Macromain

А выход из цикла если таковой нужен можно организовать так : создаем несколько копий конфигов с именами 1, 2, 3... И тд сколько надо циклов. Они - точная копия либо варианты тела цикла - macromain.cfg. Во всех кроме последнего в конце ссылка на automacro_clone1.exe. В macromain1.cfg организован сдвиг конфигов копированием 1 в macromain.cfg, 2 в 1 , 3 в 2 и тд. Когда последний скопируется в macromain.cfg это и будет последняя итерация цикла.
Это просто идея. Тест не проводил.macromain

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NPRG054 Assignments - General information

Asignments - General informationTesting environment

Login to at parlab.ms.mff.cuni.cz using your CAS (SIS) credentials.

Use the parlab machine only for file manipulation (git, vim, ...) and scriptingNever use the parlab machine directly for compiling or running - use the parlab workers instead.

The traffic at parlab workers is controlled by SLURM - you need to understand at least the basics described here: parlab SLURM - crash courseYou may ignore the parts specific for GPUs and gpulab. All machines at parlab are equipped with cmake and g , capable of C 20.Parlab partitions relevant for this courseOnly users registered for this course will have access to the -long and -short partitions. Unregistered users can use the -ffa partitions.Frameworks and skeletonsAll homework assignments share the same git project. This allows to easily share some files across the assignments.Usage:At the machine you want to use for development:Ensure that you have a working git client and that you understand git basicsIf you want to use git over ssh (preferred), you have to register your public key at gitlab.mff.cuni.czLogon to gitlab.mff.cuni.cz (with your SIS credentialslocate the teaching/nprg054/2022/ projectand clone it into a local folder.If you do not see your project in gitlab, contact your teacher.Important: Updating your repository from teaching/nprg054/asgn:At parlab:If you want to use git over ssh (preferred), you have to generate a private key here (ssh-keygen) and register the corresponding public key (~/.ssh/id_rsa.pub) at gitlab.mff.cuni.czClone your project into a local folderAll machines in parlab share the same NFS tree with your home folder. Therefore, the git actions may be done on parlab itself, once for all.For compiling, you need to create a special build folder for every parlab environment (debug|mpi-homo|phi), you may also want to distinguish Debug and Release builds. Compiling and running with command-line:Make yourself familiar with the purpose of cmake.In a (initially empty) build folder, run this:Target-name is defined in CMakeLists.txt ("macro" for the first assignment).Important: if you want to test performance, you need to configure cmake to Release mode as follows:It may be a good idea to separate Debug and Release build folders.Compiling and running using Microsoft Visual Studio 2019 or Visual Studio Code:Install cmake support in Visual StudioOpen your local clone folder with the Visual Studio (you can also create the clone directly with Visual Studio)Wait until the "cache" is generated (i.e. cmake is run), usually automaticallySelect the target, build the project and runVisual studio also supports compiling/running/debugging with clang on Windows, g /gdb in WSL, and clang or g /gdb in Linux via sshUnfortunately, the ssh approach does not work well with SLURMliulli>When done:Push everything into your gitlab repository (aka origin), branch "master"If you finished the work before the deadline, no further action is requiredAfter the deadline, you have to send me an email indicating that you want your submision evaluated (with a penalty for late submission)Please be patient, I will usually check the new solutions in batches, approx. every two weeksIf you continue development after the deadline and after commiting some working solution, use a branch other than master for incomplete versionsotherwise, you risk that an incomplete version will be evaluated instead of the working versionIf you share a header file across assignments, remember that updating this file during a second assignment may spoil the commited solution of the first oneliul> Handling different vector instruction setsAll your solutions shall be templated classes with the template argument policy. This argument is used to specify the desired vector platform. In the skeleton, you will find the following four policy classes: policy_scalar, policy_sse, policy_avx, and policy_avx512. You may fill the policy classes with whatever contents or you may leave them empty and use explicit specializations of your class.

In addition, the parts of source code which use AVX512 intrinsics must be enclosed inside "#ifdef USE_AVX512" directives to avoid compilation errors on unsupporting platforms, similarly for USE_AVXDon't try to run programs built in avx-enabled modes on non-avx platforms since avx-enabled compilers may emit avx-instructions from normal C codeThats why you must compile for every SLURM partition at parlab independently, although they share the same folders via NFS.)

New: AVX512BW instructions may be used if enclosed inside "#ifdef USE_AVX512BWIn addition, USE_AVX512 now means that AVX512CD is also available.

Your solution shall support all the four policy classes; however, you are not required to actually use the respective vector instructions. For instance, the implementation for may be identical to the implementation with or . (E.g., for the Macroprocessor, it is unlikely that vectorizing brings any measurable speed-up.)

The USE_AVX, USE_AVX512, and USE_AVX512BW flags are set by the cmake configuration filesconsistently with the command-line compiler options that enable the corresponding instructions.At Linux machines, the cmake configuration files will automatically detect the CPU capability using /proc/cpuinfo.

At Windows, there is no reliable way of detectionThe defaults (USE_AVX=True, USE_AVX512=False, USE_AVX512BW=False) are set in cmake cacheit may be changed in Project/CMake Settings in Visual Studio or using cmake-guiIt must be changed for very old CPUs which do not support AVX2.) OutputThe testing framework produces standard output in tab-separated format (without any headerThe columns are the following:Machine namePlatformThread id (not present in Debug mode)Asignment-specific parameters, usually affecting the size of particular testThe last of these parameters is usually auto-adjustingi.e. increased until the test time becomes reliably measurableover 1 sec; 0.1 sec for Debug modelili>Time in nanoseconds, divided by the complexity of the test (derived from the parameters).The result of the test, or a checksum of the results, depending on the assignment.Immediately after finishing a particular testan output line containing the columns descibed above is producedThis output may be switched off by the --direct-print=no optionlili>After finishing all tests, partial and full aggregates are printedThe first set of lines is based on aggregation over the auto-adjusting parameter valueswhere the last (i.e. the most precisely measured) time is selectedwhile the results are taken from the first runThe remaining parameters, in right-to-left order, produce further line setswhere the description of parameter values is replaced by their rangesover which the aggregation was donefinally the threads and the platforms are aggregated tooFor these results, time is aggregated by geometric meanBesides the columns described above, every aggregated line contains two additional columnsulli>A sign OK/MISMATCH indicating the correctness of the result/checksumThe ratio between the measured and the reference timingsi.e. a number smaller than 1.0 means that the code is faster than the referenceReference timings are available only at parlabliulliulh4>Testing procedureThe output shows all the inividual tests performedThe meaning of the parameters is described with each assignment.The testing is performed in parallelto simulate the workload on the other CPU cores during a typical parallel computationEach thread performs the same sequence of testshowever, each thread uses a different seedfor the random generation of input data (therefore the different outputs/checksumsThe threads run the tests in lockstep, i.e. there is a global rendez-vous after finishing each testDue to different inputs and other variations, different threads may run for slightly different timepp>To mitigate the effect of context-switching after the rendez-vous and different run timeseach test is actually run three times (with identical data) in each threadOnly the middle of the tree runs is measured (and printedthe first and the last run are set to last only 20% of the measured runby manipulating the auto-adjusting parameterThe triple run is implemented together with the loop over the auto-adjust parameterby a range-based for like this (from macromain.cppfor (auto ctx5 : auto_measurement(ctx4, 1024line_policyThe loop itself is entered for every auto-adjusting group of teststhe number of iterations of the loop is three times the number of auto-adjusting parameter values usedThe time measurement (implemented inside the * and operators of the loop range iteratorsis thus done on the 2-nd, 5-th, 8-th, etc. iterationsonly the last measurement is actually used in the final statisticsNote that this complex behavior is observable during debuggingph4>Command-line argumentsThe testing framework compiled together with your code supports the following command-line arguments:--platform=(scalar|sse|avx|avx512) - run tests only in the specified platform--(scalar|sse|avx|avx512)=no - disable specific platform--threads= - use the specified number of worker threads for testingDefaults to the number of hardware threads in the CPU or allocated in SLURMOfficial timings are measured with 8 threadsUse srun -n 1 -c 8 to reproduce the official settings in parlabIn Debug mode, tests are always done in the main thread to simplify debugging.--machine= - override the autodetected machine name printed in the first column--direct-print=no - disable printing individual results during testing, print only final statsIn addition, each assignment has its specific command-line argumentswhich influence the testing sequence or enable debuging outputsSee the respective assignment pages.Advanced options:--code-check= - produce a .cpp file containing checksums from this runuse with --platform to make results unique)--code-time= - produce a .cpp file containing timings from this runThe *gold*.cpp files were obtained using these optionsTiming files for other machines may be produced by --code-time, compiled and linked with the projectThe framework will then compare the timings against them whenever run on the same machine name.The program may also be run via the command "make test". In this casecommand-line arguemnts may be adding the arguments to the MAKE_TARGET call in "CMakeLists.txte.gp>

MAKE_TARGET("MACRO" "macro" "--dump=onprebody>

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