diff --git a/ggml-opencl.cpp b/ggml-opencl.cpp index 7e4069d76b259..4a331f24a92ae 100644 --- a/ggml-opencl.cpp +++ b/ggml-opencl.cpp @@ -202,14 +202,14 @@ inline void get_scale_min_k4(int j, const __global uint8_t *q, uint8_t *d, uint8 __kernel void dequantize_block_q2_K(__global const struct block_q2_K *x, __global float *yy) { - const int i = get_group_id(0); + const int i = get_group_id(0) + get_global_offset(0); const int tid = get_local_id(0); const int n = tid / 32; const int l = tid - 32 * n; const int is = 8 * n + l / 16; const uint8_t q = x[i].qs[32 * n + l]; - __global float *y = yy + i * QK_K + 128 * n; + __global float *y = yy + get_group_id(0) * QK_K + 128 * n; const float dall = vload_half(0, &x[i].d); const float dmin = vload_half(0, &x[i].dmin); @@ -223,7 +223,7 @@ __kernel void dequantize_block_q2_K(__global const struct block_q2_K *x, __globa __kernel void dequantize_block_q3_K(__global const struct block_q3_K *x, __global float *yy) { int r = get_local_id(0) / 4; - int i = get_group_id(0); + int i = get_group_id(0) + get_global_offset(0); int tid = r / 2; int is0 = r % 2; int l0 = 16 * is0 + 4 * (get_local_id(0) % 4); @@ -241,7 +241,7 @@ __kernel void dequantize_block_q3_K(__global const struct block_q3_K *x, __globa float d_all = vload_half(0, &x[i].d); float dl = d_all * (us - 32); - __global float *y = yy + i * QK_K + 128 * n + 32 * j; + __global float *y = yy + get_group_id(0) * QK_K + 128 * n + 32 * j; const __global uint8_t *q = x[i].qs + 32 * n; const __global uint8_t *hm = x[i].hmask; @@ -251,14 +251,14 @@ __kernel void dequantize_block_q3_K(__global const struct block_q3_K *x, __globa __kernel void dequantize_block_q4_K(__global const struct block_q4_K *x, __global float *yy) { - const int i = get_group_id(0); + const int i = get_group_id(0) + get_global_offset(0); const int tid = get_local_id(0); const int il = tid / 8; const int ir = tid % 8; const int is = 2 * il; const int n = 4; - __global float *y = yy + i * QK_K + 64 * il + n * ir; + __global float *y = yy + get_group_id(0) * QK_K + 64 * il + n * ir; const float dall = vload_half(0, &x[i].d); const float dmin = vload_half(0, &x[i].dmin); @@ -281,13 +281,13 @@ __kernel void dequantize_block_q4_K(__global const struct block_q4_K *x, __globa __kernel void dequantize_block_q5_K(__global const struct block_q5_K *x, __global float *yy) { - const int i = get_group_id(0); + const int i = get_group_id(0) + get_global_offset(0); const int tid = get_local_id(0); const int il = tid / 16; const int ir = tid % 16; const int is = 2 * il; - __global float *y = yy + i * QK_K + 64 * il + 2 * ir; + __global float *y = yy + get_group_id(0) * QK_K + 64 * il + 2 * ir; const float dall = vload_half(0, &x[i].d); const float dmin = vload_half(0, &x[i].dmin); @@ -313,13 +313,13 @@ __kernel void dequantize_block_q5_K(__global const struct block_q5_K *x, __globa __kernel void dequantize_block_q6_K(__global const struct block_q6_K *x, __global float *yy) { - const int i = get_group_id(0); + const int i = get_group_id(0) + get_global_offset(0); const int tid = get_local_id(0); const int ip = tid / 32; const int il = tid - 32 * ip; const int is = 8 * ip + il / 16; - __global float *y = yy + i * QK_K + 128 * ip + il; + __global float *y = yy + get_group_id(0) * QK_K + 128 * ip + il; const float d = vload_half(0, &x[i].d); @@ -730,7 +730,7 @@ __kernel void KERNEL_NAME(__global X_TYPE* x, __global float* y) { const uint qk = QUANT_K; const uint qr = QUANT_R; - const int ib = i/qk; // block index + const int ib = i/qk + get_global_offset(0); // block index const int iqs = (i%qk)/qr; // quant index const int iybs = i - i%qk; // y block start index const int y_offset = qr == 1 ? 1 : qk/2; @@ -1349,30 +1349,42 @@ static cl_int ggml_cl_h2d_tensor_2d(cl_command_queue queue, cl_mem dst, size_t o const enum ggml_type type = src->type; const size_t ts = ggml_type_size(type); const size_t bs = ggml_blck_size(type); + const uint64_t row_size = ts*ne0/bs; - const void * x = (const void *) ((const char *) src->data + i2*nb2 + i3*nb3); - if (nb0 == ts && nb1 == ts*ne0/bs) { - err = clEnqueueWriteBuffer(queue, dst, CL_FALSE, offset, ne1*nb1, x, 0, NULL, ev); - return err; + const char * x = (const char *) src->data + i2*nb2 + i3*nb3; + if (nb0 == ts && nb1 == row_size) { + return clEnqueueWriteBuffer(queue, dst, CL_FALSE, offset, ne1*row_size, x, 0, NULL, ev); } if (nb0 == ts) { const size_t buffer_origin[3] = { offset, 0, 0 }; const size_t host_origin[3] = { 0, 0, 0 }; - const size_t region[3] = { ts*ne0/bs, ne1, 1 }; - err = clEnqueueWriteBufferRect(queue, dst, CL_FALSE, buffer_origin, host_origin, region, ts*ne0/bs, 0, nb1, 0, x, 0, NULL, ev); - return err; + const size_t region[3] = { row_size, ne1, 1 }; + return clEnqueueWriteBufferRect(queue, dst, CL_FALSE, buffer_origin, host_origin, region, row_size, 0, nb1, 0, x, 0, NULL, ev); } + std::vector events; + if (ev && ne1>1) events.reserve(ne1-1); for (uint64_t i1 = 0; i1 < ne1; i1++) { // pretend the row is a matrix with cols=1 - const size_t buffer_origin[3] = { offset, i1, 0 }; + const size_t buffer_origin[3] = { offset + i1*row_size, 0, 0 }; const size_t host_origin[3] = { 0, 0, 0 }; - const size_t region[3] = { ts/bs, ne0, 1 }; - err = clEnqueueWriteBufferRect(queue, dst, CL_FALSE, buffer_origin, host_origin, region, 0, 0, nb0, 0, ((const char *)x) + i1*nb0, 0, NULL, ev); + const size_t region[3] = { ts, ne0/bs, 1 }; + // if an event is requested, make the last write wait for all previous writes to complete + if (ev && i1) { + events.push_back(*ev); + } + cl_uint nevents = i1 == ne1-1 ? events.size() : 0U; + err = clEnqueueWriteBufferRect(queue, dst, CL_FALSE, buffer_origin, host_origin, region, ts, 0, nb0, 0, x + i1*nb1, nevents, nevents ? events.data() : nullptr, ev); if (err != CL_SUCCESS) { - break; + for (auto event : events) { + clReleaseEvent(event); + } + return err; } } - return err; + for (auto event : events) { + CL_CHECK(clReleaseEvent(event)); + } + return CL_SUCCESS; } static void ggml_cl_mul_f32(const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) { @@ -1503,6 +1515,7 @@ static void ggml_cl_mul_mat_f32(const ggml_tensor * src0, const ggml_tensor * sr cl_mem d_Y = ggml_cl_pool_malloc(sizeof(float) * y_ne, &y_size); cl_mem d_D = ggml_cl_pool_malloc(sizeof(float) * d_ne, &d_size); + size_t x_offset = 0; int64_t pi02 = -1; int64_t pi03 = -1; @@ -1513,7 +1526,9 @@ static void ggml_cl_mul_mat_f32(const ggml_tensor * src0, const ggml_tensor * sr int64_t i02 = i12 / r2; // copy data to device - if (src0->backend != GGML_BACKEND_GPU && (i02 != pi02 || i03 != pi03)) { + if (src0->backend == GGML_BACKEND_GPU) { + x_offset = (i03 * ne02 + i02) * x_ne; + } else if (i02 != pi02 || i03 != pi03) { CL_CHECK(ggml_cl_h2d_tensor_2d(queue, d_X, 0, src0, i03, i02, NULL)); pi02 = i02; pi03 = i03; @@ -1528,7 +1543,7 @@ static void ggml_cl_mul_mat_f32(const ggml_tensor * src0, const ggml_tensor * sr clblast::Transpose::kYes, clblast::Transpose::kNo, ne01, ne11, ne10, alpha, - d_X, 0, ne00, + d_X, x_offset, ne00, d_Y, 0, ne10, beta, d_D, 0, ne01, @@ -1596,6 +1611,7 @@ static void ggml_cl_mul_mat_f16(const ggml_tensor * src0, const ggml_tensor * sr bool src1_cont_rows = nb10 == sizeof(float); bool src1_cont_cols = (size_t)nb11 == ne11*sizeof(float); + size_t x_offset = 0; int64_t pi02 = -1; int64_t pi03 = -1; @@ -1606,7 +1622,9 @@ static void ggml_cl_mul_mat_f16(const ggml_tensor * src0, const ggml_tensor * sr int64_t i02 = i12 / r2; // copy src0 to device - if (src0->backend != GGML_BACKEND_GPU && (i02 != pi02 || i03 != pi03)) { + if (src0->backend == GGML_BACKEND_GPU) { + x_offset = (i03 * ne02 + i02) * x_ne; + } else if (i02 != pi02 || i03 != pi03) { CL_CHECK(ggml_cl_h2d_tensor_2d(queue, d_X, 0, src0, i03, i02, NULL)); pi02 = i02; pi03 = i03; @@ -1646,7 +1664,7 @@ static void ggml_cl_mul_mat_f16(const ggml_tensor * src0, const ggml_tensor * sr clblast::Transpose::kYes, clblast::Transpose::kNo, ne01, ne11, ne10, alpha, - d_X, 0, ne00, + d_X, x_offset, ne00, d_Y, 0, ne10, beta, d_D, 0, ne01, @@ -1696,7 +1714,8 @@ static void ggml_cl_mul_mat_q_f32(const ggml_tensor * src0, const ggml_tensor * const int x_ne = ne01 * ne00; const int y_ne = ne11 * ne10; const int d_ne = ne11 * ne01; - const size_t q_sz = ggml_type_size(type) * x_ne / ggml_blck_size(type); + const int x_bps = x_ne / ggml_blck_size(type); // blocks per 2D slice + const size_t q_sz = ggml_type_size(type) * x_bps; size_t x_size; size_t y_size; @@ -1764,9 +1783,10 @@ static void ggml_cl_mul_mat_q_f32(const ggml_tensor * src0, const ggml_tensor * } else { // general dequantization kernel + CLBlast matrix matrix multiplication // convert src0 to fp32 on device const size_t global = x_ne / global_denom; + const size_t offset = src0->backend == GGML_BACKEND_GPU ? (i03 * ne02 + i02) * x_bps : 0; CL_CHECK(clSetKernelArg(*to_fp32_cl, 0, sizeof(cl_mem), &d_Q)); CL_CHECK(clSetKernelArg(*to_fp32_cl, 1, sizeof(cl_mem), &d_X)); - CL_CHECK(clEnqueueNDRangeKernel(queue, *to_fp32_cl, 1, NULL, &global, local > 0 ? &local : NULL, events.size(), !events.empty() ? events.data() : NULL, NULL)); + CL_CHECK(clEnqueueNDRangeKernel(queue, *to_fp32_cl, 1, offset > 0 ? &offset : NULL, &global, local > 0 ? &local : NULL, events.size(), !events.empty() ? events.data() : NULL, NULL)); // copy src1 to device CL_CHECK(ggml_cl_h2d_tensor_2d(queue, d_Y, 0, src1, i13, i12, NULL)); @@ -1888,17 +1908,19 @@ void ggml_cl_transform_tensor(void * data, ggml_tensor * tensor) { const int64_t ne3 = tensor->ne[3]; const ggml_type type = tensor->type; - const size_t q_sz = ggml_type_size(type) * ne0 * ne1 * ne2 * ne3 / ggml_blck_size(type); + const size_t s_sz = ggml_type_size(type) * (size_t) (ne0 * ne1 / ggml_blck_size(type)); + const size_t q_sz = s_sz * (size_t) (ne2 * ne3); size_t q_size; cl_mem dst = ggml_cl_pool_malloc(q_sz, &q_size); tensor->data = data; // copy tensor to device + size_t offset = 0; for (int64_t i3 = 0; i3 < ne3; i3++) { for (int64_t i2 = 0; i2 < ne2; i2++) { - int i = i3*ne2 + i2; - CL_CHECK(ggml_cl_h2d_tensor_2d(queue, dst, i*ne0*ne1, tensor, i3, i2, NULL)); + CL_CHECK(ggml_cl_h2d_tensor_2d(queue, dst, offset, tensor, i3, i2, NULL)); + offset += s_sz; } }