Merge branch 'gsoc2022-isosurface' of https://github.com/JulyCode/cgal into gsoc2022-isosurface

Isosurfacing_3/benchmark/Isosurfacing_3/benchmark.cpp

@@ -267,4 +267,6 @@ int main(int argc, char* argv[]) {
     }
 
     std::cout << "internal timer: " << ms << std::endl;
+    std::cout << "internal polygons: " << polygons.size() << std::endl;
+    std::cout << "internal points: " << points.size() << std::endl;
 }

Isosurfacing_3/benchmark/Isosurfacing_3/benchmark_size.py

@@ -1,12 +1,12 @@
 from benchmark_util import *
 
-scenario = "SCENARIO_GRID_SPHERE"
+scenario = "SCENARIO_IMPLICIT_IWP"
-kernel = "KERNEL_SIMPLE_CARTESIAN_FLOAT"
+kernel = "KERNEL_SIMPLE_CARTESIAN_DOUBLE"
-algorithm = "ALGO_DUAL_CONTOURING"
+algorithm = "ALGO_MARCHING_CUBES"
 tag = "TAG_SEQUENTIAL"
 threads = 1
 exponent = 1.2
-min_cells = 1000000
+min_cells = 100000
 max_cells = 100000000
 
 build(scenario, kernel, algorithm, tag)
@@ -17,11 +17,11 @@ c = min_cells
 while c < max_cells:
 	n = int(c ** (1.0 / 3.0))
 
-	time = execute(n, threads)
+	res = execute(n, threads, 5)
-	data.append([scenario, kernel, algorithm, tag, threads, int(c), time])
+	data.append([scenario, kernel, algorithm, tag, threads, int(c), res["time"], res["polygons"], res["points"]])
 
 	c *= exponent
 
-df = pd.DataFrame(data, columns=["scenario", "kernel", "algorithm", "tag", "threads", "cells", "time"])
+df = pd.DataFrame(data, columns=["scenario", "kernel", "algorithm", "tag", "threads", "cells", "time", "polygons", "points"])
 
 df.to_csv("benchmark_size.csv")

Isosurfacing_3/benchmark/Isosurfacing_3/benchmark_threads.py

@@ -1,12 +1,12 @@
 from benchmark_util import *
 
-scenario = "SCENARIO_IMPLICIT_SPHERE"
+scenario = "SCENARIO_IMPLICIT_IWP"
 kernel = "KERNEL_SIMPLE_CARTESIAN_DOUBLE"
 algorithm = "ALGO_MARCHING_CUBES"
 tag = "TAG_PARALLEL"
 min_threads = 1
-max_threads = 12
+max_threads = 26
-n = 300
+n = 500
 cells = n ** 3
 
 build(scenario, kernel, algorithm, tag)
@@ -14,10 +14,10 @@ build(scenario, kernel, algorithm, tag)
 data = []
 
 for t in range(min_threads, max_threads):
-	time = execute(n, t)
+	res = execute(n, t, times=5)
 
-	data.append([scenario, kernel, algorithm, tag, t, cells, time])
+	data.append([scenario, kernel, algorithm, tag, t, cells, res["time"], res["bandwidth"]])
 
-df = pd.DataFrame(data, columns=["scenario", "kernel", "algorithm", "tag", "threads", "cells", "time"])
+df = pd.DataFrame(data, columns=["scenario", "kernel", "algorithm", "tag", "threads", "cells", "time", "bandwidth"])
 
 df.to_csv("benchmark_threads.csv")

Isosurfacing_3/benchmark/Isosurfacing_3/benchmark_util.py

@@ -27,15 +27,47 @@ def build(scenario, kernel, algorithm, tag):
     run(["make", "-C", "build"])
 
 def execute(n, threads, times=1):
-    time = 0
+    measurements = {"time" : 0, "polygons" : 0, "points" : 0, "bandwidth" : 0, "transfer" : 0, "performance" : 0, "clock" : 0, "intensity" : 0}
+
     for i in range(times):
         process = run(["likwid-perfctr", "-g", "MEM_DP", "-C", "S0:0-" + str(threads - 1), "./build/benchmark", "-N", str(n)], False)
 
         for line in process.stdout.readlines():
             print(line, end='')
 
-            m = re.search(r'internal timer:\s*(\d*)', line)
+            m = re.search(r'internal timer:\s*(\d+)', line)
             if m is not None:
-                time += int(m.group(1))
+                measurements["time"] += int(m.group(1))
+
+            m = re.search(r'internal polygons:\s*(\d+)', line)
+            if m is not None:
+                measurements["polygons"] += int(m.group(1))
+
+            m = re.search(r'internal points:\s*(\d+)', line)
+            if m is not None:
+                measurements["points"] += int(m.group(1))
+
+            m = re.search(r'Memory bandwidth.*\s+(\d+(\.\d+)?) |\s*$', line)
+            if m is not None:
+                measurements["bandwidth"] += int(m.group(1))
+
+            m = re.search(r'Memory data volume.*\s+(\d+(\.\d+)?) |\s*$', line)
+            if m is not None:
+                measurements["transfer"] += int(m.group(1))
+
+            m = re.search(r'DP.*\s+(\d+(\.\d+)?) |\s*$', line)
+            if m is not None:
+                measurements["performance"] += int(m.group(1))
+
+            m = re.search(r'Clock.*\s+(\d+(\.\d+)?) |\s*$', line)
+            if m is not None:
+                measurements["clock"] += int(m.group(1))
+
+            m = re.search(r'Operational intensity.*\s+(\d+(\.\d+)?) |\s*$', line)
+            if m is not None:
+                measurements["intensity"] += int(m.group(1))
         
-    return time / times
+    for key, value in measurements:
+        measurements[key] = value / times
+
+    return measurements