1 files changed, 69 insertions, 0 deletions
diff --git a/larson.py b/larson.py
new file mode 100644
index 0000000..5ba93fb
--- /dev/null
+++ b/larson.py
@@ -0,0 +1,69 @@
+import csv
+import pickle
+import matplotlib.pyplot as plt
+import multiprocessing
+import numpy as np
+import os
+import re
+import subprocess
+
+from benchmark import Benchmark
+
+throughput_re = re.compile("^Throughput =\s*(?P<throughput>\d+) operations per second.$")
+
+class Benchmark_Larson( Benchmark ):
+    def __init__(self):
+        self.name = "larson"
+        self.descrition = """This benchmark is courtesy of Paul Larson at Microsoft
+                             Research. It simulates a server: each thread allocates
+                             and deallocates objects, and then transfers some objects
+                             (randomly selected) to other threads to be freed."""
+
+        self.cmd = "build/larson{binary_suffix} 1 8 {maxsize} 1000 10000 1 {threads}"
+
+        self.args = {
+                        "maxsize" : [8, 32, 64, 128, 256, 512, 1024],
+                        "threads" : range(1, multiprocessing.cpu_count() * 2 + 1)
+                    }
+
+        self.requirements = ["build/larson"]
+        super().__init__()
+
+    def process_stdout(self, result, stdout, verbose):
+        for l in stdout.splitlines():
+            res = throughput_re.match(l)
+            if res:
+                result["throughput"] = int(res.group("throughput"))
+                return
+        print(stdout)
+        print("no match")
+
+    def summary(self, sd=None):
+        # Speedup thrash
+        args = self.results["args"]
+        nthreads = args["threads"]
+        targets = self.results["targets"]
+
+        sd = sd or ""
+
+        for arg in args:
+            loose_arg = [a for a in args if a != arg][0]
+            for arg_value in args[arg]:
+                for target in targets:
+                    y_vals = []
+                    for perm in self.iterate_args_fixed({arg : arg_value}, args=args):
+                        d = [m["throughput"] for m in self.results[target][perm]]
+                        y_vals.append(np.mean(d))
+                    x_vals = list(range(1, len(y_vals) + 1))
+                    plt.plot(x_vals, y_vals, marker='.', linestyle='-',
+                        label=target, color=targets[target]["color"])
+                plt.legend()
+                plt.xticks(x_vals, args[loose_arg])
+                plt.xlabel(loose_arg)
+                plt.ylabel("OPS/s")
+                plt.title("Larson: " + arg + " " + str(arg_value))
+                plt.savefig(os.path.join(sd, ".".join([self.name, arg, str(arg_value), "png"])))
+                plt.clf()
+
+
+larson = Benchmark_Larson()