diff options
Diffstat (limited to 'resources/tools')
| -rw-r--r-- | resources/tools/presentation/doc/pal_lld.rst | 116 | ||||
| -rw-r--r-- | resources/tools/presentation/generator_tables.py | 175 | ||||
| -rw-r--r-- | resources/tools/presentation/requirements.txt | 1 | ||||
| -rw-r--r-- | resources/tools/presentation/specification.yaml | 81 |
4 files changed, 354 insertions, 19 deletions
diff --git a/resources/tools/presentation/doc/pal_lld.rst b/resources/tools/presentation/doc/pal_lld.rst index 027d6b326a..64bde3e5fe 100644 --- a/resources/tools/presentation/doc/pal_lld.rst +++ b/resources/tools/presentation/doc/pal_lld.rst @@ -1109,8 +1109,9 @@ For example, the element which specification includes: filter: - "'64B' and 'BASE' and 'NDRDISC' and '1T1C' and ('L2BDMACSTAT' or 'L2BDMACLRN' or 'L2XCFWD') and not 'VHOST'" -will be constructed using data from the job "csit-vpp-perf-1707-all", for all listed -builds and the tests with the list of tags matching the filter conditions. +will be constructed using data from the job "csit-vpp-perf-1707-all", for all +listed builds and the tests with the list of tags matching the filter +conditions. The output data structure for filtered test data is: @@ -1189,6 +1190,83 @@ Subset of existing performance tests is covered by TSA graphs. "plot-throughput-speedup-analysis" +Comparison of results from two sets of the same test executions +''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''' + +This algorithm enables comparison of results coming from two sets of the +same test executions. It is used to quantify performance changes across +all tests after test environment changes e.g. Operating System +upgrades/patches, Hardware changes. + +It is assumed that each set of test executions includes multiple runs +of the same tests, 10 or more, to verify test results repeatibility and +to yield statistically meaningful results data. + +Comparison results are presented in a table with a specified number of +the best and the worst relative changes between the two sets. Following table +columns are defined: + + - name of the test; + - throughput mean values of the reference set; + - throughput standard deviation of the reference set; + - throughput mean values of the set to compare; + - throughput standard deviation of the set to compare; + - relative change of the mean values. + +**The model** + +The model specifies: + + - type: "table" - means this section defines a table. + - title: Title of the table. + - algorithm: Algorithm which is used to generate the table. The other + parameters in this section must provide all information needed by the used + algorithm. + - output-file-ext: Extension of the output file. + - output-file: File which the table will be written to. + - reference - the builds which are used as the reference for comparison. + - compare - the builds which are compared to the reference. + - data: Specify the sources, jobs and builds, providing data for generating + the table. + - filter: Filter based on tags applied on the input data, if "template" is + used, filtering is based on the template. + - parameters: Only these parameters will be put to the output data + structure. + - nr-of-tests-shown: Number of the best and the worst tests presented in the + table. Use 0 (zero) to present all tests. + +*Example:* + +:: + + - + type: "table" + title: "Performance comparison" + algorithm: "table_performance_comparison" + output-file-ext: ".csv" + output-file: "{DIR[DTR,PERF,VPP,IMPRV]}/vpp_performance_comparison" + reference: + title: "csit-vpp-perf-1801-all - 1" + data: + csit-vpp-perf-1801-all: + - 1 + - 2 + compare: + title: "csit-vpp-perf-1801-all - 2" + data: + csit-vpp-perf-1801-all: + - 1 + - 2 + data: + "vpp-perf-comparison" + filter: "all" + parameters: + - "name" + - "parent" + - "throughput" + nr-of-tests-shown: 20 + + Advanced data analytics ``````````````````````` @@ -1216,7 +1294,8 @@ Tables - tables are generated by algorithms implemented in PAL, the model includes the algorithm and all necessary information. - output format: csv - - generated tables are stored in specified directories and linked to .rst files. + - generated tables are stored in specified directories and linked to .rst + files. Plots @@ -1232,8 +1311,8 @@ Report generation ----------------- Report is generated using Sphinx and Read_the_Docs template. PAL generates html -and pdf formats. It is possible to define the content of the report by specifying -the version (TODO: define the names and content of versions). +and pdf formats. It is possible to define the content of the report by +specifying the version (TODO: define the names and content of versions). The process @@ -1251,12 +1330,13 @@ The process 5. Generate the report. 6. Store the report (Nexus). -The process is model driven. The elements’ models (tables, plots, files and -report itself) are defined in the specification file. Script reads the elements’ -models from specification file and generates the elements. +The process is model driven. The elements' models (tables, plots, files +and report itself) are defined in the specification file. Script reads +the elements' models from specification file and generates the elements. -It is easy to add elements to be generated, if a new kind of element is -required, only a new algorithm is implemented and integrated. +It is easy to add elements to be generated in the report. If a new type +of an element is required, only a new algorithm needs to be implemented +and integrated. API @@ -1396,12 +1476,12 @@ PAL functional diagram How to add an element ````````````````````` -Element can be added by adding its model to the specification file. If the -element will be generated by an existing algorithm, only its parameters must be -set. +Element can be added by adding it's model to the specification file. If +the element is to be generated by an existing algorithm, only it's +parameters must be set. -If a brand new type of element will be added, also the algorithm must be -implemented. -The algorithms are implemented in the files which names start with "generator". -The name of the function implementing the algorithm and the name of algorithm in -the specification file had to be the same. +If a brand new type of element needs to be added, also the algorithm +must be implemented. Element generation algorithms are implemented in +the files with names starting with "generator" prefix. The name of the +function implementing the algorithm and the name of algorithm in the +specification file have to be the same. diff --git a/resources/tools/presentation/generator_tables.py b/resources/tools/presentation/generator_tables.py index 3bb30b5ab8..71ec431e6a 100644 --- a/resources/tools/presentation/generator_tables.py +++ b/resources/tools/presentation/generator_tables.py @@ -16,6 +16,9 @@ import logging +import csv +import prettytable + from string import replace from errors import PresentationError @@ -64,7 +67,6 @@ def table_details(table, input_data): # Generate the data for the table according to the model in the table # specification - job = table["data"].keys()[0] build = str(table["data"][job][0]) try: @@ -331,3 +333,174 @@ def _read_csv_template(file_name): return tmpl_data except IOError as err: raise PresentationError(str(err), level="ERROR") + + +def table_performance_comparision(table, input_data): + """Generate the table(s) with algorithm: table_performance_comparision + specified in the specification file. + + :param table: Table to generate. + :param input_data: Data to process. + :type table: pandas.Series + :type input_data: InputData + """ + + # Transform the data + data = input_data.filter_data(table) + + # Prepare the header of the tables + try: + header = ["Test case", + "{0} Throughput [Mpps]".format(table["reference"]["title"]), + "{0} stdev [Mpps]".format(table["reference"]["title"]), + "{0} Throughput [Mpps]".format(table["compare"]["title"]), + "{0} stdev [Mpps]".format(table["compare"]["title"]), + "Change [%]"] + header_str = ",".join(header) + "\n" + except (AttributeError, KeyError) as err: + logging.error("The model is invalid, missing parameter: {0}". + format(err)) + return + + # Prepare data to the table: + tbl_dict = dict() + for job, builds in table["reference"]["data"].items(): + for build in builds: + for tst_name, tst_data in data[job][str(build)].iteritems(): + if tbl_dict.get(tst_name, None) is None: + name = "{0}-{1}".format(tst_data["parent"].split("-")[0], + "-".join(tst_data["name"]. + split("-")[1:])) + tbl_dict[tst_name] = {"name": name, + "ref-data": list(), + "cmp-data": list()} + tbl_dict[tst_name]["ref-data"].\ + append(tst_data["throughput"]["value"]) + + for job, builds in table["compare"]["data"].items(): + for build in builds: + for tst_name, tst_data in data[job][str(build)].iteritems(): + tbl_dict[tst_name]["cmp-data"].\ + append(tst_data["throughput"]["value"]) + + tbl_lst = list() + for tst_name in tbl_dict.keys(): + item = [tbl_dict[tst_name]["name"], ] + if tbl_dict[tst_name]["ref-data"]: + item.append(round(mean(tbl_dict[tst_name]["ref-data"]) / 1000000, + 2)) + item.append(round(stdev(tbl_dict[tst_name]["ref-data"]) / 1000000, + 2)) + else: + item.extend([None, None]) + if tbl_dict[tst_name]["cmp-data"]: + item.append(round(mean(tbl_dict[tst_name]["cmp-data"]) / 1000000, + 2)) + item.append(round(stdev(tbl_dict[tst_name]["cmp-data"]) / 1000000, + 2)) + else: + item.extend([None, None]) + if item[1] is not None and item[3] is not None: + item.append(int(relative_change(float(item[1]), float(item[3])))) + if len(item) == 6: + tbl_lst.append(item) + + # Sort the table according to the relative change + tbl_lst.sort(key=lambda rel: rel[-1], reverse=True) + + # Generate tables: + # All tests in csv: + tbl_names = ["{0}-ndr-1t1c-full{1}".format(table["output-file"], + table["output-file-ext"]), + "{0}-ndr-2t2c-full{1}".format(table["output-file"], + table["output-file-ext"]), + "{0}-ndr-4t4c-full{1}".format(table["output-file"], + table["output-file-ext"]), + "{0}-pdr-1t1c-full{1}".format(table["output-file"], + table["output-file-ext"]), + "{0}-pdr-2t2c-full{1}".format(table["output-file"], + table["output-file-ext"]), + "{0}-pdr-4t4c-full{1}".format(table["output-file"], + table["output-file-ext"]) + ] + for file_name in tbl_names: + with open(file_name, "w") as file_handler: + file_handler.write(header_str) + for test in tbl_lst: + if (file_name.split("-")[-3] in test[0] and # NDR vs PDR + file_name.split("-")[-2] in test[0]): # cores + test[0] = "-".join(test[0].split("-")[:-1]) + file_handler.write(",".join([str(item) for item in test]) + + "\n") + + # All tests in txt: + tbl_names_txt = ["{0}-ndr-1t1c-full.txt".format(table["output-file"]), + "{0}-ndr-2t2c-full.txt".format(table["output-file"]), + "{0}-ndr-4t4c-full.txt".format(table["output-file"]), + "{0}-pdr-1t1c-full.txt".format(table["output-file"]), + "{0}-pdr-2t2c-full.txt".format(table["output-file"]), + "{0}-pdr-4t4c-full.txt".format(table["output-file"]) + ] + + for i, txt_name in enumerate(tbl_names_txt): + txt_table = None + with open(tbl_names[i], 'rb') as csv_file: + csv_content = csv.reader(csv_file, delimiter=',', quotechar='"') + for row in csv_content: + if txt_table is None: + txt_table = prettytable.PrettyTable(row) + else: + txt_table.add_row(row) + with open(txt_name, "w") as txt_file: + txt_file.write(str(txt_table)) + + # Selected tests in csv: + input_file = "{0}-ndr-1t1c-full{1}".format(table["output-file"], + table["output-file-ext"]) + with open(input_file, "r") as in_file: + lines = list() + for line in in_file: + lines.append(line) + + output_file = "{0}-ndr-1t1c-top{1}".format(table["output-file"], + table["output-file-ext"]) + with open(output_file, "w") as out_file: + out_file.write(header_str) + for i, line in enumerate(lines[1:]): + if i == table["nr-of-tests-shown"]: + break + out_file.write(line) + + output_file = "{0}-ndr-1t1c-bottom{1}".format(table["output-file"], + table["output-file-ext"]) + with open(output_file, "w") as out_file: + out_file.write(header_str) + for i, line in enumerate(lines[-1:0:-1]): + if i == table["nr-of-tests-shown"]: + break + out_file.write(line) + + input_file = "{0}-pdr-1t1c-full{1}".format(table["output-file"], + table["output-file-ext"]) + with open(input_file, "r") as in_file: + lines = list() + for line in in_file: + lines.append(line) + + output_file = "{0}-pdr-1t1c-top{1}".format(table["output-file"], + table["output-file-ext"]) + with open(output_file, "w") as out_file: + out_file.write(header_str) + for i, line in enumerate(lines[1:]): + if i == table["nr-of-tests-shown"]: + break + out_file.write(line) + + output_file = "{0}-pdr-1t1c-bottom{1}".format(table["output-file"], + table["output-file-ext"]) + with open(output_file, "w") as out_file: + out_file.write(header_str) + for i, line in enumerate(lines[-1:0:-1]): + if i == table["nr-of-tests-shown"]: + break + out_file.write(line) diff --git a/resources/tools/presentation/requirements.txt b/resources/tools/presentation/requirements.txt index 5765dc4ef0..a33848d681 100644 --- a/resources/tools/presentation/requirements.txt +++ b/resources/tools/presentation/requirements.txt @@ -8,3 +8,4 @@ python-dateutil numpy pandas plotly +PTable diff --git a/resources/tools/presentation/specification.yaml b/resources/tools/presentation/specification.yaml index 8a105fe974..d6e0b0ea78 100644 --- a/resources/tools/presentation/specification.yaml +++ b/resources/tools/presentation/specification.yaml @@ -44,6 +44,8 @@ DIR[DTR,FUNC,HC]: "{DIR[DTR]}/honeycomb_functional_results" DIR[DTR,FUNC,NSHSFC]: "{DIR[DTR]}/nshsfc_functional_results" DIR[DTR,PERF,VPP,IMPRV]: "{DIR[WORKING,SRC]}/vpp_performance_tests/performance_improvements" + DIR[DTR,PERF,VPP,IMPACT,SPECTRE]: "{DIR[WORKING,SRC]}/vpp_performance_tests/performance_impact_spectre" + DIR[DTR,PERF,VPP,IMPACT,MELTDOWN]: "{DIR[WORKING,SRC]}/vpp_performance_tests/performance_improvements" # Detailed test configurations DIR[DTC]: "{DIR[WORKING,SRC]}/test_configuration" @@ -87,6 +89,21 @@ - type: "configuration" data-sets: + vpp-meltdown-impact: +# TODO: specify data sources +# csit-vpp-perf-1801-all: +# - 1 +# - 2 + plot-throughput-speedup-analysis: +# TODO: Add the data sources +# csit-vpp-perf-1801-all: +# - 1 +# - 2 + vpp-spectre-impact: +# TODO: specify data sources +# csit-vpp-perf-1801-all: +# - 1 +# - 2 plot-throughput-speedup-analysis: # TODO: Add the data sources # csit-vpp-perf-1801-all: @@ -431,6 +448,70 @@ - type: "table" + title: "Performance Impact of Meltdown Patches" + algorithm: "table_performance_comparision" + output-file-ext: ".csv" +# TODO: specify dir + output-file: "{DIR[DTR,PERF,VPP,IMPACT,MELTDOWN]}/meltdown-impact" + reference: + title: "No Meltdown" +# TODO: specify data sources +# data: +# csit-vpp-perf-1801-all: +# - 1 +# - 2 + compare: + title: "Meltdown Patches Applied" +# TODO: specify data sources +# data: +# csit-vpp-perf-1801-all: +# - 1 +# - 2 + data: + "vpp-meltdown-impact" + filter: "all" + parameters: + - "name" + - "parent" + - "throughput" + # Number of the best and the worst tests presented in the table. Use 0 (zero) + # to present all tests. + nr-of-tests-shown: 20 + +- + type: "table" + title: "Performance Impact of Spectre Patches" + algorithm: "table_performance_comparision" + output-file-ext: ".csv" +# TODO: specify dir + output-file: "{DIR[DTR,PERF,VPP,IMPACT,SPECTRE]}/spectre-impact" + reference: + title: "No Spectre" +# TODO: specify data sources +# data: +# csit-vpp-perf-1801-all: +# - 1 +# - 2 + compare: + title: "Spectre Patches Applied" +# TODO: specify data sources +# data: +# csit-vpp-perf-1801-all: +# - 1 +# - 2 + data: + "vpp-spectre-impact" + filter: "all" + parameters: + - "name" + - "parent" + - "throughput" + # Number of the best and the worst tests presented in the table. Use 0 (zero) + # to present all tests. + nr-of-tests-shown: 20 + +- + type: "table" title: "Performance improvements" algorithm: "table_performance_improvements" template: "{DIR[DTR,PERF,VPP,IMPRV]}/tmpl_performance_improvements.csv" |