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-rw-r--r--src/benchmark.py510
-rw-r--r--src/benchmarks/blowup.py12
-rw-r--r--src/benchmarks/cfrac.py26
-rw-r--r--src/benchmarks/espresso.py30
-rw-r--r--src/benchmarks/falsesharing.py39
-rw-r--r--src/benchmarks/fd.py23
-rw-r--r--src/benchmarks/httpd.py46
-rw-r--r--src/benchmarks/larson.py15
-rw-r--r--src/benchmarks/lld.py9
-rw-r--r--src/benchmarks/loop.py48
-rw-r--r--src/benchmarks/raxmlng.py29
-rw-r--r--src/plots.py518
12 files changed, 672 insertions, 633 deletions
diff --git a/src/benchmark.py b/src/benchmark.py
index fd094d0..6f81ba2 100644
--- a/src/benchmark.py
+++ b/src/benchmark.py
@@ -9,8 +9,6 @@ import os
import subprocess
from time import sleep
-import matplotlib
-import matplotlib.pyplot as plt
import numpy as np
import src.globalvars
@@ -18,9 +16,6 @@ import src.util
from src.util import print_status, print_error, print_warn
from src.util import print_info0, print_info, print_debug
-# This is useful when evaluating strings in the plot functions. str(np.NaN) == "nan"
-nan = np.NaN
-
class Benchmark:
"""Default implementation of most methods allocbench expects from a benchmark"""
@@ -568,508 +563,3 @@ class Benchmark:
stats["outliers"][dp] = outliers
self.results["stats"][alloc][perm] = stats
-
- ###### Summary helpers ######
- def _eval_with_stat(self, evaluation, alloc, perm, stat):
- try:
- s = evaluation.format(**self.results["stats"][alloc][perm][stat])
- except KeyError as e:
- import traceback
- print_warn(traceback.format_exc())
- print_warn(f"For {alloc} in {perm}")
- return nan
- return eval(s)
-
- def plot_single_arg(self, yval, ylabel="'y-label'", xlabel="'x-label'",
- autoticks=True, title="'default title'", filepostfix="",
- sumdir="", arg="", scale=None, file_ext=src.globalvars.summary_file_ext):
-
- args = self.results["args"]
- allocators = self.results["allocators"]
-
- arg = arg or list(args.keys())[0]
-
- if not autoticks:
- x_vals = list(range(1, len(args[arg]) + 1))
- else:
- x_vals = args[arg]
-
- for allocator in allocators:
- y_vals = []
- for perm in self.iterate_args(args=args):
- if scale:
- if scale == allocator:
- y_vals = [1] * len(x_vals)
- else:
- mean = self._eval_with_stat(yval, allocator, perm, "mean")
- norm_mean = self._eval_with_stat(yval, scale, perm, "mean")
- y_vals.append(mean / norm_mean)
- else:
- y_vals.append(self._eval_with_stat(yval, allocator, perm, "mean"))
-
- plt.plot(x_vals, y_vals, marker='.', linestyle='-',
- label=allocator, color=allocators[allocator]["color"])
-
- plt.legend(loc="best")
- if not autoticks:
- plt.xticks(x_vals, args[arg])
- plt.xlabel(eval(xlabel))
- plt.ylabel(eval(ylabel))
- plt.title(eval(title))
- figname = os.path.join(sumdir, f"{self.name}.{filepostfix}.{file_ext}")
- if figname.endswith(".tex"):
- import tikzplotlib
- tikzplotlib.save(figname)
- else:
- plt.savefig(figname)
- plt.clf()
-
- def barplot_single_arg(self, yval, ylabel="'y-label'", xlabel="'x-label'",
- title="'default title'", filepostfix="", sumdir="",
- arg="", scale=None, file_ext=src.globalvars.summary_file_ext, yerr=True):
-
- args = self.results["args"]
- allocators = self.results["allocators"]
- nallocators = len(allocators)
-
- if arg:
- arg = args[arg]
- elif args.keys():
- arg = args[list(args.keys())[0]]
- else:
- arg = [""]
-
- narg = len(arg)
-
- for i, allocator in enumerate(allocators):
- x_vals = list(range(i, narg * (nallocators+1), nallocators+1))
- y_vals = []
- y_errs = None
- if yerr:
- y_errs = []
-
- for perm in self.iterate_args(args=args):
- if scale:
- if scale == allocator:
- y_vals = [1] * len(x_vals)
- else:
- mean = self._eval_with_stat(yval, allocator, perm, "mean")
- norm_mean = self._eval_with_stat(yval, scale, perm, "mean")
- y_vals.append(mean / norm_mean)
- else:
- y_vals.append(self._eval_with_stat(yval, allocator, perm, "mean"))
-
- if yerr:
- y_errs.append(self._eval_with_stat(yval, allocator, perm, "std"))
-
- plt.bar(x_vals, y_vals, width=1, label=allocator, yerr=y_errs,
- color=allocators[allocator]["color"])
-
- plt.legend(loc="best")
- plt.xticks(list(range(int(np.floor(nallocators/2)), narg*(nallocators+1), nallocators+1)), arg)
- plt.xlabel(eval(xlabel))
- plt.ylabel(eval(ylabel))
- plt.title(eval(title))
- figname = os.path.join(sumdir, f"{self.name}.{filepostfix}.{file_ext}")
- if figname.endswith(".tex"):
- import tikzplotlib
- tikzplotlib.save(figname)
- else:
- plt.savefig(figname)
- plt.clf()
-
- def plot_fixed_arg(self, yval, ylabel="'y-label'", xlabel="loose_arg",
- autoticks=True, title="'default title'", filepostfix="",
- sumdir="", fixed=[], file_ext=src.globalvars.summary_file_ext, scale=None):
-
- args = self.results["args"]
- allocators = self.results["allocators"]
-
- for arg in fixed or args:
- loose_arg = [a for a in args if a != arg][0]
-
- if not autoticks:
- x_vals = list(range(1, len(args[loose_arg]) + 1))
- else:
- x_vals = args[loose_arg]
-
- for arg_value in args[arg]:
- for allocator in allocators:
- y_vals = []
- for perm in self.iterate_args_fixed({arg: arg_value}, args=args):
- if scale:
- if scale == allocator:
- y_vals = [1] * len(x_vals)
- else:
- mean = self._eval_with_stat(yval, allocator, perm, "mean")
- norm_mean = self._eval_with_stat(yval, scale, perm, "mean")
- y_vals.append(mean / norm_mean)
- else:
- y_vals.append(self._eval_with_stat(yval, allocator, perm, "mean"))
-
- plt.plot(x_vals, y_vals, marker='.', linestyle='-',
- label=allocator, color=allocators[allocator]["color"])
-
- plt.legend(loc="best")
- if not autoticks:
- plt.xticks(x_vals, args[loose_arg])
- plt.xlabel(eval(xlabel))
- plt.ylabel(eval(ylabel))
- plt.title(eval(title))
- figname = os.path.join(sumdir,
- f"{self.name}.{arg}.{arg_value}.{filepostfix}.{file_ext}")
- if figname.endswith(".tex"):
- import tikzplotlib
- tikzplotlib.save(figname)
- else:
- plt.savefig(figname)
- plt.clf()
-
- def export_facts_to_file(self, comment_symbol, f):
- """Write collected facts about used system and benchmark to file"""
- print(comment_symbol, self.name, file=f)
- print(file=f)
- print(comment_symbol, "Common facts:", file=f)
- for k, v in src.facter.FACTS.items():
- print(comment_symbol, k + ":", v, file=f)
- print(file=f)
- print(comment_symbol, "Benchmark facts:", file=f)
- for k, v in self.results["facts"].items():
- print(comment_symbol, k + ":", v, file=f)
- print(file=f)
-
- def export_stats_to_csv(self, datapoint, path=None):
- """Write descriptive statistics about datapoint to csv file"""
- allocators = self.results["allocators"]
- args = self.results["args"]
- stats = self.results["stats"]
-
- if path is None:
- path = datapoint
-
- path = path + ".csv"
-
- stats_fields = list(stats[list(allocators)[0]][list(self.iterate_args(args=args))[0]])
- fieldnames = ["allocator", *args, *stats_fields]
- widths = []
- for fieldname in fieldnames:
- widths.append(len(fieldname) + 2)
-
- # collect rows
- rows = {}
- for alloc in allocators:
- rows[alloc] = {}
- for perm in self.iterate_args(args=args):
- d = []
- d.append(alloc)
- d += list(perm._asdict().values())
- d += [stats[alloc][perm][s][datapoint] for s in stats[alloc][perm]]
- d[-1] = (",".join([str(x) for x in d[-1]]))
- rows[alloc][perm] = d
-
- # calc widths
- for i in range(0, len(fieldnames)):
- for alloc in allocators:
- for perm in self.iterate_args(args=args):
- field_len = len(str(rows[alloc][perm][i])) + 2
- if field_len > widths[i]:
- widths[i] = field_len
-
- with open(path, "w") as f:
- headerline = ""
- for i, h in enumerate(fieldnames):
- headerline += h.capitalize().ljust(widths[i]).replace("_", "-")
- print(headerline, file=f)
-
- for alloc in allocators:
- for perm in self.iterate_args(args=args):
- line = ""
- for i, x in enumerate(rows[alloc][perm]):
- line += str(x).ljust(widths[i])
- print(line.replace("_", "-"), file=f)
-
- def export_stats_to_dataref(self, datapoint, path=None):
- """Write descriptive statistics about datapoint to dataref file"""
- stats = self.results["stats"]
-
- if path is None:
- path = datapoint
-
- path = path + ".dataref"
-
- # Example: \drefset{/mysql/glibc/40/Lower-whisker}{71552.0}
- line = "\\drefset{{/{}/{}/{}/{}}}{{{}}}"
-
- with open(path, "w") as f:
- # Write facts to file
- self.export_facts_to_file("%", f)
-
- for alloc in self.results["allocators"]:
- for perm in self.iterate_args(args=self.results["args"]):
- for statistic, values in stats[alloc][perm].items():
- cur_line = line.format(self.name, alloc,
- "/".join([str(p) for p in list(perm)]),
- statistic, values[datapoint])
- # Replace empty outliers
- cur_line.replace("[]", "")
- # Replace underscores
- cur_line.replace("_", "-")
- print(cur_line, file=f)
-
- def write_best_doublearg_tex_table(self, evaluation, sort=">",
- filepostfix="", sumdir="", std=False):
- args = self.results["args"]
- keys = list(args.keys())
- allocators = self.results["allocators"]
-
- header_arg = keys[0] if len(args[keys[0]]) < len(args[keys[1]]) else keys[1]
- row_arg = [arg for arg in args if arg != header_arg][0]
-
- headers = args[header_arg]
- rows = args[row_arg]
-
- cell_text = []
- for av in rows:
- row = []
- for perm in self.iterate_args_fixed({row_arg: av}, args=args):
- best = []
- best_val = None
- for allocator in allocators:
- d = []
- for m in self.results[allocator][perm]:
- d.append(eval(evaluation.format(**m)))
- mean = np.mean(d)
- if not best_val:
- best = [allocator]
- best_val = mean
- elif ((sort == ">" and mean > best_val)
- or (sort == "<" and mean < best_val)):
- best = [allocator]
- best_val = mean
- elif mean == best_val:
- best.append(allocator)
-
- row.append("{}: {:.3f}".format(best[0], best_val))
- cell_text.append(row)
-
- fname = os.path.join(sumdir, ".".join([self.name, filepostfix, "tex"]))
- with open(fname, "w") as f:
- print("\\documentclass{standalone}", file=f)
- print("\\begin{document}", file=f)
- print("\\begin{tabular}{|", end="", file=f)
- print(" l |" * len(headers), "}", file=f)
-
- print(header_arg+"/"+row_arg, end=" & ", file=f)
- for header in headers[:-1]:
- print(header, end="& ", file=f)
- print(headers[-1], "\\\\", file=f)
-
- for i, row in enumerate(cell_text):
- print(rows[i], end=" & ", file=f)
- for e in row[:-1]:
- print(e, end=" & ", file=f)
- print(row[-1], "\\\\", file=f)
- print("\\end{tabular}", file=f)
- print("\\end{document}", file=f)
-
- def write_tex_table(self, entries, sort=">",
- filepostfix="", sumdir="", std=False):
- """generate a latex standalone table from an list of entries dictionaries
-
- Entries must have at least the two keys: "label" and "expression".
- The optional "sort" key specifies the direction of the order:
- ">" : bigger is better.
- "<" : smaller is better.
-
- Table layout:
-
- | alloc1 | alloc2 | ....
- ---------------------------------------
- | name1 name2 | ...
- ---------------------------------------
- perm1 | eavl1 eval2 | ...
- perm2 | eval1 eval2 | ...
- """
- args = self.results["args"]
- allocators = self.results["allocators"]
- nallocators = len(allocators)
- nentries = len(entries)
- perm_fields = self.Perm._fields
- nperm_fields = len(perm_fields)
-
- alloc_header_line = f"\\multicolumn{{{nperm_fields}}}{{c|}}{{}} &"
- for alloc in allocators:
- alloc_header_line += f"\\multicolumn{{{nentries}}}{{c|}}{{{alloc}}} &"
- alloc_header_line = alloc_header_line[:-1] + "\\\\"
-
- perm_fields_header = ""
- for field in self.Perm._fields:
- perm_fields_header += f'{field} &'
- entry_header_line = ""
- for entry in entries:
- entry_header_line += f'{entry["label"]} &'
- entry_header_line = perm_fields_header + entry_header_line * nallocators
- entry_header_line = entry_header_line[:-1] + "\\\\"
-
- fname = os.path.join(sumdir, ".".join([self.name, filepostfix, "tex"]))
- with open(fname, "w") as f:
- print("\\documentclass{standalone}", file=f)
- print("\\usepackage{booktabs}", file=f)
- print("\\usepackage{xcolor}", file=f)
- print("\\begin{document}", file=f)
- print("\\begin{tabular}{|", f"{'c|'*nperm_fields}", f"{'c'*nentries}|"*nallocators, "}", file=f)
- print("\\toprule", file=f)
-
- print(alloc_header_line, file=f)
- print("\\hline", file=f)
- print(entry_header_line, file=f)
- print("\\hline", file=f)
-
- for perm in self.iterate_args(args=args):
- values = [[] for _ in entries]
- maxs = [None for _ in entries]
- mins = [None for _ in entries]
- for allocator in allocators:
- for i, entry in enumerate(entries):
- expr = entry["expression"]
- values[i].append(eval(expr.format(**self.results["stats"][allocator][perm]["mean"])))
-
- # get max and min for each entry
- for i, entry in enumerate(entries):
- if not "sort" in entry:
- continue
- # bigger is better
- elif entry["sort"] == ">":
- maxs[i] = max(values[i])
- mins[i] = min(values[i])
- # smaller is better
- elif entry["sort"] == "<":
- mins[i] = max(values[i])
- maxs[i] = min(values[i])
-
- # build row
- row = ""
- perm_dict = perm._asdict()
- for field in perm_fields:
- row += str(perm_dict[field]) + "&"
-
- for i, _ in enumerate(allocators):
- for y, entry_vals in enumerate(values):
- val = entry_vals[i]
-
- # format
- val_str = str(val)
- if type(val) == float:
- val_str = f"{val:.2f}"
-
- # colorize
- if val == maxs[y]:
- val_str = f"\\textcolor{{green}}{{{val_str}}}"
- elif val == mins[y]:
- val_str = f"\\textcolor{{red}}{{{val_str}}}"
- row += f"{val_str} &"
- #escape _ for latex
- row = row.replace("_", "\\_")
- print(row[:-1], "\\\\", file=f)
-
- print("\\end{tabular}", file=f)
- print("\\end{document}", file=f)
-
- def pgfplot_legend(self, sumdir=""):
-
- allocators = self.results["allocators"]
- s =\
-"""
-\\documentclass{standalone}
-\\usepackage{pgfplots}
-
-\\usepackage{pgfkeys}
-
-\\newenvironment{customlegend}[1][]{%
-\t\\begingroup
-\t\\csname pgfplots@init@cleared@structures\\endcsname
-\t\\pgfplotsset{#1}%
-}{%
-\t\\csname pgfplots@createlegend\\endcsname
-\t\\endgroup
-}%
-\\def\\addlegendimage{\\csname pgfplots@addlegendimage\\endcsname}
-
-\\usepackage{xcolor}
-"""
-
- for alloc_name, alloc_dict in allocators.items():
- # define color
- rgb = matplotlib.colors.to_rgb(alloc_dict["color"])
- s += f"\\providecolor{{{alloc_name}-color}}{{rgb}}{{{rgb[0]},{rgb[1]},{rgb[2]}}}\n"
-
- s +=\
-"""
-\\begin{document}
-\\begin{tikzpicture}
-\\begin{customlegend}[
-\tlegend entries={"""
-
- alloc_list = ""
- addlegendimage_list = ""
- for alloc_name in allocators:
- alloc_list += f"{alloc_name}, "
- addlegendimage_list += "\t\\addlegendimage{}\n"
-
- s += alloc_list[:-2] + "},\n]"
- s += addlegendimage_list
- s +=\
-"""
-\\end{customlegend}
-\\end{tikzpicture}
-\\end{document}"""
-
- with open(os.path.join(sumdir, "legend.tex"), "w") as legend_file:
- print(s, file=legend_file)
-
- def pgfplot_linear(self, perms, xval, yval, ylabel="'y-label'", xlabel="'x-label'",
- title="'default title'", postfix="", sumdir="", scale=None):
-
- allocators = self.results["allocators"]
- perms = list(perms)
- title = eval(title)
- s =\
-"""\\documentclass{standalone}
-\\usepackage{pgfplots}
-\\usepackage{xcolor}
-"""
-
- for alloc_name, alloc_dict in allocators.items():
- s += f"\\begin{{filecontents*}}{{{alloc_name}.dat}}\n"
- for i, perm in enumerate(perms):
- x = self._eval_with_stat(xval, alloc_name, perm, "mean")
- y = self._eval_with_stat(yval, alloc_name, perm, "mean")
- s += f"{x} {y}\n"
- s += "\\end{filecontents*}\n"
-
- # define color
- rgb = matplotlib.colors.to_rgb(alloc_dict["color"])
- s += f"\\providecolor{{{alloc_name}-color}}{{rgb}}{{{rgb[0]},{rgb[1]},{rgb[2]}}}\n"
-
- s +=\
-f"""
-\\begin{{document}}
-\\begin{{tikzpicture}}
-\\begin{{axis}}[
-\ttitle={{{title}}},
-\txlabel={{{eval(xlabel)}}},
-\tylabel={{{eval(ylabel)}}},
-]
-"""
-
- for alloc_name in allocators:
- s += f"\\addplot [{alloc_name}-color] table {{{alloc_name}.dat}};\n"
- # s += f"\t\\addplot table {{{alloc_name}.dat}};\n"
-
- s +=\
-"""\\end{axis}
-\\end{tikzpicture}
-\\end{document}"""
-
- with open(os.path.join(sumdir, f"{self.name}.{postfix}.tex"), "w") as plot_file:
- print(s, file=plot_file)
diff --git a/src/benchmarks/blowup.py b/src/benchmarks/blowup.py
index aca9293..8f8e550 100644
--- a/src/benchmarks/blowup.py
+++ b/src/benchmarks/blowup.py
@@ -17,6 +17,7 @@
"""Definition of the blowup micro benchmark"""
from src.benchmark import Benchmark
+import src.plots as plt
class BenchmarkBlowup(Benchmark):
@@ -53,15 +54,16 @@ class BenchmarkBlowup(Benchmark):
}
}
- self.barplot_single_arg("{VmHWM}/1000",
- ylabel='"VmHWM in MB"',
- title='"blowup test"',
- filepostfix="vmhwm")
+ plt.barplot_single_arg(self,
+ "{VmHWM}/1000",
+ ylabel='"VmHWM in MB"',
+ title='"blowup test"',
+ filepostfix="vmhwm")
del allocators["Ideal-RSS"]
del self.results["stats"]["Ideal-RSS"]
- self.export_stats_to_dataref("VmHWM")
+ plt.export_stats_to_dataref(self, "VmHWM")
blowup = BenchmarkBlowup()
diff --git a/src/benchmarks/cfrac.py b/src/benchmarks/cfrac.py
index dfd87d6..34c0894 100644
--- a/src/benchmarks/cfrac.py
+++ b/src/benchmarks/cfrac.py
@@ -59,6 +59,7 @@ API function as well as memory placement strategies with good data locality.
"""
from src.benchmark import Benchmark
+import src.plots as plt
class BenchmarkCfrac(Benchmark):
@@ -75,13 +76,15 @@ class BenchmarkCfrac(Benchmark):
def summary(self):
# Speed
- self.barplot_single_arg("{task-clock}/1000",
- ylabel='"cpu-second"',
- title='"Cfrac: runtime"',
- filepostfix="time")
+ plt.barplot_single_arg(self,
+ "{task-clock}/1000",
+ ylabel='"cpu-second"',
+ title='"Cfrac: runtime"',
+ filepostfix="time")
# L1 cache misses
- self.barplot_single_arg(
+ plt.barplot_single_arg(
+ self,
"({L1-dcache-load-misses}/{L1-dcache-loads})*100",
ylabel='"L1 misses in %"',
title='"Cfrac l1 cache misses"',
@@ -89,10 +92,11 @@ class BenchmarkCfrac(Benchmark):
yerr=False)
# Memusage
- self.barplot_single_arg("{VmHWM}",
- ylabel='"VmHWM in KB"',
- title='"Cfrac VmHWM"',
- filepostfix="vmhwm")
+ plt.barplot_single_arg(self,
+ "{VmHWM}",
+ ylabel='"VmHWM in KB"',
+ title='"Cfrac VmHWM"',
+ filepostfix="vmhwm")
self.write_tex_table([{
"label": "Runtime [ms]",
@@ -105,9 +109,9 @@ class BenchmarkCfrac(Benchmark):
}],
filepostfix="table")
- self.export_stats_to_dataref("task-clock")
+ plt.export_stats_to_dataref(self, "task-clock")
- self.export_stats_to_dataref("VmHWM")
+ plt.export_stats_to_dataref(self, "VmHWM")
cfrac = BenchmarkCfrac()
diff --git a/src/benchmarks/espresso.py b/src/benchmarks/espresso.py
index 2f8b8bf..1c9d4d2 100644
--- a/src/benchmarks/espresso.py
+++ b/src/benchmarks/espresso.py
@@ -59,6 +59,7 @@ import os
from src.benchmark import Benchmark
import src.globalvars
+import src.plots as plt
class BenchmarkEspresso(Benchmark):
@@ -79,13 +80,15 @@ class BenchmarkEspresso(Benchmark):
def summary(self):
# Speed
- self.barplot_single_arg("{task-clock}/1000",
- ylabel='"cpu-second"',
- title='"Espresso: runtime"',
- filepostfix="time")
+ plt.barplot_single_arg(self,
+ "{task-clock}/1000",
+ ylabel='"cpu-second"',
+ title='"Espresso: runtime"',
+ filepostfix="time")
# L1 cache misses
- self.barplot_single_arg(
+ plt.barplot_single_arg(
+ self,
"({L1-dcache-load-misses}/{L1-dcache-loads})*100",
ylabel='"L1 misses in %"',
title='"Espresso l1 cache misses"',
@@ -93,12 +96,13 @@ class BenchmarkEspresso(Benchmark):
yerr=False)
# Memusage
- self.barplot_single_arg("{VmHWM}",
- ylabel='"VmHWM in KB"',
- title='"Espresso VmHWM"',
- filepostfix="vmhwm")
+ plt.barplot_single_arg(self,
+ "{VmHWM}",
+ ylabel='"VmHWM in KB"',
+ title='"Espresso VmHWM"',
+ filepostfix="vmhwm")
- self.write_tex_table([{
+ plt.write_tex_table(self, [{
"label": "Runtime [ms]",
"expression": "{task-clock}",
"sort": "<"
@@ -107,11 +111,11 @@ class BenchmarkEspresso(Benchmark):
"expression": "{VmHWM}",
"sort": "<"
}],
- filepostfix="table")
+ filepostfix="table")
- self.export_stats_to_dataref("task-clock")
+ plt.export_stats_to_dataref(self, "task-clock")
- self.export_stats_to_dataref("VmHWM")
+ plt.export_stats_to_dataref(self, "VmHWM")
espresso = BenchmarkEspresso()
diff --git a/src/benchmarks/falsesharing.py b/src/benchmarks/falsesharing.py
index 530ca99..626104a 100644
--- a/src/benchmarks/falsesharing.py
+++ b/src/benchmarks/falsesharing.py
@@ -23,6 +23,7 @@ import numpy as np
from src.benchmark import Benchmark
from src.globalvars import summary_file_ext
+import src.plots as plt
TIME_RE = re.compile("^Time elapsed = (?P<time>\\d*\\.\\d*) seconds.$")
@@ -78,14 +79,16 @@ class BenchmarkFalsesharing(Benchmark):
del self.results["stats"]
self.calc_desc_statistics()
- self.plot_fixed_arg("{speedup}",
- ylabel="'Speedup'",
- title="'Speedup: ' + arg + ' ' + str(arg_value)",
- filepostfix="speedup",
- autoticks=False,
- fixed=["bench"])
+ plt.plot_fixed_arg(self,
+ "{speedup}",
+ ylabel="'Speedup'",
+ title="'Speedup: ' + arg + ' ' + str(arg_value)",
+ filepostfix="speedup",
+ autoticks=False,
+ fixed=["bench"])
- self.plot_fixed_arg(
+ plt.plot_fixed_arg(
+ self,
"{l1chache_misses}",
ylabel="'l1 cache misses in %'",
title="'cache misses: ' + arg + ' ' + str(arg_value)",
@@ -93,23 +96,23 @@ class BenchmarkFalsesharing(Benchmark):
autoticks=False,
fixed=["bench"])
- self.plot_fixed_arg(
- "({LLC-load-misses}/{LLC-loads})*100",
- ylabel="'llc cache misses in %'",
- title="'LLC misses: ' + arg + ' ' + str(arg_value)",
- filepostfix="llc-misses",
- autoticks=False,
- fixed=["bench"])
+ plt.plot_fixed_arg(self,
+ "({LLC-load-misses}/{LLC-loads})*100",
+ ylabel="'llc cache misses in %'",
+ title="'LLC misses: ' + arg + ' ' + str(arg_value)",
+ filepostfix="llc-misses",
+ autoticks=False,
+ fixed=["bench"])
- self.write_tex_table([{
+ plt.write_tex_table(self, [{
"label": "Speedup",
"expression": "{speedup}",
"sort": ">"
}],
- filepostfix="speedup.table")
+ filepostfix="speedup.table")
- self.export_stats_to_csv("speedup", "time")
- self.export_stats_to_csv("l1chache_misses", "l1-misses")
+ plt.export_stats_to_csv(self, "speedup", "time")
+ plt.export_stats_to_csv(self, "l1chache_misses", "l1-misses")
falsesharing = BenchmarkFalsesharing()
diff --git a/src/benchmarks/fd.py b/src/benchmarks/fd.py
index 4fab958..bede21a 100644
--- a/src/benchmarks/fd.py
+++ b/src/benchmarks/fd.py
@@ -22,6 +22,7 @@ from urllib.request import urlretrieve
from src.artifact import ArchiveArtifact, GitArtifact
from src.benchmark import Benchmark
+import src.plots as plt
from src.util import print_info
@@ -66,19 +67,21 @@ class BenchmarkFd(Benchmark):
os.link(src, dest)
def summary(self):
- self.barplot_single_arg("{task-clock}",
- ylabel='"runtime in ms"',
- title='"fd runtime"',
- filepostfix="runtime")
+ plt.barplot_single_arg(self,
+ "{task-clock}",
+ ylabel='"runtime in ms"',
+ title='"fd runtime"',
+ filepostfix="runtime")
- self.export_stats_to_dataref("task-clock")
+ plt.export_stats_to_dataref(self, "task-clock")
- self.barplot_single_arg("{VmHWM}",
- ylabel='"VmHWM in KB"',
- title='"fd memusage"',
- filepostfix="memusage")
+ plt.barplot_single_arg(self,
+ "{VmHWM}",
+ ylabel='"VmHWM in KB"',
+ title='"fd memusage"',
+ filepostfix="memusage")
- self.export_stats_to_dataref("VmHWM")
+ plt.export_stats_to_dataref(self, "VmHWM")
fd = BenchmarkFd()
diff --git a/src/benchmarks/httpd.py b/src/benchmarks/httpd.py
index 64f8e11..2a848c5 100644
--- a/src/benchmarks/httpd.py
+++ b/src/benchmarks/httpd.py
@@ -20,6 +20,7 @@ import re
from src.benchmark import Benchmark
import src.facter
+import src.plots as plt
class BenchmarkHTTPD(Benchmark):
@@ -59,28 +60,29 @@ class BenchmarkHTTPD(Benchmark):
"Requests per second:\\s*(\\d*\\.\\d*) .*", stdout).group(1)
def summary(self):
- allocators = self.results["allocators"]
-
- self.plot_fixed_arg("{requests}",
- xlabel='"threads"',
- ylabel='"requests/s"',
- autoticks=False,
- filepostfix="requests",
- title='perm.site + ": requests/s"')
-
- self.plot_fixed_arg("{nginx_vmhwm}",
- xlabel='"threads"',
- ylabel='"VmHWM in KB"',
- title='perm.site + ": nginx memory usage"',
- filepostfix="httpd_vmhwm",
- autoticks=False)
-
- self.plot_fixed_arg("{php-fpm_vmhwm}",
- xlabel='"threads"',
- ylabel='"VmHWM in KB"',
- title='perm.site + ": php-fpm memory usage"',
- filepostfix="php-fpm_vmhwm",
- autoticks=False)
+ plt.plot_fixed_arg(self,
+ "{requests}",
+ xlabel='"threads"',
+ ylabel='"requests/s"',
+ autoticks=False,
+ filepostfix="requests",
+ title='perm.site + ": requests/s"')
+
+ plt.plot_fixed_arg(self,
+ "{nginx_vmhwm}",
+ xlabel='"threads"',
+ ylabel='"VmHWM in KB"',
+ title='perm.site + ": nginx memory usage"',
+ filepostfix="httpd_vmhwm",
+ autoticks=False)
+
+ plt.plot_fixed_arg(self,
+ "{php-fpm_vmhwm}",
+ xlabel='"threads"',
+ ylabel='"VmHWM in KB"',
+ title='perm.site + ": php-fpm memory usage"',
+ filepostfix="php-fpm_vmhwm",
+ autoticks=False)
httpd = BenchmarkHTTPD()
diff --git a/src/benchmarks/larson.py b/src/benchmarks/larson.py
index 6e55fbe..8fce9ed 100644
--- a/src/benchmarks/larson.py
+++ b/src/benchmarks/larson.py
@@ -48,6 +48,7 @@ false sharing because it uses multiple threads, which pass memory around.
import re
from src.benchmark import Benchmark
+import src.plots as plt
THROUGHPUT_RE = re.compile(
"^Throughput =\\s*(?P<throughput>\\d+) operations per second.$")
@@ -80,12 +81,14 @@ class BenchmarkLarson(Benchmark):
def summary(self):
# Plot threads->throughput and maxsize->throughput
- self.plot_fixed_arg("{throughput}/1000000",
- ylabel="'MOPS/s'",
- title="'Larson: ' + arg + ' ' + str(arg_value)",
- filepostfix="throughput")
-
- self.plot_fixed_arg(
+ plt.plot_fixed_arg(self,
+ "{throughput}/1000000",
+ ylabel="'MOPS/s'",
+ title="'Larson: ' + arg + ' ' + str(arg_value)",
+ filepostfix="throughput")
+
+ plt.plot_fixed_arg(
+ self,
"({L1-dcache-load-misses}/{L1-dcache-loads})*100",
ylabel="'l1 cache misses in %'",
title="'Larson cache misses: ' + arg + ' ' + str(arg_value)",
diff --git a/src/benchmarks/lld.py b/src/benchmarks/lld.py
index 3657896..b2da35b 100644
--- a/src/benchmarks/lld.py
+++ b/src/benchmarks/lld.py
@@ -204,6 +204,7 @@ import matplotlib.pyplot as plt
from src.artifact import ArchiveArtifact
from src.benchmark import Benchmark
import src.facter
+import src.plots
from src.globalvars import summary_file_ext
@@ -283,17 +284,17 @@ class BenchmarkLld(Benchmark):
plt.clf()
# self.export_stats_to_csv("VmHWM")
- self.export_stats_to_csv("task-clock")
+ src.plots.export_stats_to_csv("task-clock")
# self.export_stats_to_dataref("VmHWM")
- self.export_stats_to_dataref("task-clock")
+ src.plots.export_stats_to_dataref("task-clock")
- self.write_tex_table([{
+ src.plots.write_tex_table([{
"label": "Runtime [ms]",
"expression": "{task-clock}",
"sort": "<"
}],
- filepostfix="table")
+ filepostfix="table")
lld = BenchmarkLld()
diff --git a/src/benchmarks/loop.py b/src/benchmarks/loop.py
index a969f4a..75c56ee 100644
--- a/src/benchmarks/loop.py
+++ b/src/benchmarks/loop.py
@@ -35,6 +35,7 @@ Interpretation:
"""
from src.benchmark import Benchmark
+import src.plots as plt
class BenchmarkLoop(Benchmark):
@@ -57,14 +58,16 @@ class BenchmarkLoop(Benchmark):
def summary(self):
# Speed
- self.plot_fixed_arg("perm.nthreads / ({task-clock}/1000)",
- ylabel='"MOPS/cpu-second"',
- title='"Loop: " + arg + " " + str(arg_value)',
- filepostfix="time",
- autoticks=False)
+ plt.plot_fixed_arg(self,
+ "perm.nthreads / ({task-clock}/1000)",
+ ylabel='"MOPS/cpu-second"',
+ title='"Loop: " + arg + " " + str(arg_value)',
+ filepostfix="time",
+ autoticks=False)
# L1 cache misses
- self.plot_fixed_arg(
+ plt.plot_fixed_arg(
+ self,
"({L1-dcache-load-misses}/{L1-dcache-loads})*100",
ylabel='"L1 misses in %"',
title='"Loop l1 cache misses: " + arg + " " + str(arg_value)',
@@ -72,29 +75,34 @@ class BenchmarkLoop(Benchmark):
autoticks=False)
# Speed Matrix
- self.write_best_doublearg_tex_table(
- "perm.nthreads / ({task-clock}/1000)", filepostfix="time.matrix")
+ plt.write_best_doublearg_tex_table(
+ self,
+ "perm.nthreads / ({task-clock}/1000)",
+ filepostfix="time.matrix")
- self.write_tex_table([{
+ plt.write_tex_table(self, [{
"label": "MOPS/s",
"expression": "perm.nthreads / ({task-clock}/1000)",
"sort": ">"
}],
- filepostfix="mops.table")
+ filepostfix="mops.table")
- self.export_stats_to_csv("task-clock")
- self.export_stats_to_dataref("task-clock")
+ plt.export_stats_to_csv(self, "task-clock")
+ plt.export_stats_to_dataref(self, "task-clock")
# pgfplot test
- self.pgfplot_linear(self.iterate_args_fixed({"maxsize": 1024}, args=self.results["args"]),
- "int(perm.nthreads)",
- "perm.nthreads / ({task-clock}/1000)",
- xlabel='"Threads"',
- ylabel='"MOPS/cpu-second"',
- title='"Loop: 1024B"',
- postfix='mops_1024B')
+ plt.pgfplot_linear(self,
+ self.iterate_args_fixed({"maxsize": 1024},
+ args=self.results["args"]),
+ "int(perm.nthreads)",
+ "perm.nthreads / ({task-clock}/1000)",
+ xlabel='"Threads"',
+ ylabel='"MOPS/cpu-second"',
+ title='"Loop: 1024B"',
+ postfix='mops_1024B')
# create pgfplot legend
- self.pgfplot_legend()
+ plt.pgfplot_legend(self)
+
loop = BenchmarkLoop()
diff --git a/src/benchmarks/raxmlng.py b/src/benchmarks/raxmlng.py
index 05a6ca7..228c220 100644
--- a/src/benchmarks/raxmlng.py
+++ b/src/benchmarks/raxmlng.py
@@ -18,11 +18,10 @@
import os
import re
-import sys
-from urllib.request import urlretrieve
from src.artifact import GitArtifact
from src.benchmark import Benchmark
+import src.plots as plt
from src.util import print_info, run_cmd
RUNTIME_RE = re.compile("Elapsed time: (?P<runtime>(\\d*.\\d*)) seconds")
@@ -58,8 +57,8 @@ class BenchmarkRaxmlng(Benchmark):
os.makedirs(raxmlng_builddir, exist_ok=True)
# building raxml-ng
- run_cmd( ["cmake", ".."], cwd=raxmlng_builddir)
- run_cmd( ["make"], cwd=raxmlng_builddir)
+ run_cmd(["cmake", ".."], cwd=raxmlng_builddir)
+ run_cmd(["make"], cwd=raxmlng_builddir)
# create symlinks
for exe in ["raxml-ng"]:
@@ -83,19 +82,21 @@ class BenchmarkRaxmlng(Benchmark):
result["runtime"] = RUNTIME_RE.search(stdout).group("runtime")
def summary(self):
- self.barplot_single_arg("{runtime}",
- ylabel='"runtime in s"',
- title='"raxml-ng tree inference benchmark"',
- filepostfix="runtime")
+ plt.barplot_single_arg(self,
+ "{runtime}",
+ ylabel='"runtime in s"',
+ title='"raxml-ng tree inference benchmark"',
+ filepostfix="runtime")
- self.export_stats_to_dataref("runtime")
+ plt.export_stats_to_dataref(self, "runtime")
- self.barplot_single_arg("{VmHWM}",
- ylabel='"VmHWM in KB"',
- title='"raxml-ng memusage"',
- filepostfix="memusage")
+ plt.barplot_single_arg(self,
+ "{VmHWM}",
+ ylabel='"VmHWM in KB"',
+ title='"raxml-ng memusage"',
+ filepostfix="memusage")
- self.export_stats_to_dataref("VmHWM")
+ plt.export_stats_to_dataref(self, "VmHWM")
raxmlng = BenchmarkRaxmlng()
diff --git a/src/plots.py b/src/plots.py
new file mode 100644
index 0000000..b6ef4f8
--- /dev/null
+++ b/src/plots.py
@@ -0,0 +1,518 @@
+import os
+
+import matplotlib
+import matplotlib.pyplot as plt
+import numpy as np
+import tikzplotlib
+
+from src.benchmark import Benchmark
+import src.globalvars
+from src.util import print_warn
+
+# This is useful when evaluating strings in the plot functions. str(np.NaN) == "nan"
+nan = np.NaN
+
+
+###### Summary helpers ######
+def _eval_with_stat(bench, evaluation, alloc, perm, stat):
+ try:
+ s = evaluation.format(**bench.results["stats"][alloc][perm][stat])
+ except KeyError as e:
+ import traceback
+ print_warn(traceback.format_exc())
+ print_warn(f"For {alloc} in {perm}")
+ return nan
+ return eval(s)
+
+def plot_single_arg(bench, yval, ylabel="'y-label'", xlabel="'x-label'",
+ autoticks=True, title="'default title'", filepostfix="",
+ sumdir="", arg="", scale=None, file_ext=src.globalvars.summary_file_ext):
+
+ args = bench.results["args"]
+ allocators = bench.results["allocators"]
+
+ arg = arg or list(args.keys())[0]
+
+ if not autoticks:
+ x_vals = list(range(1, len(args[arg]) + 1))
+ else:
+ x_vals = args[arg]
+
+ for allocator in allocators:
+ y_vals = []
+ for perm in bench.iterate_args(args=args):
+ if scale:
+ if scale == allocator:
+ y_vals = [1] * len(x_vals)
+ else:
+ mean = _eval_with_stat(bench, yval, allocator, perm, "mean")
+ norm_mean = _eval_with_stat(bench, yval, scale, perm, "mean")
+ y_vals.append(mean / norm_mean)
+ else:
+ y_vals.append(_eval_with_stat(bench, yval, allocator, perm, "mean"))
+
+ plt.plot(x_vals, y_vals, marker='.', linestyle='-',
+ label=allocator, color=allocators[allocator]["color"])
+
+ plt.legend(loc="best")
+ if not autoticks:
+ plt.xticks(x_vals, args[arg])
+ plt.xlabel(eval(xlabel))
+ plt.ylabel(eval(ylabel))
+ plt.title(eval(title))
+ figname = os.path.join(sumdir, f"{bench.name}.{filepostfix}.{file_ext}")
+ if figname.endswith(".tex"):
+ tikzplotlib.save(figname)
+ else:
+ plt.savefig(figname)
+ plt.clf()
+
+def barplot_single_arg(bench, yval, ylabel="'y-label'", xlabel="'x-label'",
+ title="'default title'", filepostfix="", sumdir="",
+ arg="", scale=None, file_ext=src.globalvars.summary_file_ext, yerr=True):
+
+ args = bench.results["args"]
+ allocators = bench.results["allocators"]
+ nallocators = len(allocators)
+
+ if arg:
+ arg = args[arg]
+ elif args.keys():
+ arg = args[list(args.keys())[0]]
+ else:
+ arg = [""]
+
+ narg = len(arg)
+
+ for i, allocator in enumerate(allocators):
+ x_vals = list(range(i, narg * (nallocators+1), nallocators+1))
+ y_vals = []
+ y_errs = None
+ if yerr:
+ y_errs = []
+
+ for perm in bench.iterate_args(args=args):
+ if scale:
+ if scale == allocator:
+ y_vals = [1] * len(x_vals)
+ else:
+ mean = _eval_with_stat(bench, yval, allocator, perm, "mean")
+ norm_mean = _eval_with_stat(bench, yval, scale, perm, "mean")
+ y_vals.append(mean / norm_mean)
+ else:
+ y_vals.append(_eval_with_stat(bench, yval, allocator, perm, "mean"))
+
+ if yerr:
+ y_errs.append(_eval_with_stat(bench, yval, allocator, perm, "std"))
+
+ plt.bar(x_vals, y_vals, width=1, label=allocator, yerr=y_errs,
+ color=allocators[allocator]["color"])
+
+ plt.legend(loc="best")
+ plt.xticks(list(range(int(np.floor(nallocators/2)), narg*(nallocators+1), nallocators+1)), arg)
+ plt.xlabel(eval(xlabel))
+ plt.ylabel(eval(ylabel))
+ plt.title(eval(title))
+ figname = os.path.join(sumdir, f"{bench.name}.{filepostfix}.{file_ext}")
+ if figname.endswith(".tex"):
+ import tikzplotlib
+ tikzplotlib.save(figname)
+ else:
+ plt.savefig(figname)
+ plt.clf()
+
+def plot_fixed_arg(bench, yval, ylabel="'y-label'", xlabel="loose_arg",
+ autoticks=True, title="'default title'", filepostfix="",
+ sumdir="", fixed=None, file_ext=src.globalvars.summary_file_ext, scale=None):
+
+ args = bench.results["args"]
+ allocators = bench.results["allocators"]
+
+ for arg in fixed or args:
+ loose_arg = [a for a in args if a != arg][0]
+
+ if not autoticks:
+ x_vals = list(range(1, len(args[loose_arg]) + 1))
+ else:
+ x_vals = args[loose_arg]
+
+ for arg_value in args[arg]:
+ for allocator in allocators:
+ y_vals = []
+ for perm in bench.iterate_args_fixed({arg: arg_value}, args=args):
+ if scale:
+ if scale == allocator:
+ y_vals = [1] * len(x_vals)
+ else:
+ mean = _eval_with_stat(bench, yval, allocator, perm, "mean")
+ norm_mean = _eval_with_stat(bench, yval, scale, perm, "mean")
+ y_vals.append(mean / norm_mean)
+ else:
+ y_vals.append(_eval_with_stat(bench, yval, allocator, perm, "mean"))
+
+ plt.plot(x_vals, y_vals, marker='.', linestyle='-',
+ label=allocator, color=allocators[allocator]["color"])
+
+ plt.legend(loc="best")
+ if not autoticks:
+ plt.xticks(x_vals, args[loose_arg])
+ plt.xlabel(eval(xlabel))
+ plt.ylabel(eval(ylabel))
+ plt.title(eval(title))
+ figname = os.path.join(sumdir,
+ f"{bench.name}.{arg}.{arg_value}.{filepostfix}.{file_ext}")
+ if figname.endswith(".tex"):
+ import tikzplotlib
+ tikzplotlib.save(figname)
+ else:
+ plt.savefig(figname)
+ plt.clf()
+
+def export_facts_to_file(bench, comment_symbol, f):
+ """Write collected facts about used system and benchmark to file"""
+ print(comment_symbol, bench.name, file=f)
+ print(file=f)
+ print(comment_symbol, "Common facts:", file=f)
+ for k, v in src.facter.FACTS.items():
+ print(comment_symbol, k + ":", v, file=f)
+ print(file=f)
+ print(comment_symbol, "Benchmark facts:", file=f)
+ for k, v in bench.results["facts"].items():
+ print(comment_symbol, k + ":", v, file=f)
+ print(file=f)
+
+def export_stats_to_csv(bench, datapoint, path=None):
+ """Write descriptive statistics about datapoint to csv file"""
+ allocators = bench.results["allocators"]
+ args = bench.results["args"]
+ stats = bench.results["stats"]
+
+ if path is None:
+ path = datapoint
+
+ path = path + ".csv"
+
+ stats_fields = list(stats[list(allocators)[0]][list(bench.iterate_args(args=args))[0]])
+ fieldnames = ["allocator", *args, *stats_fields]
+ widths = []
+ for fieldname in fieldnames:
+ widths.append(len(fieldname) + 2)
+
+ # collect rows
+ rows = {}
+ for alloc in allocators:
+ rows[alloc] = {}
+ for perm in bench.iterate_args(args=args):
+ d = []
+ d.append(alloc)
+ d += list(perm._asdict().values())
+ d += [stats[alloc][perm][s][datapoint] for s in stats[alloc][perm]]
+ d[-1] = (",".join([str(x) for x in d[-1]]))
+ rows[alloc][perm] = d
+
+ # calc widths
+ for i in range(0, len(fieldnames)):
+ for alloc in allocators:
+ for perm in bench.iterate_args(args=args):
+ field_len = len(str(rows[alloc][perm][i])) + 2
+ if field_len > widths[i]:
+ widths[i] = field_len
+
+ with open(path, "w") as f:
+ headerline = ""
+ for i, h in enumerate(fieldnames):
+ headerline += h.capitalize().ljust(widths[i]).replace("_", "-")
+ print(headerline, file=f)
+
+ for alloc in allocators:
+ for perm in bench.iterate_args(args=args):
+ line = ""
+ for i, x in enumerate(rows[alloc][perm]):
+ line += str(x).ljust(widths[i])
+ print(line.replace("_", "-"), file=f)
+
+def export_stats_to_dataref(bench, datapoint, path=None):
+ """Write descriptive statistics about datapoint to dataref file"""
+ stats = bench.results["stats"]
+
+ if path is None:
+ path = datapoint
+
+ path = path + ".dataref"
+
+ # Example: \drefset{/mysql/glibc/40/Lower-whisker}{71552.0}
+ line = "\\drefset{{/{}/{}/{}/{}}}{{{}}}"
+
+ with open(path, "w") as f:
+ # Write facts to file
+ export_facts_to_file(bench, "%", f)
+
+ for alloc in bench.results["allocators"]:
+ for perm in bench.iterate_args(args=bench.results["args"]):
+ for statistic, values in stats[alloc][perm].items():
+ cur_line = line.format(bench.name, alloc,
+ "/".join([str(p) for p in list(perm)]),
+ statistic, values[datapoint])
+ # Replace empty outliers
+ cur_line.replace("[]", "")
+ # Replace underscores
+ cur_line.replace("_", "-")
+ print(cur_line, file=f)
+
+def write_best_doublearg_tex_table(bench, evaluation, sort=">",
+ filepostfix="", sumdir="", std=False):
+ args = bench.results["args"]
+ keys = list(args.keys())
+ allocators = bench.results["allocators"]
+
+ header_arg = keys[0] if len(args[keys[0]]) < len(args[keys[1]]) else keys[1]
+ row_arg = [arg for arg in args if arg != header_arg][0]
+
+ headers = args[header_arg]
+ rows = args[row_arg]
+
+ cell_text = []
+ for av in rows:
+ row = []
+ for perm in bench.iterate_args_fixed({row_arg: av}, args=args):
+ best = []
+ best_val = None
+ for allocator in allocators:
+ d = []
+ for m in bench.results[allocator][perm]:
+ d.append(eval(evaluation.format(**m)))
+ mean = np.mean(d)
+ if not best_val:
+ best = [allocator]
+ best_val = mean
+ elif ((sort == ">" and mean > best_val)
+ or (sort == "<" and mean < best_val)):
+ best = [allocator]
+ best_val = mean
+ elif mean == best_val:
+ best.append(allocator)
+
+ row.append("{}: {:.3f}".format(best[0], best_val))
+ cell_text.append(row)
+
+ fname = os.path.join(sumdir, ".".join([bench.name, filepostfix, "tex"]))
+ with open(fname, "w") as f:
+ print("\\documentclass{standalone}", file=f)
+ print("\\begin{document}", file=f)
+ print("\\begin{tabular}{|", end="", file=f)
+ print(" l |" * len(headers), "}", file=f)
+
+ print(header_arg+"/"+row_arg, end=" & ", file=f)
+ for header in headers[:-1]:
+ print(header, end="& ", file=f)
+ print(headers[-1], "\\\\", file=f)
+
+ for i, row in enumerate(cell_text):
+ print(rows[i], end=" & ", file=f)
+ for e in row[:-1]:
+ print(e, end=" & ", file=f)
+ print(row[-1], "\\\\", file=f)
+ print("\\end{tabular}", file=f)
+ print("\\end{document}", file=f)
+
+def write_tex_table(bench, entries, sort=">",
+ filepostfix="", sumdir="", std=False):
+ """generate a latex standalone table from an list of entries dictionaries
+
+ Entries must have at least the two keys: "label" and "expression".
+ The optional "sort" key specifies the direction of the order:
+ ">" : bigger is better.
+ "<" : smaller is better.
+
+ Table layout:
+
+ | alloc1 | alloc2 | ....
+ ---------------------------------------
+ | name1 name2 | ...
+ ---------------------------------------
+ perm1 | eavl1 eval2 | ...
+ perm2 | eval1 eval2 | ...
+ """
+ args = bench.results["args"]
+ allocators = bench.results["allocators"]
+ nallocators = len(allocators)
+ nentries = len(entries)
+ perm_fields = bench.Perm._fields
+ nperm_fields = len(perm_fields)
+
+ alloc_header_line = f"\\multicolumn{{{nperm_fields}}}{{c|}}{{}} &"
+ for alloc in allocators:
+ alloc_header_line += f"\\multicolumn{{{nentries}}}{{c|}}{{{alloc}}} &"
+ alloc_header_line = alloc_header_line[:-1] + "\\\\"
+
+ perm_fields_header = ""
+ for field in bench.Perm._fields:
+ perm_fields_header += f'{field} &'
+ entry_header_line = ""
+ for entry in entries:
+ entry_header_line += f'{entry["label"]} &'
+ entry_header_line = perm_fields_header + entry_header_line * nallocators
+ entry_header_line = entry_header_line[:-1] + "\\\\"
+
+ fname = os.path.join(sumdir, ".".join([bench.name, filepostfix, "tex"]))
+ with open(fname, "w") as f:
+ print("\\documentclass{standalone}", file=f)
+ print("\\usepackage{booktabs}", file=f)
+ print("\\usepackage{xcolor}", file=f)
+ print("\\begin{document}", file=f)
+ print("\\begin{tabular}{|", f"{'c|'*nperm_fields}", f"{'c'*nentries}|"*nallocators, "}", file=f)
+ print("\\toprule", file=f)
+
+ print(alloc_header_line, file=f)
+ print("\\hline", file=f)
+ print(entry_header_line, file=f)
+ print("\\hline", file=f)
+
+ for perm in bench.iterate_args(args=args):
+ values = [[] for _ in entries]
+ maxs = [None for _ in entries]
+ mins = [None for _ in entries]
+ for allocator in allocators:
+ for i, entry in enumerate(entries):
+ expr = entry["expression"]
+ values[i].append(eval(expr.format(**bench.results["stats"][allocator][perm]["mean"])))
+
+ # get max and min for each entry
+ for i, entry in enumerate(entries):
+ if not "sort" in entry:
+ continue
+ # bigger is better
+ elif entry["sort"] == ">":
+ maxs[i] = max(values[i])
+ mins[i] = min(values[i])
+ # smaller is better
+ elif entry["sort"] == "<":
+ mins[i] = max(values[i])
+ maxs[i] = min(values[i])
+
+ # build row
+ row = ""
+ perm_dict = perm._asdict()
+ for field in perm_fields:
+ row += str(perm_dict[field]) + "&"
+
+ for i, _ in enumerate(allocators):
+ for y, entry_vals in enumerate(values):
+ val = entry_vals[i]
+
+ # format
+ val_str = str(val)
+ if type(val) == float:
+ val_str = f"{val:.2f}"
+
+ # colorize
+ if val == maxs[y]:
+ val_str = f"\\textcolor{{green}}{{{val_str}}}"
+ elif val == mins[y]:
+ val_str = f"\\textcolor{{red}}{{{val_str}}}"
+ row += f"{val_str} &"
+ #escape _ for latex
+ row = row.replace("_", "\\_")
+ print(row[:-1], "\\\\", file=f)
+
+ print("\\end{tabular}", file=f)
+ print("\\end{document}", file=f)
+
+def pgfplot_legend(bench, sumdir=""):
+
+ allocators = bench.results["allocators"]
+ s =\
+"""
+\\documentclass{standalone}
+\\usepackage{pgfplots}
+
+\\usepackage{pgfkeys}
+
+\\newenvironment{customlegend}[1][]{%
+\t\\begingroup
+\t\\csname pgfplots@init@cleared@structures\\endcsname
+\t\\pgfplotsset{#1}%
+}{%
+\t\\csname pgfplots@createlegend\\endcsname
+\t\\endgroup
+}%
+\\def\\addlegendimage{\\csname pgfplots@addlegendimage\\endcsname}
+
+\\usepackage{xcolor}
+"""
+
+ for alloc_name, alloc_dict in allocators.items():
+ # define color
+ rgb = matplotlib.colors.to_rgb(alloc_dict["color"])
+ s += f"\\providecolor{{{alloc_name}-color}}{{rgb}}{{{rgb[0]},{rgb[1]},{rgb[2]}}}\n"
+
+ s +=\
+"""
+\\begin{document}
+\\begin{tikzpicture}
+\\begin{customlegend}[
+\tlegend entries={"""
+
+ alloc_list = ""
+ addlegendimage_list = ""
+ for alloc_name in allocators:
+ alloc_list += f"{alloc_name}, "
+ addlegendimage_list += "\t\\addlegendimage{}\n"
+
+ s += alloc_list[:-2] + "},\n]"
+ s += addlegendimage_list
+ s +=\
+"""
+\\end{customlegend}
+\\end{tikzpicture}
+\\end{document}"""
+
+ with open(os.path.join(sumdir, "legend.tex"), "w") as legend_file:
+ print(s, file=legend_file)
+
+def pgfplot_linear(bench, perms, xval, yval, ylabel="'y-label'", xlabel="'x-label'",
+ title="'default title'", postfix="", sumdir="", scale=None):
+
+ allocators = bench.results["allocators"]
+ perms = list(perms)
+ title = eval(title)
+ s =\
+"""\\documentclass{standalone}
+\\usepackage{pgfplots}
+\\usepackage{xcolor}
+"""
+
+ for alloc_name, alloc_dict in allocators.items():
+ s += f"\\begin{{filecontents*}}{{{alloc_name}.dat}}\n"
+ for i, perm in enumerate(perms):
+ x = _eval_with_stat(bench, xval, alloc_name, perm, "mean")
+ y = _eval_with_stat(bench, yval, alloc_name, perm, "mean")
+ s += f"{x} {y}\n"
+ s += "\\end{filecontents*}\n"
+
+ # define color
+ rgb = matplotlib.colors.to_rgb(alloc_dict["color"])
+ s += f"\\providecolor{{{alloc_name}-color}}{{rgb}}{{{rgb[0]},{rgb[1]},{rgb[2]}}}\n"
+
+ s +=\
+f"""
+\\begin{{document}}
+\\begin{{tikzpicture}}
+\\begin{{axis}}[
+\ttitle={{{title}}},
+\txlabel={{{eval(xlabel)}}},
+\tylabel={{{eval(ylabel)}}},
+]
+"""
+
+ for alloc_name in allocators:
+ s += f"\\addplot [{alloc_name}-color] table {{{alloc_name}.dat}};\n"
+ # s += f"\t\\addplot table {{{alloc_name}.dat}};\n"
+
+ s +=\
+"""\\end{axis}
+\\end{tikzpicture}
+\\end{document}"""
+
+ with open(os.path.join(sumdir, f"{bench.name}.{postfix}.tex"), "w") as plot_file:
+ print(s, file=plot_file)
generated by cgit v1.2.3 (git 2.25.1) at 2026-04-23 18:17:45 +0000