src: cpu: conv: Use acl_indirect_gemm for bf16 convolutions

performance improvements:

Total benchdnn tests: 57
Min: 15x
Average: 131x
Max: 320x

Author: Ryo-not-rio

src/cpu/aarch64/acl_convolution_utils.cpp

@@ -15,6 +15,7 @@
 *******************************************************************************/
 
 #include "cpu/aarch64/acl_convolution_utils.hpp"
+#include "common/convolution_pd.hpp"
 #include "common/utils.hpp"
 #include "oneapi/dnnl/dnnl.h"
 
@@ -62,9 +63,10 @@ status_t acl_init_conf(acl_conv_conf_t &acp, memory_desc_t &src_md,
                               everyone_is(data_type::f32, src_d.data_type(),
                                       wei_d.data_type(), dst_d.data_type()),
                               everyone_is(data_type::f16, src_d.data_type(),
+                                      wei_d.data_type(), dst_d.data_type()),
+                              everyone_is(data_type::bf16, src_d.data_type(),
                                       wei_d.data_type(), dst_d.data_type())),
-            " src, dst and wei must be fp16 or fp32");
-
+            " src, dst and wei must be fp16, bf16 or fp32");
     // batch size
     const int mb = src_d.dims()[0];
 

src/cpu/aarch64/acl_indirect_gemm_convolution.hpp

@@ -1,5 +1,5 @@
 /*******************************************************************************
-* Copyright 2021-2023 Arm Ltd. and affiliates
+* Copyright 2021-2024 Arm Ltd. and affiliates
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
@@ -84,12 +84,15 @@ struct acl_indirect_gemm_convolution_fwd_t : public primitive_t {
 
             const bool is_fp16_ok = expect_data_types(f16, f16, f16, f16, undef)
                     && attr()->has_default_values(smask_t::post_ops, f16);
+            const bool is_bf16_ok
+                    = expect_data_types(bf16, bf16, bf16, bf16, undef)
+                    && attr_.post_ops_.len() == 0;
             const bool is_fp32_ok = expect_data_types(f32, f32, f32, f32, undef)
                     && attr()->has_default_values(
                             smask_t::post_ops | smask_t::fpmath_mode, f32);
             bool ok = is_fwd()
                     && set_default_alg_kind(alg_kind::convolution_direct)
-                    && utils::one_of(true, is_fp16_ok, is_fp32_ok)
+                    && utils::one_of(true, is_fp16_ok, is_bf16_ok, is_fp32_ok)
                     && !has_zero_dim_memory();
             if (!ok) return status::unimplemented;
 

src/cpu/cpu_convolution_list.cpp

@@ -1,6 +1,6 @@
 /*******************************************************************************
 * Copyright 2019-2024 Intel Corporation
-* Copyright 2020-2023 Arm Ltd. and affiliates
+* Copyright 2020-2024 Arm Ltd. and affiliates
 * Copyright 2020-2024 FUJITSU LIMITED
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
@@ -179,6 +179,7 @@ const std::map<pk_dt_impl_key_t, std::vector<impl_list_item_t>> &impl_list_map()
             CPU_INSTANCE_AVX512(gemm_bf16_convolution_fwd_t<bf16>)
             CPU_INSTANCE_AVX2(brgemm_1x1_convolution_fwd_t<avx2_vnni_2>)
             CPU_INSTANCE_AVX2(brgemm_convolution_fwd_t<avx2_vnni_2>)
+            CPU_INSTANCE_AARCH64_ACL(acl_indirect_gemm_convolution_fwd_t)
             CPU_INSTANCE(ref_convolution_fwd_t)
             CPU_INSTANCE(ref_fused_convolution_fwd_t)
             nullptr,