refactor out Graph-500 specific functions

benchmarks/python_e2e/reporting.py

@@ -56,38 +56,6 @@ def generate_console_report(benchmark_result_list):
 
     return retstring
 
-
-# FIXME: refactor this out since it is Graph500-specific
-def generate_graph500_console_report(benchmark_result_list):
-    """
-    Return a string suitable for printing to the console containing the
-    benchmark run results.
-    """
-    retstring = ""
-
-    # Assume results are ordered based on the order they were run, which for
-    # Graph500 is a single graph_create run, then a run for each search key for
-    # BFS, then for each search key for SSSP.
-    r = benchmark_result_list[0]
-    name = f"{r.name}({__namify_dict(r.params)})"
-    space = " " * (30 - len(name))
-    retstring += f"{name}{space}{r.runtime:.6}\n"
-
-    remaining_results = benchmark_result_list[1:]
-    half = len(remaining_results) // 2
-    bfs_results = remaining_results[:half]
-    sssp_results = remaining_results[half:]
-
-    for results in [bfs_results, sssp_results]:
-        retstring += f"{'-'*60}\n"
-        for r in results:
-            name = f"{r.name}({__namify_dict(r.params)})"
-            space = " " * (30 - len(name))
-            retstring += f"{name}{space}{r.runtime:.6}\n"
-
-    return retstring
-
-
 def update_csv_report(csv_results_file, benchmark_result_list, ngpus):
     """
     Update (or create if DNE) csv_results_file as a CSV file containing the
@@ -135,67 +103,3 @@ def update_csv_report(csv_results_file, benchmark_result_list, ngpus):
         writer.writeheader()
         for row in rows:
             writer.writerow(row)
-
-
-# FIXME: refactor this out since it is Graph500-specific
-def update_graph500_csv_report(csv_results_file, benchmark_result_list, ngpus):
-    """
-    Update (or create if DNE) csv_results_file as a CSV file containing the
-    benchmark results.  Rows are the overall avergage for each of the three
-    timed kernels, columns are number of GPUs.
-    """
-    times = {}
-    all_times = {}
-    all_names = set()
-
-    ngpus_key = f"ngpus_{ngpus}"
-
-    for r in benchmark_result_list:
-        name = r.name
-        all_names.add(name)
-        min_time_name = f"{name}_min"
-        max_time_name = f"{name}_max"
-
-        min_time = times.get(min_time_name)
-
-        if r.runtime > times.get(max_time_name, 0):
-            times[max_time_name] = r.runtime
-        if min_time is None or r.runtime < min_time:
-            times[min_time_name] = r.runtime
-        all_times.setdefault(name, []).append(r.runtime)
-
-    for name in all_times:
-        mean_time_name = f"{name}_mean"
-        times[mean_time_name] = sum(all_times[name]) / len(all_times[name])
-
-    rows = []
-
-    if path.exists(csv_results_file):
-        with open(csv_results_file) as csv_file:
-            reader = csv.DictReader(csv_file)
-            for row in reader:
-                row[ngpus_key] = times[row["name"]]
-                rows.append(row)
-
-    else:
-        for name in all_names:
-            min_time_name = f"{name}_min"
-            max_time_name = f"{name}_max"
-            mean_time_name = f"{name}_mean"
-
-            rows.append({"name": min_time_name,
-                         ngpus_key: times[min_time_name],
-                         })
-            rows.append({"name": max_time_name,
-                         ngpus_key: times[max_time_name],
-                         })
-            rows.append({"name": mean_time_name,
-                         ngpus_key: times[mean_time_name],
-                         })
-
-    with open(csv_results_file, "w") as csv_file:
-        field_names = sorted(rows[0].keys())
-        writer = csv.DictWriter(csv_file, fieldnames=field_names)
-        writer.writeheader()
-        for row in rows:
-            writer.writerow(row)