Add single gemm comparison

test/onnx/gen_onnx.py

@@ -3924,6 +3924,36 @@ def matmul_bmbm_test():
     return ([node], [m1, m2], [y])
 
 
+@onnx_test()
+def matmul_half():
+    m1 = helper.make_tensor_value_info('1', TensorProto.FLOAT16, [1, 1, 1])
+    m2 = helper.make_tensor_value_info('2', TensorProto.FLOAT16, [1, 1, 1])
+    y = helper.make_tensor_value_info('y', TensorProto.FLOAT16, [1, 1, 1])
+
+    node = onnx.helper.make_node(
+        'MatMul',
+        inputs=['1', '2'],
+        outputs=['y'],
+    )
+
+    return ([node], [m1, m2], [y])
+
+
+@onnx_test()
+def matmul_int8():
+    m1 = helper.make_tensor_value_info('1', TensorProto.INT8, [1, 1, 1])
+    m2 = helper.make_tensor_value_info('2', TensorProto.INT8, [1, 1, 1])
+    y = helper.make_tensor_value_info('y', TensorProto.INT8, [1, 1, 1])
+
+    node = onnx.helper.make_node(
+        'MatMul',
+        inputs=['1', '2'],
+        outputs=['y'],
+    )
+
+    return ([node], [m1, m2], [y])
+
+
 @onnx_test()
 def matmul_bmv_test():
     m1 = helper.make_tensor_value_info('1', TensorProto.FLOAT, [3, 6, 7])

test/onnx/matmul_half.onnx

+matmul_half:k
+
+
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+
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y"MatMulmatmul_halfZ
+
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+
+
+

+

+
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+
+

+

+
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+
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+
+
+

+

+
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test/onnx/matmul_int8.onnx

+matmul_int8:k
+
+
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+
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y"MatMulmatmul_int8Z
+
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+
+

+

+
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+
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+
+

+

+
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+
+

+

+
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tools/gemm_perf.py

-import subprocess, csv, re, datetime
+#%matplotlib
+import subprocess, csv, re, datetime, argparse, os
+from subprocess import STDOUT, check_output
+from mpl_toolkits.mplot3d import Axes3D
+import matplotlib.pyplot as plt
+from pylab import *
+import random
+
+def parse_args():
+    parser = argparse.ArgumentParser(description="GEMM performance tools")
+    parser.add_argument('--bert',
+                        action='store_true',
+                        help='Run GEMM performance comparisons on BERT model')
+    parser.add_argument('--gemm',
+                        action='store_true',
+                        help='Run performance comparison on a range of GEMM problem sizes')
+    args = parser.parse_args()
+
+    return args
 
 
 class CSVFile:
@@ -83,7 +101,7 @@ def run_ck_perf(model, batch_size, int8=False, use_large_k=False):
     return [total_time] + gemm_times[1:]
 
 
-if __name__ == "__main__":
+def run_bert_perf():
     device_id = get_device_name()
     model = "/code/bert_base_cased_1_fp16_gpu.onnx"
     cf = CSVFile()
@@ -152,3 +170,48 @@ if __name__ == "__main__":
     # rocBLAS Only
     cf.write_row(["rocBLAS"] + run_perf(model, batch_size, quantize))
     cf.write_row()
+
+def gemm_perf(b, m, n, k, fp16):
+    print(f"{b}, {m}, {n}, {k}:", end=" ")
+    model = "../test/onnx/matmul_half.onnx" if fp16 else "../test/onnx/matmul_int8.onnx"
+    #rocBLAS run
+    cmd = f"MIGRAPHX_ENABLE_CK=0 ../build/bin/driver perf {model} --input-dim @1 {b} {m} {k} @2 {b} {k} {n}"
+    out = subprocess.run(cmd, capture_output=True, check=True, shell=True)
+    summary = re.findall("Summary.*", str(out.stdout))[0].replace("\\n", "\n")
+    # print(summary)
+    total_time = re.findall("Total time: \d+\.\d*", summary)[0]
+    total_time = total_time.replace("Total time: ", "")
+    rb_time = total_time
+
+    cmd = f"../build/bin/driver perf {model} --input-dim @1 {b} {m} {k} @2 {b} {k} {n} --exhaustive-tune"
+    try:
+        out = subprocess.run(cmd.split(), capture_output=True, check=True, timeout=300, env=dict(os.environ, MIGRAPHX_ENABLE_CK="1"))
+    except:
+        print("-69.0")
+        return -69.0
+
+    summary = re.findall("Summary.*", str(out.stdout))[0].replace("\\n", "\n")
+    # print(summary)
+    total_time = re.findall("Total time: \d+\.\d*", summary)[0]
+    total_time = total_time.replace("Total time: ", "")
+    ck_time = total_time
+
+    diff = float(ck_time)-float(rb_time)
+    print(f"{diff}")
+    return diff
+
+def run_gemm_perf():
+    batches = [1]
+    sizes = [64, 256, 384, 768, 1024, 2048, 2304, 3072]
+    results = [(b, m, n, k, gemm_perf(b, m, n, k, False)) for b in batches for m in sizes for n in sizes for k in sizes]
+    print(results)
+    with open("gemm_results.txt", "w+") as f:
+        for r in results:
+            f.write(f"{r[0]}, {r[1]}, {r[2]}, {r[3]}, {r[4]}\n")
+
+if __name__ == "__main__":
+    args = parse_args()
+    if args.bert:
+        run_bert_perf()
+    if args.gemm:
+        run_gemm_perf()
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