COMPMID-1675: Add SVE support

Change-Id: I86679adff556b6ffc9929b35cbf1b59b3958bdb1

1 files changed, 192 insertions, 0 deletions

diff --git a/examples/neon_sgemm.cpp b/examples/neon_sgemm.cpp
new file mode 100644
index 0000000000..f6f93dd507
--- /dev/null
+++ b/examples/neon_sgemm.cpp
@@ -0,0 +1,192 @@
+/*
+ * Copyright (c) 2018 ARM Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+ * SOFTWARE.
+ */
+#include "arm_compute/core/Types.h"
+#include "arm_compute/runtime/NEON/NEFunctions.h"
+#include "arm_compute/runtime/NEON/NEScheduler.h"
+#include "utils/Utils.h"
+
+#include <cstdlib>
+
+using namespace arm_compute;
+using namespace utils;
+
+class NESGEMMExample : public Example
+{
+public:
+    bool do_setup(int argc, char **argv) override
+    {
+        NPYLoader npy0, npy1, npy2;
+        alpha = 1.0f;
+        beta  = 0.0f;
+
+        std::ifstream stream;
+        if(argc > 1)
+        {
+            stream.open(argv[1], std::fstream::in);
+        }
+
+        if(argc < 3 || (argc < 4 && stream.bad()))
+        {
+            // Print help
+            std::cout << "Usage: 1) ./build/neon_sgemm input_matrix_1.npy input_matrix_2.npy [input_matrix_3.npy] [alpha = 1] [beta = 0]\n";
+            std::cout << "       2) ./build/neon_sgemm M N K [alpha = 1.0f] [beta = 0.0f]\n\n";
+            std::cout << "Too few or no input_matrices provided. Using M=7, N=3, K=5, alpha=1.0f and beta=0.0f\n\n";
+
+            src0.allocator()->init(TensorInfo(TensorShape(5U, 7U), 1, DataType::F32));
+            src1.allocator()->init(TensorInfo(TensorShape(3U, 5U), 1, DataType::F32));
+            src2.allocator()->init(TensorInfo(TensorShape(3U, 7U), 1, DataType::F32));
+        }
+        else
+        {
+            if(stream.good()) /* case file1.npy file2.npy [file3.npy] [alpha = 1.0f] [beta = 0.0f] */
+            {
+                npy0.open(argv[1]);
+                npy0.init_tensor(src0, DataType::F32);
+                npy1.open(argv[2]);
+                npy1.init_tensor(src1, DataType::F32);
+
+                if(argc > 3)
+                {
+                    stream.close();
+                    stream.clear();
+                    stream.open(argv[3], std::fstream::in);
+                    if(stream.good()) /* case with third file */
+                    {
+                        npy2.open(argv[3]);
+                        npy2.init_tensor(src2, DataType::F32);
+
+                        if(argc > 4)
+                        {
+                            // Convert string to float
+                            alpha = strtof(argv[4], nullptr);
+
+                            if(argc > 5)
+                            {
+                                // Convert string to float
+                                beta = strtof(argv[5], nullptr);
+                            }
+                        }
+                    }
+                    else /* case without third file */
+                    {
+                        alpha = strtof(argv[3], nullptr);
+
+                        if(argc > 4)
+                        {
+                            beta = strtof(argv[4], nullptr);
+                        }
+                    }
+                }
+            }
+            else /* case M N K [alpha = 1.0f] [beta = 0.0f] */
+            {
+                size_t M = strtol(argv[1], nullptr, 10);
+                size_t N = strtol(argv[2], nullptr, 10);
+                size_t K = strtol(argv[3], nullptr, 10);
+
+                src0.allocator()->init(TensorInfo(TensorShape(K, M), 1, DataType::F32));
+                src1.allocator()->init(TensorInfo(TensorShape(N, K), 1, DataType::F32));
+                src2.allocator()->init(TensorInfo(TensorShape(N, M), 1, DataType::F32));
+
+                if(argc > 4)
+                {
+                    alpha = strtof(argv[4], nullptr);
+
+                    if(argc > 5)
+                    {
+                        beta = strtof(argv[5], nullptr);
+                    }
+                }
+            }
+        }
+
+        init_sgemm_output(dst, src0, src1, DataType::F32);
+
+        // Configure function
+        sgemm.configure(&src0, &src1, nullptr, &dst, alpha, beta);
+
+        // Allocate all the images
+        src0.allocator()->allocate();
+        src1.allocator()->allocate();
+        dst.allocator()->allocate();
+
+        // Fill the input images with either the data provided or random data
+        if(npy0.is_open())
+        {
+            npy0.fill_tensor(src0);
+            npy1.fill_tensor(src1);
+
+            output_filename = "sgemm_out.npy";
+            is_fortran      = npy0.is_fortran();
+
+            if(npy2.is_open())
+            {
+                src2.allocator()->allocate();
+                npy2.fill_tensor(src2);
+            }
+        }
+        else
+        {
+            src2.allocator()->allocate();
+
+            fill_random_tensor(src0, -1.f, 1.f);
+            fill_random_tensor(src1, -1.f, 1.f);
+            fill_random_tensor(src2, -1.f, 1.f);
+        }
+
+        // Dummy run for CLTuner
+        sgemm.run();
+
+        return true;
+    }
+    void do_run() override
+    {
+        // Execute the function
+        sgemm.run();
+    }
+    void do_teardown() override
+    {
+        if(!output_filename.empty()) /* Save to .npy file */
+        {
+            save_to_npy(dst, output_filename, is_fortran);
+        }
+    }
+
+private:
+    Tensor      src0{}, src1{}, src2{}, dst{};
+    NEGEMM      sgemm{};
+    float       alpha{}, beta{};
+    bool        is_fortran{};
+    std::string output_filename{};
+};
+
+/** Main program for sgemm test
+ *
+ * @param[in] argc Number of arguments
+ * @param[in] argv Arguments ( [optional] Matrix A, [optional] Matrix B, [optional] Matrix C, [optional] alpha, [optional] beta )
+ */
+int main(int argc, char **argv)
+{
+    return utils::run_example<NESGEMMExample>(argc, argv);
+}