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cuda : revert CUDA pool stuff (#3944)
* Revert "cuda : add ROCM aliases for CUDA pool stuff (#3918)" This reverts commit 629f917. * Revert "cuda : use CUDA memory pool with async memory allocation/deallocation when available (#3903)" This reverts commit d606905. ggml-ci
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‎ggml-cuda.cu‎

Lines changed: 50 additions & 81 deletions
Original file line numberDiff line numberDiff line change
@@ -39,10 +39,6 @@
3939
#define cudaDeviceCanAccessPeer hipDeviceCanAccessPeer
4040
#define cudaDeviceDisablePeerAccess hipDeviceDisablePeerAccess
4141
#define cudaDeviceEnablePeerAccess hipDeviceEnablePeerAccess
42-
#define cudaDeviceGetMemPool hipDeviceGetMemPool
43-
#define cudaMemPoolAttrReleaseThreshold hipMemPoolAttrReleaseThreshold
44-
#define cudaMemPoolSetAttribute hipMemPoolSetAttribute
45-
#define cudaMemPool_t hipMemPool_t
4642
#define cudaDeviceProp hipDeviceProp_t
4743
#define cudaDeviceSynchronize hipDeviceSynchronize
4844
#define cudaError_t hipError_t
@@ -52,15 +48,13 @@
5248
#define cudaEvent_t hipEvent_t
5349
#define cudaEventDestroy hipEventDestroy
5450
#define cudaFree hipFree
55-
#define cudaFreeAsync hipFreeAsync
5651
#define cudaFreeHost hipHostFree
5752
#define cudaGetDevice hipGetDevice
5853
#define cudaGetDeviceCount hipGetDeviceCount
5954
#define cudaGetDeviceProperties hipGetDeviceProperties
6055
#define cudaGetErrorString hipGetErrorString
6156
#define cudaGetLastError hipGetLastError
6257
#define cudaMalloc hipMalloc
63-
#define cudaMallocFromPoolAsync hipMallocFromPoolAsync
6458
#define cudaMallocHost(ptr, size) hipHostMalloc(ptr, size, hipHostMallocDefault)
6559
#define cudaMemcpy hipMemcpy
6660
#define cudaMemcpy2DAsync hipMemcpy2DAsync
@@ -187,11 +181,11 @@ static_assert(sizeof(half) == sizeof(ggml_fp16_t), "wrong fp16 size");
187181
do { \
188182
cudaError_t err_ = (err); \
189183
if (err_ != cudaSuccess) { \
190-
int dev_id; \
191-
cudaGetDevice(&dev_id); \
184+
int id; \
185+
cudaGetDevice(&id); \
192186
fprintf(stderr, "\nCUDA error %d at %s:%d: %s\n", err_, __FILE__, __LINE__, \
193187
cudaGetErrorString(err_)); \
194-
fprintf(stderr, "current device: %d\n", dev_id); \
188+
fprintf(stderr, "current device: %d\n", id); \
195189
exit(1); \
196190
} \
197191
} while (0)
@@ -201,11 +195,11 @@ static_assert(sizeof(half) == sizeof(ggml_fp16_t), "wrong fp16 size");
201195
do { \
202196
cublasStatus_t err_ = (err); \
203197
if (err_ != CUBLAS_STATUS_SUCCESS) { \
204-
int dev_id; \
205-
cudaGetDevice(&dev_id); \
198+
int id; \
199+
cudaGetDevice(&id); \
206200
fprintf(stderr, "\ncuBLAS error %d at %s:%d: %s\n", \
207201
err_, __FILE__, __LINE__, cublasGetStatusString(err_)); \
208-
fprintf(stderr, "current device: %d\n", dev_id); \
202+
fprintf(stderr, "current device: %d\n", id); \
209203
exit(1); \
210204
} \
211205
} while (0)
@@ -471,7 +465,6 @@ static_assert(K_QUANTS_PER_ITERATION == 1 || K_QUANTS_PER_ITERATION == 2, "K_QUA
471465

472466
#define MAX_STREAMS 8
473467
static cudaStream_t g_cudaStreams[GGML_CUDA_MAX_DEVICES][MAX_STREAMS] = { nullptr };
474-
static cudaMemPool_t g_cudaMemPools[GGML_CUDA_MAX_DEVICES] = { nullptr };
475468

476469
struct ggml_tensor_extra_gpu {
477470
void * data_device[GGML_CUDA_MAX_DEVICES]; // 1 pointer for each device for split tensors
@@ -5780,16 +5773,6 @@ static void * ggml_cuda_pool_malloc(size_t size, size_t * actual_size) {
57805773
return ptr;
57815774
}
57825775

5783-
static void * ggml_cuda_pool_malloc_async(size_t size, size_t * actual_size, int id, cudaStream_t stream) {
5784-
if (g_cudaMemPools[id] == nullptr) {
5785-
return ggml_cuda_pool_malloc(size, actual_size);
5786-
}
5787-
void *ptr;
5788-
CUDA_CHECK(cudaMallocFromPoolAsync(&ptr, size, g_cudaMemPools[id], stream));
5789-
*actual_size = size;
5790-
return ptr;
5791-
}
5792-
57935776
static void ggml_cuda_pool_free(void * ptr, size_t size) {
57945777
scoped_spin_lock lock(g_cuda_pool_lock);
57955778
int id;
@@ -5808,13 +5791,6 @@ static void ggml_cuda_pool_free(void * ptr, size_t size) {
58085791
}
58095792

58105793

5811-
static void ggml_cuda_pool_free_async(void * ptr, size_t actual_size, int id, cudaStream_t stream) {
5812-
if (g_cudaMemPools[id] == nullptr) {
5813-
return ggml_cuda_pool_free(ptr, actual_size);
5814-
}
5815-
CUDA_CHECK(cudaFreeAsync(ptr, stream));
5816-
}
5817-
58185794
void ggml_init_cublas() {
58195795
static bool initialized = false;
58205796

@@ -5869,13 +5845,6 @@ void ggml_init_cublas() {
58695845
// create cublas handle
58705846
CUBLAS_CHECK(cublasCreate(&g_cublas_handles[id]));
58715847
CUBLAS_CHECK(cublasSetMathMode(g_cublas_handles[id], CUBLAS_TF32_TENSOR_OP_MATH));
5872-
5873-
// configure memory pool
5874-
cudaError_t err = cudaDeviceGetMemPool(&g_cudaMemPools[id], id);
5875-
if (err == cudaSuccess) {
5876-
size_t treshold = UINT64_MAX;
5877-
CUDA_CHECK(cudaMemPoolSetAttribute(g_cudaMemPools[id], cudaMemPoolAttrReleaseThreshold, &treshold));
5878-
}
58795848
}
58805849

58815850
// configure logging to stdout
@@ -6469,7 +6438,7 @@ inline void ggml_cuda_op_mul_mat_cublas(
64696438
const to_fp16_cuda_t to_fp16_cuda = ggml_get_to_fp16_cuda(src0->type);
64706439
GGML_ASSERT(to_fp16_cuda != nullptr);
64716440
size_t ne = row_diff*ne00;
6472-
src0_as_f16 = (half *) ggml_cuda_pool_malloc_async(ne * sizeof(half), &src0_as, id, stream);
6441+
src0_as_f16 = (half *) ggml_cuda_pool_malloc(ne * sizeof(half), &src0_as);
64736442
to_fp16_cuda(src0_dd_i, src0_as_f16, ne, stream);
64746443
}
64756444
const half * src0_ptr = src0->type == GGML_TYPE_F16 ? (const half *) src0_dd_i : src0_as_f16;
@@ -6480,12 +6449,13 @@ inline void ggml_cuda_op_mul_mat_cublas(
64806449
const to_fp16_cuda_t to_fp16_cuda = ggml_get_to_fp16_cuda(src1->type);
64816450
GGML_ASSERT(to_fp16_cuda != nullptr);
64826451
size_t ne = src1_ncols*ne10;
6483-
src1_as_f16 = (half *) ggml_cuda_pool_malloc_async(ne * sizeof(half), &src1_as, id, stream);
6452+
src1_as_f16 = (half *) ggml_cuda_pool_malloc(ne * sizeof(half), &src1_as);
64846453
to_fp16_cuda(src1_ddf_i, src1_as_f16, ne, stream);
64856454
}
64866455
const half * src1_ptr = src1->type == GGML_TYPE_F16 ? (const half *) src1_ddq_i : src1_as_f16;
6487-
size_t dst_f16_as = 0;
6488-
half * dst_f16 = (half *) ggml_cuda_pool_malloc_async(row_diff*src1_ncols * sizeof(half), &dst_f16_as, id, stream);
6456+
6457+
size_t dst_as = 0;
6458+
half * dst_f16 = (half *) ggml_cuda_pool_malloc(row_diff*src1_ncols * sizeof(half), &dst_as);
64896459

64906460
const half alpha_f16 = 1.0f;
64916461
const half beta_f16 = 0.0f;
@@ -6503,15 +6473,14 @@ inline void ggml_cuda_op_mul_mat_cublas(
65036473
const to_fp32_cuda_t to_fp32_cuda = ggml_get_to_fp32_cuda(GGML_TYPE_F16);
65046474
to_fp32_cuda(dst_f16, dst_dd_i, row_diff*src1_ncols, stream);
65056475

6506-
if (dst_f16_as != 0) {
6507-
ggml_cuda_pool_free_async(dst_f16, dst_f16_as, id, stream);
6508-
}
6476+
ggml_cuda_pool_free(dst_f16, dst_as);
65096477

65106478
if (src0_as != 0) {
6511-
ggml_cuda_pool_free_async(src0_as_f16, src0_as, id, stream);
6479+
ggml_cuda_pool_free(src0_as_f16, src0_as);
65126480
}
6481+
65136482
if (src1_as != 0) {
6514-
ggml_cuda_pool_free_async(src1_as_f16, src1_as, id, stream);
6483+
ggml_cuda_pool_free(src1_as_f16, src1_as);
65156484
}
65166485
}
65176486
else {
@@ -6521,7 +6490,7 @@ inline void ggml_cuda_op_mul_mat_cublas(
65216490
if (src0->type != GGML_TYPE_F32) {
65226491
const to_fp32_cuda_t to_fp32_cuda = ggml_get_to_fp32_cuda(src0->type);
65236492
GGML_ASSERT(to_fp32_cuda != nullptr);
6524-
src0_ddq_as_f32 = (float *) ggml_cuda_pool_malloc_async(row_diff*ne00 * sizeof(float), &src0_as, id, stream); // NOLINT
6493+
src0_ddq_as_f32 = (float *) ggml_cuda_pool_malloc(row_diff*ne00 * sizeof(float), &src0_as); // NOLINT
65256494
to_fp32_cuda(src0_dd_i, src0_ddq_as_f32, row_diff*ne00, stream);
65266495
}
65276496
const float * src0_ddf_i = src0->type == GGML_TYPE_F32 ? (const float *) src0_dd_i : src0_ddq_as_f32;
@@ -6538,7 +6507,7 @@ inline void ggml_cuda_op_mul_mat_cublas(
65386507
&beta, dst_dd_i, ldc));
65396508

65406509
if (src0_as != 0) {
6541-
ggml_cuda_pool_free_async(src0_ddq_as_f32, src0_as, id, stream);
6510+
ggml_cuda_pool_free(src0_ddq_as_f32, src0_as);
65426511
}
65436512
}
65446513

@@ -6961,30 +6930,29 @@ static void ggml_cuda_op_mul_mat(
69616930
src0_dd[id] = (char *) src0_extra->data_device[id];
69626931
} else {
69636932
const size_t size_src0_ddq = split ? (row_high[id]-row_low[id])*ne00 * src0_ts/src0_bs : ggml_nbytes(src0);
6964-
src0_dd[id] = (char *) ggml_cuda_pool_malloc_async(ggml_nbytes(src0), &src0_as[id], id, stream);
6933+
src0_dd[id] = (char *) ggml_cuda_pool_malloc(ggml_nbytes(src0), &src0_as[id]);
69656934
}
69666935

69676936
if (src1_on_device && src1_is_contiguous) {
69686937
src1_ddf[id] = (float *) src1_extra->data_device[id];
69696938
} else {
6970-
src1_ddf[id] = (float *) ggml_cuda_pool_malloc_async(ggml_nbytes(src1), &src1_asf[id], id, stream);
6939+
src1_ddf[id] = (float *) ggml_cuda_pool_malloc(ggml_nbytes(src1), &src1_asf[id]);
69716940
}
69726941

69736942
if (convert_src1_to_q8_1) {
6974-
const size_t size_dst_ddq = nrows1*src1_padded_col_size*q8_1_ts/q8_1_bs;
6975-
src1_ddq[id] = (char *) ggml_cuda_pool_malloc_async(size_dst_ddq, &src1_asq[id], id, stream);
6943+
src1_ddq[id] = (char *) ggml_cuda_pool_malloc(nrows1*src1_padded_col_size*q8_1_ts/q8_1_bs, &src1_asq[id]);
69766944

69776945
if (src1_on_device && src1_is_contiguous) {
69786946
quantize_row_q8_1_cuda(src1_ddf[id], src1_ddq[id], ne10, nrows1, src1_padded_col_size, stream);
6979-
// CUDA_CHECK(cudaGetLastError());
6947+
CUDA_CHECK(cudaGetLastError());
69806948
}
69816949
}
69826950

69836951
if (dst_on_device) {
69846952
dst_dd[id] = (float *) dst_extra->data_device[id];
69856953
} else {
69866954
const size_t size_dst_ddf = split ? (row_high[id]-row_low[id])*ne1*sizeof(float) : ggml_nbytes(dst);
6987-
dst_dd[id] = (float *) ggml_cuda_pool_malloc_async(size_dst_ddf, &dst_as[id], id, stream);
6955+
dst_dd[id] = (float *) ggml_cuda_pool_malloc(size_dst_ddf, &dst_as[id]);
69886956
}
69896957
}
69906958

@@ -7110,6 +7078,24 @@ static void ggml_cuda_op_mul_mat(
71107078
}
71117079
}
71127080

7081+
for (int64_t id = 0; id < g_device_count; ++id) {
7082+
CUDA_CHECK(ggml_cuda_set_device(id));
7083+
7084+
// free buffers again when done
7085+
if (src0_as[id] > 0) {
7086+
ggml_cuda_pool_free(src0_dd[id], src0_as[id]);
7087+
}
7088+
if (src1_asf[id] > 0) {
7089+
ggml_cuda_pool_free(src1_ddf[id], src1_asf[id]);
7090+
}
7091+
if (src1_asq[id] > 0) {
7092+
ggml_cuda_pool_free(src1_ddq[id], src1_asq[id]);
7093+
}
7094+
if (dst_as[id] > 0) {
7095+
ggml_cuda_pool_free(dst_dd[id], dst_as[id]);
7096+
}
7097+
}
7098+
71137099
// main device waits for all other devices to be finished
71147100
if (split && g_device_count > 1) {
71157101
int64_t is_max = (ne11 + MUL_MAT_SRC1_COL_STRIDE - 1) / MUL_MAT_SRC1_COL_STRIDE;
@@ -7127,21 +7113,6 @@ static void ggml_cuda_op_mul_mat(
71277113
CUDA_CHECK(ggml_cuda_set_device(g_main_device));
71287114
CUDA_CHECK(cudaDeviceSynchronize());
71297115
}
7130-
7131-
for (int64_t id = 0; id < g_device_count; ++id) {
7132-
if (src0_as[id] > 0) {
7133-
ggml_cuda_pool_free_async(src0_dd[id], src0_as[id], id, g_cudaStreams[id][0]);
7134-
}
7135-
if (src1_asf[id] > 0) {
7136-
ggml_cuda_pool_free_async(src1_ddf[id], src1_asf[id], id, g_cudaStreams[id][0]);
7137-
}
7138-
if (src1_asq[id] > 0) {
7139-
ggml_cuda_pool_free_async(src1_ddq[id], src1_asq[id], id, g_cudaStreams[id][0]);
7140-
}
7141-
if (dst_as[id] > 0) {
7142-
ggml_cuda_pool_free_async(dst_dd[id], dst_as[id], id, g_cudaStreams[id][0]);
7143-
}
7144-
}
71457116
}
71467117

71477118
static void ggml_cuda_repeat(const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
@@ -7328,11 +7299,11 @@ static void ggml_cuda_mul_mat_mat_batched_cublas(const ggml_tensor * src0, const
73287299
GGML_ASSERT(to_fp16_cuda != nullptr);
73297300

73307301
size_t src1_as = 0;
7331-
half * src1_as_f16 = (half *) ggml_cuda_pool_malloc_async(ne1 * sizeof(half), &src1_as, id, main_stream);
7302+
half * src1_as_f16 = (half *) ggml_cuda_pool_malloc(ne1 * sizeof(half), &src1_as);
73327303
to_fp16_cuda(src1_ddf, src1_as_f16, ne1, main_stream);
73337304

73347305
size_t dst_as = 0;
7335-
half * dst_f16 = (half *) ggml_cuda_pool_malloc_async(ne * sizeof(half), &dst_as, id, main_stream);
7306+
half * dst_f16 = (half *) ggml_cuda_pool_malloc(ne * sizeof(half), &dst_as);
73367307

73377308
GGML_ASSERT(ne12 % ne02 == 0);
73387309
GGML_ASSERT(ne13 % ne03 == 0);
@@ -7386,8 +7357,8 @@ static void ggml_cuda_mul_mat_mat_batched_cublas(const ggml_tensor * src0, const
73867357
size_t ptrs_src_s = 0;
73877358
size_t ptrs_dst_s = 0;
73887359

7389-
ptrs_src = (const void **) ggml_cuda_pool_malloc_async(2*ne23*sizeof(void *), &ptrs_src_s, id, main_stream);
7390-
ptrs_dst = ( void **) ggml_cuda_pool_malloc_async(1*ne23*sizeof(void *), &ptrs_dst_s, id, main_stream);
7360+
ptrs_src = (const void **) ggml_cuda_pool_malloc(2*ne23*sizeof(void *), &ptrs_src_s);
7361+
ptrs_dst = ( void **) ggml_cuda_pool_malloc(1*ne23*sizeof(void *), &ptrs_dst_s);
73917362

73927363
dim3 block_dims(ne13, ne12);
73937364
k_compute_batched_ptrs<<<1, block_dims, 0, main_stream>>>(
@@ -7400,6 +7371,7 @@ static void ggml_cuda_mul_mat_mat_batched_cublas(const ggml_tensor * src0, const
74007371
dst->nb[2], dst->nb[3],
74017372
r2, r3);
74027373
CUDA_CHECK(cudaGetLastError());
7374+
74037375
CUBLAS_CHECK(
74047376
cublasGemmBatchedEx(g_cublas_handles[id], CUBLAS_OP_T, CUBLAS_OP_N,
74057377
ne01, ne11, ne10,
@@ -7411,22 +7383,19 @@ static void ggml_cuda_mul_mat_mat_batched_cublas(const ggml_tensor * src0, const
74117383
CUBLAS_GEMM_DEFAULT_TENSOR_OP));
74127384

74137385
if (ptrs_src_s != 0) {
7414-
ggml_cuda_pool_free_async(ptrs_src, ptrs_src_s, id, main_stream);
7386+
ggml_cuda_pool_free(ptrs_src, ptrs_src_s);
74157387
}
74167388
if (ptrs_dst_s != 0) {
7417-
ggml_cuda_pool_free_async(ptrs_dst, ptrs_dst_s, id, main_stream);
7389+
ggml_cuda_pool_free(ptrs_dst, ptrs_dst_s);
74187390
}
74197391
}
74207392
#endif
74217393

74227394
const to_fp32_cuda_t to_fp32_cuda = ggml_get_to_fp32_cuda(GGML_TYPE_F16);
74237395
to_fp32_cuda(dst_f16, dst_ddf, ne, main_stream);
7424-
if (src1_as != 0) {
7425-
ggml_cuda_pool_free_async(src1_as_f16, src1_as, id, main_stream);
7426-
}
7427-
if (dst_as != 0) {
7428-
ggml_cuda_pool_free_async(dst_f16, dst_as, id, main_stream);
7429-
}
7396+
7397+
ggml_cuda_pool_free(src1_as_f16, src1_as);
7398+
ggml_cuda_pool_free(dst_f16, dst_as);
74307399
}
74317400

74327401
static void ggml_cuda_mul_mat(const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {

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