add python files to make dnnl_gemm run in benchmarker

benchmarker/frameworks/do_oneDNN_dnnl.py

@@ -0,0 +1,33 @@
+import os
+
+from benchmarker.util.abstractprocess import Process
+
+from .i_gemm import IGEMM
+
+
+class Benchmark(IGEMM):
+    def __init__(self, params, remaining_args=None):
+        super().__init__(params, remaining_args)
+        assert self.params["problem"]["precision"] in ["FP32", "mixed"]
+
+    def run(self):
+        if "nb_gpus" in self.params:
+            if self.params["nb_gpus"] > 0:
+                raise Exception("cblas does not work on GPU")
+        # TODO(Alex): this does not work inless the binaries are copied to site_packages
+        dirname = os.path.dirname(os.path.realpath(__file__))
+        path_binary = os.path.join(dirname, "../kernels", self.params["problem"].get("name"), self.params["framework"], "main")
+        if not os.path.isfile(path_binary):
+            raise (RuntimeError(f"{path_binary} not found, run make manually"))
+        command = [
+            path_binary,
+            self.params["problem"]["precision"],
+            *map(str, self.params["problem"]["size"]),
+            str(self.params["nb_epoch"]),
+        ]
+        process = Process(command=command)
+        result = process.get_output()
+        std_out = result["out"]
+        elapsed_time = float(std_out.strip())
+        self.params["time_total"] = elapsed_time
+        self.post_process()

benchmarker/kernels/gemm/oneDNN_dnnl.py

@@ -0,0 +1,2 @@
+def get_kernel(params):
+    return None