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# Copyright (c) 2017, 2026, Oracle and/or its affiliates.
# Copyright (c) 2013, Regents of the University of California
#
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without modification, are
# permitted provided that the following conditions are met:
#
# 1. Redistributions of source code must retain the above copyright notice, this list of
# conditions and the following disclaimer.
# 2. Redistributions in binary form must reproduce the above copyright notice, this list of
# conditions and the following disclaimer in the documentation and/or other materials provided
# with the distribution.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS
# OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
# MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
# COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE
# GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED
# AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
# NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED
# OF THE POSSIBILITY OF SUCH DAMAGE.
import os
import mx
_graalpython_suite = mx.suite('graalpython')
py = ".py"
_BASE_PATH = os.path.join(_graalpython_suite.dir, 'graalpython', 'com.oracle.graal.python.benchmarks', 'python')
HARNESS_PATH = os.path.join(_BASE_PATH, 'harness.py')
PATH_BENCH = os.path.join(_BASE_PATH, 'com.oracle.graal.python.benchmarks')
PATH_MICRO = os.path.join(_BASE_PATH, 'micro')
PATH_MESO = os.path.join(_BASE_PATH, 'meso')
PATH_MACRO = os.path.join(_BASE_PATH, 'macro')
PATH_WARMUP = os.path.join(_BASE_PATH, 'warmup')
PATH_INTEROP = os.path.join(_BASE_PATH, 'host_interop')
PATH_JAVA_EMBEDDING = os.path.join(_BASE_PATH, 'java-embedding')
PATH_HEAP = os.path.join(_BASE_PATH, 'heap')
# ----------------------------------------------------------------------------------------------------------------------
#
# the python micro benchmarks
#
# ----------------------------------------------------------------------------------------------------------------------
# the argument list contains both the harness and benchmark args
ITER_100 = ['-i', '100']
ITER_50 = ['-i', '50']
ITER_35 = ['-i', '35']
ITER_25 = ['-i', '25']
ITER_20 = ['-i', '20']
ITER_15 = ['-i', '15']
ITER_10 = ['-i', '10']
ITER_6 = ['-i', '6']
ITER_5 = ['-i', '5']
ITER_3 = ['-i', '3']
ITER_1 = ['-i', '1']
WARMUP_2 = ['-w', '2']
# For benchmarking with Truffle compilation
MICRO_BENCHMARKS = {
'arith-binop': ITER_10 + ['5'],
'arith-modulo-sized': ITER_10 + ['500'],
'attribute-access-megamorphic': ITER_10 + ['200'],
'attribute-access-polymorphic': ITER_10 + ['1000'],
'attribute-access': ITER_15 + ['5000'],
'attribute-access-super': ITER_20 + ['5_000'],
'super-zero-attribute': ITER_10 + ['950_000_000'],
'super-explicit-attribute': ITER_10 + ['950_000_000'],
'super-zero-method': ITER_10 + ['950_000_000'],
'super-explicit-method': ITER_10 + ['950_000_000'],
'attribute-bool': ITER_10 + ['3000'],
'boolean-logic-sized': ITER_15 + ['5_000'],
'builtin-len-tuple-sized': ITER_100 + ['1_000_000_000'],
'builtin-len': ITER_10 + [],
'call-method-polymorphic': ITER_10 + ['1000'],
'for-range': ITER_15 + ['50000'],
'function-call-sized': ITER_10 + ['2_000_000_000'],
'generator-expression-sized': ITER_10 + ['30_000'],
'generator-notaligned-sized': ITER_10 + ['30_000'],
'generator-sized': ITER_10 + ['30_000'],
'genexp-builtin-call-sized': ITER_10 + ['50_000'],
'list-comp': ITER_10 + ['5000'],
'list-comp2': ITER_10 + ['100_000_000'],
'list-indexing': ITER_10 + ['1000000'],
'list-indexing-from-constructor': ITER_10 + ['10000000'],
'list-indexing-from-literal': ITER_10 + ['10000000'],
'list-iterating-explicit': ITER_10 + ['1000000'],
'list-iterating': ITER_10 + ['1000000'],
'list-iterating-obj-sized': ITER_10 + ['100_000_000'],
'list-constructions-sized': ITER_10 + ['10_000'],
'list-sort-objects': ITER_10 + ['10_000'],
'list-sort-strings': ITER_10 + ['500_000'],
'list-sort-keyed': ITER_10 + ['50_000'],
'dict-getitem-sized': ITER_10 + ['50_000_000'],
'math-sqrt': ITER_10 + ['500000000'],
'object-allocate': ITER_10 + ['5000'],
'object-dir': ITER_10 + ['10_000'],
'object-dir-custom-bases': ITER_10 + ['10_000'],
'object-layout-change': ITER_10 + ['1000000'],
'special-add-int-sized': ITER_10 + ['20_000'],
'special-add-sized': ITER_10 + ['20_000'],
'special-len': ITER_10 + ['5'],
'member-access': ITER_15 + ['5000'],
'magic-bool-sized': ITER_10 + ['300_000_000'],
'magic-iter': ITER_10 + ['50000000'],
'call-classmethod-sized': ITER_10 + ['500_000_000'],
'mmap-anonymous-sized': ITER_10 + ['20_000'],
'mmap-file': ITER_10 + ['1000'],
'posix-operations': ITER_10 + WARMUP_2 + ['2000'],
'posix-read': ITER_10 + WARMUP_2 + ['16384'],
'posix-write': ITER_10 + WARMUP_2 + ['16384'],
'posix-stat': ITER_10 + WARMUP_2 + ['40000'],
'posix-open-close': ITER_10 + WARMUP_2 + ['20000'],
'posix-lseek': ITER_10 + WARMUP_2 + ['40000'],
'posix-scandir': ITER_10 + WARMUP_2 + ['1200'],
'generate-functions-sized': ITER_15 + ['500_000_000'],
'try-except-simple': ITER_10 + ['500_000_000'],
'try-except-store-simple': ITER_10 + ['500_000_000'],
'try-except-store-two-types': ITER_10 + ['100_000_000'],
'try-except-two-types': ITER_10 + ['100_000_000'],
'with-exception': ITER_10 + ['100_000_000'],
'tuple-indexing-from-constructor': ITER_10 + ['10000000'],
'tuple-indexing-from-literal': ITER_10 + ['10000000'],
'repeated-import': ITER_10 + ['10000000'],
'codeobject-interpretation': ITER_10 + ['2000'],
'regexp': ITER_10,
'regexp-split': ITER_10,
'regexp-literal-no-match': ITER_10,
'regexp-literal-match': ITER_10,
'regexp-universal-match': ITER_10,
'regexp-char-class-match': ITER_10,
'regexp-char-class-no-match': ITER_10,
'virtualize-in-try-catch-oom': ITER_10,
'phase_shift_warmup_baseline': ITER_5 + ['--self-measurement'] + ['500'],
'phase_shift_warmup': ITER_3 + ['--self-measurement'] + ['1600', '500'],
'jsonrpc-pipe': ITER_15 + ['500', 'text', 'text', 'mask', '64'],
'startup': ITER_5 + ['50'],
'startup-imports': ITER_5 + ['20'],
}
# For benchmarking the interpreter with --engine.Compilation=false
MICRO_BENCHMARKS_SMALL = {
'call-binary': ITER_10 + WARMUP_2,
'empty-loop': ITER_10 + WARMUP_2,
'posix-operations': ITER_6 + WARMUP_2 + ['2000'],
'posix-read': ITER_6 + WARMUP_2 + ['16384'],
'posix-write': ITER_6 + WARMUP_2 + ['16384'],
'posix-stat': ITER_6 + WARMUP_2 + ['40000'],
'posix-open-close': ITER_6 + WARMUP_2 + ['20000'],
'posix-lseek': ITER_6 + WARMUP_2 + ['40000'],
'posix-scandir': ITER_6 + WARMUP_2 + ['1200'],
'nano-arith': ITER_6 + WARMUP_2,
'nano-loop': ITER_6 + WARMUP_2,
'nano-if': ITER_6 + WARMUP_2,
'nano-attribute': ITER_6 + WARMUP_2,
'nano-attribute-slot': ITER_6 + WARMUP_2,
'nano-property': ITER_6 + WARMUP_2,
'jsonrpc-pipe': ITER_6 + WARMUP_2 + ['100', 'text', 'text', 'mask', '64'],
'arith-modulo-sized': ITER_6 + WARMUP_2 + ['1'],
'if-generic': ITER_10 + WARMUP_2 + ['500000'],
'if-generic-non-builtin': ITER_10 + WARMUP_2 + ['500000'],
'if-polymorph': ITER_10 + WARMUP_2 + ['1000000'],
'attribute-access-megamorphic': ITER_6 + WARMUP_2 + ['13'],
'attribute-access-polymorphic': ITER_6 + WARMUP_2 + ['20'],
'attribute-access': ITER_6 + WARMUP_2 + ['100'],
'attribute-access-super': ITER_6 + WARMUP_2 + ['40'],
'super-zero-attribute': ITER_6 + WARMUP_2 + ['1_000_000'],
'super-explicit-attribute': ITER_6 + WARMUP_2 + ['1_000_000'],
'super-zero-method': ITER_6 + WARMUP_2 + ['1_000_000'],
'super-explicit-method': ITER_6 + WARMUP_2 + ['1_000_000'],
'nano-attribute-type': ITER_6 + WARMUP_2 + ['30_000_000'],
'nano-attribute-type-descr': ITER_6 + WARMUP_2 + ['30_000_000'],
'attribute-bool': ITER_6 + WARMUP_2 + ['2'],
'boolean-logic-sized': ITER_6 + WARMUP_2 + ['10'],
'builtin-len-tuple-sized': ITER_6 + WARMUP_2 + ['10_000_000'],
'builtin-len': ITER_10 + WARMUP_2 + ['2_500_000'],
'bytecode-benchmark': ITER_6 + WARMUP_2 + ['500'],
'call-method-polymorphic': ITER_6 + WARMUP_2 + ['10'],
'for-range': ITER_10 + WARMUP_2 + WARMUP_2 + ['50'],
'function-call-sized': ITER_10 + WARMUP_2 + ['2_000_000'],
'generator-expression-sized': ITER_10 + WARMUP_2 + ['3000', '500'],
'generator-notaligned-sized': ITER_10 + WARMUP_2 + ['3000', '500'],
'generator-sized': ITER_10 + WARMUP_2 + ['3000', '500'],
'genexp-builtin-call-sized': ITER_10 + WARMUP_2 + ['3000', '500'],
'list-comp': ITER_15 + WARMUP_2 + ['25'],
'list-comp2': ITER_15 + WARMUP_2 + ['1000000'],
'list-indexing': ITER_6 + WARMUP_2 + ['10_000'],
'list-indexing-from-constructor': ITER_6 + WARMUP_2 + ['250_000'],
'list-indexing-from-literal': ITER_6 + WARMUP_2 + ['250_000'],
'list-iterating-explicit': ITER_6 + WARMUP_2 + ['10_000'],
'list-iterating': ITER_6 + WARMUP_2 + ['25_000'],
'list-iterating-obj-sized': ITER_6 + WARMUP_2 + ['1_000_000'],
'list-constructions-sized': ITER_15 + WARMUP_2 + ['500'],
'dict-getitem-sized': ITER_10 + WARMUP_2 + ['1_000_000'],
'math-sqrt': ITER_6 + WARMUP_2 + ['20_000_000'],
'object-allocate': ITER_6 + WARMUP_2 + ['50'],
'object-dir': ITER_6 + WARMUP_2 + ['100'],
'object-dir-custom-bases': ITER_6 + WARMUP_2 + ['100'],
'object-layout-change': ITER_6 + WARMUP_2 + ['10_000'],
'special-add-int-sized': ITER_6 + WARMUP_2 + ['1_000'],
'special-add-sized': ITER_6 + WARMUP_2 + ['1_000'],
'special-len': ITER_10 + WARMUP_2 + ['1', '1_000'],
'member-access': ITER_10 + WARMUP_2 + ['10'],
'magic-bool-sized': ITER_10 + WARMUP_2 + ['1_000_000'],
'magic-iter': ITER_6 + WARMUP_2 + ['250000'],
'call-classmethod-sized': ITER_10 + WARMUP_2 + ['1_000_000'],
'mmap-anonymous-sized': ITER_6 + WARMUP_2 + ['1_000'],
'mmap-file': ITER_15 + WARMUP_2 + ['100'],
'generate-functions-sized': ITER_10 + WARMUP_2 + ['1_000_000'],
'try-except-simple': ITER_6 + WARMUP_2 + ['2_500_000'],
'try-except-store-simple': ITER_6 + WARMUP_2 + ['2_000_000'],
'try-except-store-two-types': ITER_10 + WARMUP_2 + ['1_000_000'],
'try-except-two-types': ITER_10 + WARMUP_2 + ['1_000_000'],
'with-exception': ITER_6 + WARMUP_2 + ['5_000_000'],
'tuple-indexing-from-constructor': ITER_6 + WARMUP_2 + ['250_000'],
'tuple-indexing-from-literal': ITER_6 + WARMUP_2 + ['400_000'],
'unmarshal-pyc': ITER_5 + WARMUP_2 + ['50'],
'c-member-access': ITER_5 + ['30'],
'c-list-iterating-obj': ITER_5 + ['500000'],
'c-dict-iterating': ITER_5 + ['500000'],
'c-magic-bool': ITER_5 + ['1000000'],
'c-magic-iter': ITER_5 + ['500000'],
'c-arith-binop': ITER_5 + ['3'],
'c-arith-binop2': ITER_5 + ['5'],
'c-call-classmethod': ITER_5 + ['200000'],
'c-issubtype-polymorphic': ITER_5 + ['100000'],
'c-issubtype-monorphic': ITER_5 + ['200000'],
'c-call-method': ITER_5 + ['50000'],
'c-call-method-o': ITER_5 + ['50000'],
'c-call-method-noargs': ITER_5 + ['50000'],
'c-call-method-varargs': ITER_5 + ['50000'],
'c-call-method-int-float': ITER_5 + ['500000'],
'regexp': ITER_5 + WARMUP_2,
'c-upcall': ITER_5 + [str(2**28)],
'c-to-c': ITER_5 + [str(2**31 - 1)],
'startup': ITER_5 + ['50'],
'startup-imports': ITER_5 + ['10'],
}
def _pickling_benchmarks(module='pickle'):
return {
'{}-strings'.format(module): ITER_20 + ['4'],
'{}-lists'.format(module): ITER_20 + ['4'],
'{}-dicts'.format(module): ITER_20 + ['4'],
'{}-objects'.format(module): ITER_20 + ['20'],
'{}-funcs'.format(module): ITER_20 + ['30'],
}
# MICRO_BENCHMARKS.update(_pickling_benchmarks('pickle'))
# MICRO_BENCHMARKS.update(_pickling_benchmarks('cPickle'))
MICRO_NATIVE_BENCHMARKS = {
'c-member-access': ITER_5 + ['10000'],
'c-list-iterating-obj': ITER_5 + ['50000000'],
'c-many-shortlived-objs': ITER_3 + ['100000000'],
'c-dict-iterating': ITER_5 + ['50000000'],
'c-magic-bool': ITER_5 + ['100000000'],
'c-magic-iter': ITER_5 + ['50000000'],
'c-arith-binop': ITER_5 + ['1000'],
'c-arith-binop2': ITER_5 + ['100'],
'c-call-classmethod': ITER_5 + ['50000000'],
'c-issubtype-polymorphic': ITER_5 + ['50000000'],
'c-issubtype-monorphic': ITER_5 + ['50000000'],
'c-call-method': ITER_5 + ['5000000'],
'c-call-method-o': ITER_5 + ['5000000'],
'c-call-method-noargs': ITER_5 + ['5000000'],
'c-call-method-varargs': ITER_5 + ['5000000'],
'c-call-method-fastcall': ITER_5 + ['5000000'],
'c-call-method-int-float': ITER_5 + ['5000000'],
'c-call-method-obj-args': ITER_5 + ['5000000'],
'c-instantiate-large': ITER_5 + ['1000'],
'c-upcall': ITER_5 + [str(2**28)],
'c-upcall-builtin-function': ITER_5 + [str(2**26)],
'c-upcall-slot': ITER_5 + [str(2**20)],
'c-to-c': ITER_5 + [str(2**31 - 1)],
}
MESO_BENCHMARKS = {
# -------------------------------------------------------
# generator benchmarks
# -------------------------------------------------------
'euler31': ITER_10 + ['200'],
'euler11': ITER_10 + ['10000'],
'ai-nqueen': ITER_10 + ['10'],
'pads-eratosthenes': ITER_10 + ['100000'],
'pads-integerpartitions': ITER_10 + ['700'],
'pads-bipartite-sized': ITER_10 + ['100_000'],
'pads-lyndon': ITER_15 + ['10000000'],
# -------------------------------------------------------
# object benchmarks
# -------------------------------------------------------
'richards3': ITER_10 + ['200'],
'bm-float': ITER_10 + ['1000'],
# -------------------------------------------------------
# normal benchmarks
# -------------------------------------------------------
'binarytrees3': ITER_25 + ['18'],
'fannkuchredux3': ITER_10 + ['11'],
'fasta3': ITER_10 + ['25000000'],
'mandelbrot3': ITER_10 + ['4000'],
'meteor3': ITER_15 + ['2098'],
'nbody3': ITER_10 + ['5000000'],
'spectralnorm3': ITER_10 + ['3000'],
'pidigits': ITER_10 + [],
'sieve-sized': ITER_15 + ['500_000'],
'image-magix-sized2': ITER_10 + ['30000'],
'parrot-b2': ITER_10 + ['200'],
'threadring': ITER_25 + ['100_000_000'],
'regexdna-sized2': ITER_50 + ['4'],
'knucleotide': ITER_25 + [],
'chaos-sized2': ITER_10 + ['500'],
'chaos-traced': ITER_5 + ['500'],
'go-sized2': ITER_15 + ['50'],
'raytrace-simple': ITER_20 + [],
'lud-sized2': ITER_10 + ['1536'],
'mm-sized2': ITER_15 + ['350'],
# Rodinia
'backprop_rodinia-sized2': ITER_15 + ['8388608'],
'lavaMD_rodinia-sized2': ITER_15 + ['48'],
'pathfinder_rodinia-sized2': ITER_25 + ['50'],
'particlefilter_rodinia': ITER_10 + ['2048'],
'srad_rodinia-sized2': ITER_15 + ['1000'],
}
MESO_BENCHMARKS_SMALL = {
'pads-eratosthenes': ITER_20 + WARMUP_2 + ['2000'],
'richards3': ITER_10 + WARMUP_2 + ['2'],
'chaos': ITER_15 + WARMUP_2 + ['2'],
'image-magix': ITER_15 + WARMUP_2 + ['100'],
'raytrace-simple': ITER_10 + WARMUP_2 + ['110', '110'],
}
MACRO_BENCHMARKS = {
'gcbench': ITER_10 + ['10'],
'pygal-demo': ITER_10 + ['1000'],
'c-cythonize-numpy': ITER_1 + [],
'c-pydantic-schema-build': ITER_10 + ['100'],
'c-pydantic-serialize-json': ITER_10 + ['1000'],
'c-pydantic-validate': ITER_10 + ['200000'],
'c-pydantic-validate-callbacks': ITER_10 + ['1000'],
'c-pydantic-validate-json': ITER_10 + ['2000'],
'c-pydantic-validation-errors': ITER_10 + ['1000'],
'c-pymupdf-parse': ITER_10 + ['1'],
'c-oracledb-load': ITER_5 + ['2000000'],
'c-ujson-loads': ITER_10 + ['150'],
}
WARMUP_BENCHMARKS = {
'gcbench': ITER_100 + ["--startup=1,10,100"] + ['10'],
'binarytrees3': ITER_100 + ["--startup=1,10,100"] + ['18'],
'pads-integerpartitions': ITER_100 + ["--startup=1,10,100"] + ['700'],
}
INTEROP_BENCHMARKS = {
'euler_java': ITER_10 + ['200'],
'image-magix': ITER_10 + ['10000'],
'image-magix-java': ITER_10 + ['10000'],
'java-register': ITER_10 + ['2_000'],
}
JAVA_EMBEDDING_MESO_BENCHMARKS = {
'chaos': ITER_6 + WARMUP_2 + [],
'richards3': ITER_6 + WARMUP_2 + [],
'image-magix': ITER_6 + WARMUP_2 + [],
'raytrace-simple': ITER_6 + WARMUP_2 + [],
}
JAVA_EMBEDDING_MESO_BENCHMARKS_SMALL = {
'chaos': ITER_6 + WARMUP_2 + ['--', '1'],
'richards3': ITER_6 + WARMUP_2 + ['--', '2'],
'image-magix': ITER_6 + WARMUP_2 + ['--', '100'],
'raytrace-simple': ITER_6 + WARMUP_2 + ['--', '110', '110'],
}
# NOTE: there are also JMH benchmarks, which are based on JMH support in MX
# see PythonJMHDistMxBenchmarkSuite
# -------------------------------------------------------
# Parameters for parsing benchmarks
# Parameters for parsing benchmarks
# 1. full qualified name of class that define the benchmark
# 2. -i number : is number of benchmark iterations (defualt 5)
# 3. -w number : is number of warmup iterations, in these cases should not be necessary (default 0)
# 4. -n number : is number of parsing cycles of on file in one iteration (default 1)
# 5. -r : if it's present, then folders on the defined paths are parsed recursively
# 6. : files or directories, that will be processed
# 7. -e : after this mark all the listed files and directories are excluded from the benchmark
# 8. : files or directories that will be excluded from the benchmark
# -------------------------------------------------------
_PARSER_JAVA_PACKAGE = 'com.oracle.graal.python.benchmarks.parser.'
PATH_RUNTIME_FILES_PARSER_TESTS = os.path.join(_graalpython_suite.dir, 'graalpython', 'com.oracle.graal.python.test', 'testData', 'testFiles', 'RuntimeFileTests')
PATH_PYTHON_LIB = os.path.join(_graalpython_suite.dir, 'graalpython', 'lib-python', '3')
# ----------------------------------------------------------------------------------------------------------------------
#
# the benchmarks
#
# ----------------------------------------------------------------------------------------------------------------------
BENCHMARKS = {
"micro": [PATH_MICRO, MICRO_BENCHMARKS],
"micro-native": [PATH_MICRO, MICRO_NATIVE_BENCHMARKS],
"meso": [PATH_MESO, MESO_BENCHMARKS],
"macro": [PATH_MACRO, MACRO_BENCHMARKS],
"interop": [PATH_INTEROP, INTEROP_BENCHMARKS],
"micro-small": [PATH_MICRO, MICRO_BENCHMARKS_SMALL],
"meso-small": [PATH_MESO, MESO_BENCHMARKS_SMALL],
}
JAVA_DRIVER_BENCHMARKS = {
"java-embedding-meso": [PATH_MESO, JAVA_EMBEDDING_MESO_BENCHMARKS],
"java-embedding-meso-small": [PATH_MESO, JAVA_EMBEDDING_MESO_BENCHMARKS_SMALL],
}
WARMUP_BENCHMARKS = {
"python-warmup": [PATH_WARMUP, WARMUP_BENCHMARKS],
}
HEAP_BENCHMARKS = {
"heap": [PATH_HEAP, {
"post-startup": [],
"import-a-lot": [],
"allocate-objects": [],
"allocate-dicts": [],
}],
"micro-small-heap": [PATH_MICRO, MICRO_BENCHMARKS_SMALL],
}