COMPMID-3939: Update GEMM heuristic Mali-G77

- Update heuristic for GEMM reshaped RHS only
- Fix left-over block size in CLGEMMMatrixMultiplyReshapedOlyRHSKernel

Change-Id: I34c738821ed2e4a537da4a15058eec164cb6b61f
Signed-off-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/4305
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>

diff --git a/src/core/CL/gemm/reshaped/CLGEMMReshapedKernelConfigurationValhall.cpp b/src/core/CL/gemm/reshaped/CLGEMMReshapedKernelConfigurationValhall.cpp
index 519e903a5a320fdd96c6651c56ede72004ae02f6..3f82dcab00ba6af286b699169f545c23bad8ec56 100644 (file)
--- a/src/core/CL/gemm/reshaped/CLGEMMReshapedKernelConfigurationValhall.cpp
+++ b/src/core/CL/gemm/reshaped/CLGEMMReshapedKernelConfigurationValhall.cpp
@@ -90,13 +90,88 @@ std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> CLGEMMReshapedKernelConfiguratio
     ARM_COMPUTE_UNUSED(k);
     ARM_COMPUTE_UNUSED(b);
 
-    if(n <= 4)
+    const float r_mn     = static_cast<float>(m) / static_cast<float>(n);
+    const float workload = (static_cast<float>(m) * static_cast<float>(n) * static_cast<float>(b)) / 20.0f;
+    const float r_mk = static_cast<float>(m) / static_cast<float>(k);
+    const float r_nk = static_cast<float>(n) / static_cast<float>(k);
+
+    if(r_mk <= 0.11824845522642136)
     {
-        return configure_lhs_rhs_info(m, n, 4, 2, 8, 8, 2, true, true, true, false);
+        if(workload <= 880.0)
+        {
+            return configure_lhs_rhs_info(m, n, 2, 4, 4, 1, 4, false, false, true, false, false);
+        }
+        else
+        {
+            if(r_nk <= 0.42521367967128754)
+            {
+                if(workload <= 1726.4000244140625)
+                {
+                    return configure_lhs_rhs_info(m, n, 4, 4, 4, 2, 2, false, false, true, false, false);
+                }
+                else
+                {
+                    return configure_lhs_rhs_info(m, n, 4, 4, 4, 2, 1, false, true, true, false, true);
+                }
+            }
+            else
+            {
+                if(workload <= 1241.6000366210938)
+                {
+                    return configure_lhs_rhs_info(m, n, 2, 4, 4, 1, 4, false, false, true, false, false);
+                }
+                else
+                {
+                    return configure_lhs_rhs_info(m, n, 4, 4, 4, 4, 4, false, false, true, false, false);
+                }
+            }
+        }
     }
     else
     {
-        return configure_lhs_rhs_info(m, n, 4, 8, 4, 4, 2, true, true, true, false);
+        if(workload <= 11404.7998046875)
+        {
+            if(r_mk <= 1.0126488208770752)
+            {
+                if(r_mn <= 2.545312523841858)
+                {
+                    return configure_lhs_rhs_info(m, n, 4, 4, 4, 2, 1, false, true, true, false, true);
+                }
+                else
+                {
+                    return configure_lhs_rhs_info(m, n, 2, 4, 4, 1, 4, false, false, true, false, false);
+                }
+            }
+            else
+            {
+                if(workload <= 2881.199951171875)
+                {
+                    return configure_lhs_rhs_info(m, n, 4, 4, 4, 4, 2, false, false, true, false, true);
+                }
+                else
+                {
+                    return configure_lhs_rhs_info(m, n, 4, 4, 4, 2, 1, false, true, true, false, true);
+                }
+            }
+        }
+        else
+        {
+            if(r_nk <= 0.5765306055545807)
+            {
+                if(r_mn <= 6.010416746139526)
+                {
+                    return configure_lhs_rhs_info(m, n, 4, 4, 4, 2, 1, false, true, true, false, true);
+                }
+                else
+                {
+                    return configure_lhs_rhs_info(m, n, 4, 4, 4, 2, 1, true, false, true, false, true);
+                }
+            }
+            else
+            {
+                return configure_lhs_rhs_info(m, n, 4, 4, 4, 2, 1, true, false, true, false, true);
+            }
+        }
     }
 }
 

diff --git a/src/core/CL/gemm/reshaped_only_rhs/CLGEMMReshapedOnlyRHSKernelConfigurationValhall.cpp b/src/core/CL/gemm/reshaped_only_rhs/CLGEMMReshapedOnlyRHSKernelConfigurationValhall.cpp
index f7939d29c096ca1fd6765e051141eba083031b05..e0991674b1d084c655901221475492c4b3a97fec 100644 (file)
--- a/src/core/CL/gemm/reshaped_only_rhs/CLGEMMReshapedOnlyRHSKernelConfigurationValhall.cpp
+++ b/src/core/CL/gemm/reshaped_only_rhs/CLGEMMReshapedOnlyRHSKernelConfigurationValhall.cpp
@@ -78,66 +78,107 @@ std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> CLGEMMReshapedOnlyRHSKernelConfi
 
 std::pair<GEMMLHSMatrixInfo, GEMMRHSMatrixInfo> CLGEMMReshapedOnlyRHSKernelConfigurationValhall::configure_G77_f32(unsigned int m, unsigned int n, unsigned int k, unsigned int b)
 {
-    ARM_COMPUTE_UNUSED(k);
-
-    GEMMLHSMatrixInfo lhs_info_buf;
-    GEMMRHSMatrixInfo rhs_info_buf;
-    GEMMLHSMatrixInfo lhs_info_img;
-    GEMMRHSMatrixInfo rhs_info_img;
-
-    // Get lhs_info/rhs_info in case of OpenCL buffer
     if(m == 1)
     {
-        const unsigned int h0 = std::max(n / 4, 1U);
-        std::tie(lhs_info_buf, rhs_info_buf) = configure_lhs_rhs_info(m, n, 1, 4, 4, 1, h0, false, true, false, true);
-    }
-    else
-    {
-        if(m > 256)
+        const float r_mn = static_cast<float>(m) / static_cast<float>(n);
+        const float r_mk = static_cast<float>(m) / static_cast<float>(k);
+
+        if(r_mk <= 0.0064484127797186375)
         {
-            const int v0 = std::max(std::min(static_cast<int>(n / 4), static_cast<int>(8)), static_cast<int>(1));
-            std::tie(lhs_info_buf, rhs_info_buf) = configure_lhs_rhs_info(m, n, 4, 4, 4, 1, v0, false, true, false, true);
+            if(r_mn <= 0.0028273810748942196)
+            {
+                GEMMLHSMatrixInfo lhs_info_buf;
+                GEMMRHSMatrixInfo rhs_info_buf;
+                GEMMLHSMatrixInfo lhs_info_img;
+                GEMMRHSMatrixInfo rhs_info_img;
+
+                const unsigned int h0 = std::max(n / 4, 1U);
+                std::tie(lhs_info_img, rhs_info_img) = configure_lhs_rhs_info(m, n, 1, 4, 8, 1, 16, false, true, false, false, true);
+                std::tie(lhs_info_buf, rhs_info_buf) = configure_lhs_rhs_info(m, n, 1, 4, 4, 1, h0, false, true, false, true, false);
+
+                return select_lhs_rhs_info(std::make_pair(lhs_info_img, rhs_info_img),
+                                           std::make_pair(lhs_info_buf, rhs_info_buf),
+                                           n, k, b, DataType::F32);
+            }
+            else
+            {
+                return configure_lhs_rhs_info(m, n, 1, 2, 16, 1, 8, false, true, false, false, false);
+            }
         }
         else
         {
-            const int v0 = std::max(std::min(static_cast<int>(n / 4), static_cast<int>(8)), static_cast<int>(1));
-            std::tie(lhs_info_buf, rhs_info_buf) = configure_lhs_rhs_info(m, n, 2, 4, 4, 1, v0, false, true, false, true);
+            if(r_mk <= 0.020312500186264515)
+            {
+                return configure_lhs_rhs_info(m, n, 1, 2, 16, 1, 4, false, true, false, false, false);
+            }
+            else
+            {
+                return configure_lhs_rhs_info(m, n, 1, 4, 16, 1, 16, false, true, false, true, false);
+            }
         }
     }
-
-    // Get lhs_info/rhs_info in case of OpenCL image
-    if(m == 1)
-    {
-        std::tie(lhs_info_img, rhs_info_img) = configure_lhs_rhs_info(m, n, 1, 4, 4, 1, 8, true, true, false, false, true);
-    }
     else
     {
-        if((m / 4) * (n / 4) > 4096)
+        const float r_mn     = static_cast<float>(m) / static_cast<float>(n);
+        const float workload = (static_cast<float>(m) * static_cast<float>(n) * static_cast<float>(b)) / 20.0f;
+        const float r_mk = static_cast<float>(m) / static_cast<float>(k);
+
+        if(workload <= 1999.2000122070312)
         {
-            const int h0 = std::max(std::min(static_cast<int>(n / 4), static_cast<int>(8)), static_cast<int>(1));
-            std::tie(lhs_info_img, rhs_info_img) = configure_lhs_rhs_info(m, n, 4, 4, 4, 1, h0, false, true, false, false, true);
+            if(workload <= 747.1999816894531)
+            {
+                return configure_lhs_rhs_info(m, n, 2, 2, 4, 1, 8, false, true, false, true, false);
+            }
+            else
+            {
+                GEMMLHSMatrixInfo lhs_info_buf;
+                GEMMRHSMatrixInfo rhs_info_buf;
+                GEMMLHSMatrixInfo lhs_info_img;
+                GEMMRHSMatrixInfo rhs_info_img;
+                std::tie(lhs_info_img, rhs_info_img) = configure_lhs_rhs_info(m, n, 2, 4, 8, 1, 2, false, false, false, true, true);
+                std::tie(lhs_info_buf, rhs_info_buf) = configure_lhs_rhs_info(m, n, 2, 2, 4, 1, 8, false, true, false, true, false);
+
+                return select_lhs_rhs_info(std::make_pair(lhs_info_img, rhs_info_img),
+                                           std::make_pair(lhs_info_buf, rhs_info_buf),
+                                           n, k, b, DataType::F32);
+            }
         }
         else
         {
-            const int h0 = std::max(std::min(static_cast<int>(n / 4), static_cast<int>(8)), static_cast<int>(1));
-            std::tie(lhs_info_img, rhs_info_img) = configure_lhs_rhs_info(m, n, 2, 4, 4, 1, h0, false, true, false, false, true);
-        }
-    }
-
-    const TensorInfo  tensor_rhs_info(TensorShape(n, k, b), 1, DataType::F32);
-    const TensorShape shape = compute_rhs_reshaped_shape(tensor_rhs_info, rhs_info_img);
-    const TensorInfo  tensor_reshaped_info(shape, 1, DataType::F32);
+            if(r_mn <= 0.03348214365541935)
+            {
+                if(r_mk <= 0.028125000186264515)
+                {
+                    return configure_lhs_rhs_info(m, n, 2, 2, 4, 1, 8, false, true, false, true, false);
+                }
+                else
+                {
+                    GEMMLHSMatrixInfo lhs_info_buf;
+                    GEMMRHSMatrixInfo rhs_info_buf;
+                    GEMMLHSMatrixInfo lhs_info_img;
+                    GEMMRHSMatrixInfo rhs_info_img;
+                    std::tie(lhs_info_img, rhs_info_img) = configure_lhs_rhs_info(m, n, 2, 4, 8, 1, 2, false, false, false, true, true);
+                    std::tie(lhs_info_buf, rhs_info_buf) = configure_lhs_rhs_info(m, n, 2, 2, 4, 1, 8, false, true, false, true, false);
 
-    // In case of small workloads, we use the OpenCL buffer rather than the OpenCL image2d
-    const bool use_cl_image2d = ((m / lhs_info_img.m0) * (n / rhs_info_img.n0)) * b < 1024 ? false : true;
+                    return select_lhs_rhs_info(std::make_pair(lhs_info_img, rhs_info_img),
+                                               std::make_pair(lhs_info_buf, rhs_info_buf),
+                                               n, k, b, DataType::F32);
+                }
+            }
+            else
+            {
+                GEMMLHSMatrixInfo lhs_info_buf;
+                GEMMRHSMatrixInfo rhs_info_buf;
+                GEMMLHSMatrixInfo lhs_info_img;
+                GEMMRHSMatrixInfo rhs_info_img;
+                std::tie(lhs_info_img, rhs_info_img) = configure_lhs_rhs_info(m, n, 4, 4, 4, 1, 2, false, true, false, false, true);
+                std::tie(lhs_info_buf, rhs_info_buf) = configure_lhs_rhs_info(m, n, 4, 4, 4, 1, 16, false, true, false, true, false);
 
-    if(bool(validate_image2d_support_on_rhs(tensor_reshaped_info, rhs_info_img)) && use_cl_image2d)
-    {
-        return std::make_pair(lhs_info_img, rhs_info_img);
-    }
-    else
-    {
-        return std::make_pair(lhs_info_buf, rhs_info_buf);
+                return select_lhs_rhs_info(std::make_pair(lhs_info_img, rhs_info_img),
+                                            std::make_pair(lhs_info_buf, rhs_info_buf),
+                                            n, k, b, DataType::F32);
+            }
+        }
     }
 }
 

diff --git a/src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.cpp b/src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.cpp
index 68f761b9e7d2c0dc7027ea2650f1dd08de882e62..d53aede3c8a903171004fa491accdd44731a4c6c 100644 (file)
--- a/src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedOnlyRHSKernel.cpp
@@ -247,14 +247,14 @@ void CLGEMMMatrixMultiplyReshapedOnlyRHSKernel::configure(const CLCompileContext
     const unsigned int h_gemm_3d = _reinterpret_output_as_3d ? output->info()->dimension(1) : input0->info()->dimension(1);
     const unsigned int d_gemm_3d = _reinterpret_output_as_3d ? output->info()->dimension(2) : input0->info()->dimension(2);
 
-    // Calculate partial (store instead of load) M0 and partial N0 for the partial blocks at the end of a row/column if any. This is to avoid padding.
-    const unsigned int partial_store_m0 = internal_m % lhs_info.m0;
-    const unsigned int partial_store_n0 = gemm_info.n % rhs_info.n0;
-
     // Shrink M0 to be always <= M (internal_m) to prevent out-of-bounds reads.
     // NOTE: This might have implications on heuristics and performance
     const unsigned int internal_m0 = std::min(internal_m, lhs_info.m0);
 
+    // Calculate partial (store instead of load) M0 and partial N0 for the partial blocks at the end of a row/column if any. This is to avoid padding.
+    const unsigned int partial_store_m0 = internal_m % internal_m0;
+    const unsigned int partial_store_n0 = gemm_info.n % rhs_info.n0;
+
     // Create build options
     CLBuildOptions build_opts;
     build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input0->info()->data_type()));

diff --git a/src/runtime/CL/gemm/CLGEMMKernelSelectionValhall.cpp b/src/runtime/CL/gemm/CLGEMMKernelSelectionValhall.cpp
index acae0e7565cae1b223dd5a7ac5d240ab7aa2081e..da41859b87bb54e51f50e48ad2b3cf80f8f7fc97 100644 (file)
--- a/src/runtime/CL/gemm/CLGEMMKernelSelectionValhall.cpp
+++ b/src/runtime/CL/gemm/CLGEMMKernelSelectionValhall.cpp
@@ -46,8 +46,8 @@ CLGEMMKernelType CLGEMMKernelSelectionValhall::select_kernel(const CLGEMMKernelS
 
     using FunctionExecutorPtr = CLGEMMKernelType (CLGEMMKernelSelectionValhall::*)(unsigned int m, unsigned int n, unsigned int k, unsigned int b, bool is_rhs_constant);
 
-    // Configurations for Valhall architectures
-    static std::map<DataType, FunctionExecutorPtr> gemm_configs =
+    // Default configurations for Valhall architectures
+    static std::map<DataType, FunctionExecutorPtr> gemm_default_configs =
     {
         { DataType::F32, &CLGEMMKernelSelectionValhall::default_f32 },
         { DataType::F16, &CLGEMMKernelSelectionValhall::default_f16 },
@@ -57,14 +57,34 @@ CLGEMMKernelType CLGEMMKernelSelectionValhall::select_kernel(const CLGEMMKernelS
         { DataType::QSYMM8_PER_CHANNEL, &CLGEMMKernelSelectionValhall::default_q8 }
     };
 
+    // Mali-G77 configurations
+    static std::map<DataType, FunctionExecutorPtr> gemm_g77_configs =
+    {
+        { DataType::F32, &CLGEMMKernelSelectionValhall::default_f32 },
+        { DataType::F16, &CLGEMMKernelSelectionValhall::g77_f16 },
+        { DataType::QASYMM8, &CLGEMMKernelSelectionValhall::default_q8 },
+        { DataType::QASYMM8_SIGNED, &CLGEMMKernelSelectionValhall::default_q8 },
+        { DataType::QSYMM8, &CLGEMMKernelSelectionValhall::default_q8 },
+        { DataType::QSYMM8_PER_CHANNEL, &CLGEMMKernelSelectionValhall::default_q8 }
+    };
+
     const DataType data_type = params.data_type;
 
-    if(gemm_configs.find(data_type) != gemm_configs.end())
+    switch(_target)
     {
-        return (this->*gemm_configs[data_type])(params.m, params.n, params.k, params.b, params.is_rhs_constant);
+        case GPUTarget::G77:
+            if(gemm_g77_configs.find(data_type) != gemm_g77_configs.end())
+            {
+                return (this->*gemm_g77_configs[data_type])(params.m, params.n, params.k, params.b, params.is_rhs_constant);
+            }
+            ARM_COMPUTE_ERROR("Not supported data type");
+        default:
+            if(gemm_default_configs.find(data_type) != gemm_default_configs.end())
+            {
+                return (this->*gemm_default_configs[data_type])(params.m, params.n, params.k, params.b, params.is_rhs_constant);
+            }
+            ARM_COMPUTE_ERROR("Not supported data type");
     }
-
-    ARM_COMPUTE_ERROR("Not supported data type");
 }
 
 CLGEMMKernelType CLGEMMKernelSelectionValhall::default_f32(unsigned int m, unsigned int n, unsigned int k, unsigned int b, bool is_rhs_constant)
@@ -81,6 +101,110 @@ CLGEMMKernelType CLGEMMKernelSelectionValhall::default_f16(unsigned int m, unsig
     return is_rhs_constant ? CLGEMMKernelType::RESHAPED_ONLY_RHS : CLGEMMKernelType::NATIVE_V1;
 }
 
+CLGEMMKernelType CLGEMMKernelSelectionValhall::g77_f16(unsigned int m, unsigned int n, unsigned int k, unsigned int b, bool is_rhs_constant)
+{
+    if (!is_rhs_constant)
+    {
+        return CLGEMMKernelType::NATIVE_V1;
+    }
+
+    if (m == 1)
+    {
+        return CLGEMMKernelType::RESHAPED_ONLY_RHS;
+    }
+
+    const float r_mn = static_cast<float>(m) / static_cast<float>(n);
+    const float r_mk = static_cast<float>(m) / static_cast<float>(k);
+    const float r_nk = static_cast<float>(n) / static_cast<float>(k);
+    const float workload = (static_cast<float>(m) * static_cast<float>(n) * static_cast<float>(b)) / 20.0f;
+
+    if(r_mk <= 0.6817956566810608)
+    {
+        if(workload <= 801.6000061035156)
+        {
+            return CLGEMMKernelType::RESHAPED_ONLY_RHS;
+        }
+        else
+        {
+            if(r_mn <= 0.0839829258620739)
+            {
+                return CLGEMMKernelType::RESHAPED_ONLY_RHS;
+            }
+            else
+            {
+                if(r_mk <= 0.24917218834161758)
+                {
+                    return CLGEMMKernelType::RESHAPED;
+                }
+                else
+                {
+                    if(workload <= 2551.75)
+                    {
+                        return CLGEMMKernelType::RESHAPED_ONLY_RHS;
+                    }
+                    else
+                    {
+                        if(workload <= 5061.574951171875)
+                        {
+                            return CLGEMMKernelType::RESHAPED_ONLY_RHS;
+                        }
+                        else
+                        {
+                            return CLGEMMKernelType::RESHAPED;
+                        }
+                    }
+                }
+            }
+        }
+    }
+    else
+    {
+        if(r_mk <= 4.849947690963745)
+        {
+            if(workload <= 17618.4501953125)
+            {
+                if(workload <= 5224.699951171875)
+                {
+                    return CLGEMMKernelType::RESHAPED_ONLY_RHS;
+                }
+                else
+                {
+                    if(r_nk <= 0.7933054566383362)
+                    {
+                        return CLGEMMKernelType::RESHAPED;
+                    }
+                    else
+                    {
+                        return CLGEMMKernelType::RESHAPED_ONLY_RHS;
+                    }
+                }
+            }
+            else
+            {
+                if(workload <= 20275.2001953125)
+                {
+                    return CLGEMMKernelType::RESHAPED;
+                }
+                else
+                {
+                    if(r_mk <= 3.07421875)
+                    {
+                        return CLGEMMKernelType::RESHAPED_ONLY_RHS;
+                    }
+                    else
+                    {
+                        return CLGEMMKernelType::RESHAPED;
+                    }
+                }
+            }
+        }
+        else
+        {
+            return CLGEMMKernelType::RESHAPED_ONLY_RHS;
+        }
+    }
+}
+
 CLGEMMKernelType CLGEMMKernelSelectionValhall::default_q8(unsigned int m, unsigned int n, unsigned int k, unsigned int b, bool is_rhs_constant)
 {
     ARM_COMPUTE_UNUSED(m, n, k, b);

diff --git a/src/runtime/CL/gemm/CLGEMMKernelSelectionValhall.h b/src/runtime/CL/gemm/CLGEMMKernelSelectionValhall.h
index cbea9ea5480541474beb186bf171b87515a281af..82e46f694ed1408831235e29ad723fa508a02bb2 100644 (file)
--- a/src/runtime/CL/gemm/CLGEMMKernelSelectionValhall.h
+++ b/src/runtime/CL/gemm/CLGEMMKernelSelectionValhall.h
@@ -47,6 +47,7 @@ private:
     CLGEMMKernelType default_f32(unsigned int m, unsigned int n, unsigned int k, unsigned int b, bool is_rhs_constant);
     CLGEMMKernelType default_f16(unsigned int m, unsigned int n, unsigned int k, unsigned int b, bool is_rhs_constant);
     CLGEMMKernelType default_q8(unsigned int m, unsigned int n, unsigned int k, unsigned int b, bool is_rhs_constant);
+    CLGEMMKernelType g77_f16(unsigned int m, unsigned int n, unsigned int k, unsigned int b, bool is_rhs_constant);
 };
 } // namespace cl_gemm
 } // namespace arm_compute