne[1], b->ne[2], b->ne[3], nbb[1], nbb[2], nbb[3], /*offset =*/ 0);
1702+
GGML_ASSERT(ggml_nbytes(a) == ggml_nbytes(a->src[0]));
1703+
GGML_ASSERT(ggml_nbytes(b) == ggml_nbytes(b->src[0]));
1704+
ggml_set_name(a, "a_permuted");
1705+
ggml_set_name(b, "b_permuted");
1706+
}
1707+
16841708
ggml_tensor * out = ggml_mul_mat(ctx, a, b);
16851709
ggml_set_name(out, "out");
16861710

@@ -3442,13 +3466,14 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_eval() {
34423466
#if 1
34433467
for (ggml_type type_a : base_types) {
34443468
for (ggml_type type_b : {GGML_TYPE_F32, GGML_TYPE_F16}) {
3445-
test_cases.emplace_back(new test_mul_mat(type_a, type_b, 16, 1, 256, { 1, 1}, {1, 1}));
3446-
test_cases.emplace_back(new test_mul_mat(type_a, type_b, 16, 1, 256, {10, 1}, {1, 1}));
3447-
test_cases.emplace_back(new test_mul_mat(type_a, type_b, 16, 1, 256, {10, 1}, {2, 1}));
3448-
test_cases.emplace_back(new test_mul_mat(type_a, type_b, 16, 1, 256, {10, 10}, {1, 1}));
3449-
test_cases.emplace_back(new test_mul_mat(type_a, type_b, 16, 1, 256, {10, 10}, {2, 1}));
3450-
test_cases.emplace_back(new test_mul_mat(type_a, type_b, 16, 1, 256, {10, 10}, {1, 2}));
3451-
test_cases.emplace_back(new test_mul_mat(type_a, type_b, 16, 1, 256, {10, 10}, {2, 2}));
3469+
// test cases without permutation
3470+
test_cases.emplace_back(new test_mul_mat(type_a, type_b, 16, 1, 256, { 1, 1}, {1, 1}));
3471+
test_cases.emplace_back(new test_mul_mat(type_a, type_b, 16, 1, 256, {10, 1}, {1, 1}));
3472+
test_cases.emplace_back(new test_mul_mat(type_a, type_b, 16, 1, 256, {10, 1}, {2, 1}));
3473+
test_cases.emplace_back(new test_mul_mat(type_a, type_b, 16, 1, 256, {10, 10}, {1, 1}));
3474+
test_cases.emplace_back(new test_mul_mat(type_a, type_b, 16, 1, 256, {10, 10}, {2, 1}));
3475+
test_cases.emplace_back(new test_mul_mat(type_a, type_b, 16, 1, 256, {10, 10}, {1, 2}));
3476+
test_cases.emplace_back(new test_mul_mat(type_a, type_b, 16, 1, 256, {10, 10}, {2, 2}));
34523477

34533478
test_cases.emplace_back(new test_mul_mat(type_a, type_b, 16, 16, 256, { 1, 1}, {1, 1}));
34543479
test_cases.emplace_back(new test_mul_mat(type_a, type_b, 16, 16, 256, {10, 1}, {1, 1}));
@@ -3457,6 +3482,19 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_eval() {
34573482
test_cases.emplace_back(new test_mul_mat(type_a, type_b, 16, 16, 256, {10, 10}, {2, 1}));
34583483
test_cases.emplace_back(new test_mul_mat(type_a, type_b, 16, 16, 256, {10, 10}, {1, 2}));
34593484
test_cases.emplace_back(new test_mul_mat(type_a, type_b, 16, 16, 256, {10, 10}, {2, 2}));
3485+
3486+
// test cases with permutation
3487+
test_cases.emplace_back(new test_mul_mat(type_a, type_b, 16, 1, 256, {2, 3}, {1, 1}, {0, 2, 1, 3}));
3488+
test_cases.emplace_back(new test_mul_mat(type_a, type_b, 16, 1, 256, {2, 3}, {1, 1}, {0, 1, 3, 2}));
3489+
test_cases.emplace_back(new test_mul_mat(type_a, type_b, 16, 1, 256, {2, 3}, {1, 1}, {0, 3, 2, 1}));
3490+
3491+
test_cases.emplace_back(new test_mul_mat(type_a, type_b, 16, 8, 256, {2, 3}, {1, 1}, {0, 2, 1, 3}));
3492+
test_cases.emplace_back(new test_mul_mat(type_a, type_b, 16, 8, 256, {2, 3}, {1, 1}, {0, 1, 3, 2}));
3493+
test_cases.emplace_back(new test_mul_mat(type_a, type_b, 16, 8, 256, {2, 3}, {1, 1}, {0, 3, 2, 1}));
3494+
3495+
test_cases.emplace_back(new test_mul_mat(type_a, type_b, 16, 16, 256, {2, 3}, {1, 1}, {0, 2, 1, 3}));
3496+
test_cases.emplace_back(new test_mul_mat(type_a, type_b, 16, 16, 256, {2, 3}, {1, 1}, {0, 1, 3, 2}));
3497+
test_cases.emplace_back(new test_mul_mat(type_a, type_b, 16, 16, 256, {2, 3}, {1, 1}, {0, 3, 2, 1}));
34603498
}
34613499
}
34623500
for (ggml_type type_a : other_types) {

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