pipeline program
Component: cr-action:pipeline program (v1.0.2)
Added by: gfursin (2020-01-31 13:27:43)
Authors: Grigori Fursin
License: BSD 3-clause (code) and CC BY-SA 4.0 (data)
Source: GitHub
Creation date: 2015-01-28 08:47:33
CID: 081173242a88bc94:3bbc50d1eb87d47ecr-action:pipeline program  )

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How to get and run stable version (under development):
  pip install codereef
  cr download module:program --version=1.0.2 --all
  ck pipeline program --help

How to get and run development version:
  pip install ck
  ck pull repo:ck-autotuning
  ck pipeline program --help

How to run from Python:
   import ck.kernel as ck

                ... See JSON API below ...
   if r['return']>0: return r
Info about the CK module with this action: program
Workflow framework: CK
Development repository: ck-autotuning
Module description: program compilation and execution workflow (pipeline)
Workflow: program compilation, execution and validation pipeline (workflow)
API Python code: Link
        "    Input:  {
              (repo_uoa)             - program repo UOA
              (module_uoa)           - program module UOA
              (data_uoa)             - program data UOA
              (program_uoa)          - useful if univeral pipeline is used, i.e. ck run pipeline:program program_uoa=...
                 or taken from .cm/meta.json from current directory

              (random)               - if 'yes', random selection of program, cmd, dataset uoa and dataset file
                                       (to support collaborative program optimization)

              (skip_local)           - if 'yes', skip detection of program in a local path

              (program_tags)         - select programs by these tags

              (program_dir)          - force program directory

              (target)               - target machine added via 'ck add machine' with prepared target description
                                       (useful to create farms of machines for crowd-benchmarking and crowd-tuning using CK)

              (host_os)              - host OS (detect, if omitted)
              (target_os)            - OS module to check (if omitted, analyze host)
              (device_id)            - device id if remote (such as adb)

              (local_platform)       - if 'yes', use host_os/target_os from the current platform
                                       (useful when replaying experiments from another machine and even OS)

              (prepare)              - if 'yes', only prepare setup, but do not clean/compile/run program
              (save_to_file)         - if !='', save updated input/output (state) to this file
              (skip_interaction)     - if 'yes' and out=='con', skip interaction to choose parameters

              (skip_device_init)     - if 'yes', skip device init
              (skip_info_collection) - if 'yes', skip info collection

              (skip_device_info)     - if 'yes', skip any device info -
                                       useful to prepare experiment crowdsourcing packs for remote devices

                 Pipeline sections' settings:

              (compute_platform_id)  - if !='', set env['CK_COMPUTE_PLATFORM_ID']
              (compute_device_id)    - if !='', set env['CK_COMPUTE_DEVICE_ID']

              (no_platform_features)    - if 'yes', do not collect full platform features
              (no_dataset_features)     - if 'yes', do not search and extract data set features
              (no_clean)                - if 'yes', do not clean directory before compile/run
              (no_compile)              - if 'yes', do not compile program (useful when running the same program
                                           under different system state conditions: CPU/GPU freq, cache/bus contentions, etc)
              (compile_only_once)       - if 'yes', compile only at first iteration
              (no_compiler_description) - if 'yes', do not search for most close compiler description with flags ...
              (no_run)                  - if 'yes', do not run program
                                             useful when using autotuning to find bugs in compiler,
                                             or find differently generated code sequencies, etc ...
              (no_state_check)          - do not check system/CPU state (frequency) over iterations ...

              (generate_rnd_tmp_dir) - if 'yes', compile and run program in randomly generated temporal dir
              (tmp_dir)              - if !='', use this tmp_dir

              (skip_clean_after)     - if 'yes', do not remove run batch
              (keep)                 - the same as skip_clean_after

              (console)              - if 'yes', output from program goes to console rather than file
                                          (usually for testing/demos)

              (cmd_key)              - CMD key
              (cmd_keys)             - Select only from this list of available CMD keys

              (dataset_uoa)          - UOA of a dataset
              (dataset_file)         - dataset filename (if more than one inside one entry - suggest to have a UID in name)
              (extra_dataset_tags)   - list of extra data set tags (useful to set \"small\" during mobile phone crowdtuning)

              (compiler_env_uoa)     - env of a compiler

              (compile_type)         - static or dynamic (dynamic by default;
                                         however takes compiler default_compile_type into account)
              (static or dynamic)

              (compiler_description_uoa)    - compiler description UOA (module compiler),
                                              if not set, there will be an attempt to detect the most close
                                              by version

              (compiler_vars)        - dict with set up compiler flags (-Dvar=value) ->
                                       they will update the ones defined as default in program description ...

              (no_vars)              - skip compiler vars (if you want to use default ones from the sources) ...

              (remove_compiler_vars) - list of compiler vars to remove

              (extra_env_for_compilation) - set environment variables before compiling program

              (flags)                - compile flags
              (lflags)               - link flags

              (compiler_flags)       - dict from compiler description (during autotuning),
                                       if set, description should exist in input:choices_desc#compiler_flags# ...

              (best_base_flag)       - if 'yes', try to select best flag if available ...
              (speed)                - the same as above
              (skip_best_base_flag)  - if 'yes', do not use best base flag (useful for exploration of other levels -O2,-O1,etc)
              (env_speed)            - use environment flag for best optimization (CK_OPT_SPEED)

              (shared_solution_cid)  - CID-UID1-UID2 of the shared optimization solution at cKnowledge.org/repo
                                       You can find it by clicking on a \"Copy CID to clipboard\" button of a given solution.
                                       See example at http://cknowledge.org/repo/web.php?wcid=8289e0cf24346aa7:79bca2b76876b5c6

              (Ocid-uid1-uid2)         Substituting compiler -Ox levels with shared solutions in above format

              (select_best_base_flag_for_first_iteration) - if 'yes' and autotuning_iteration=0

              (env)                  - preset environment
              (env.{KEY})            - set env[KEY]=value (user-friendly interface via CMD)

              (deps.{KEY})           - set deps[KEY][\"uoa']=value (user-friendly interface via CMD to set any given dependency)
              (preset_deps)          - dict with {\"KEY\":\"UOA\"} to preset dependencies

              (params)               - dictionary with parameters passed via pre/post processing to third-party tools
                                       for example, to configure ARM Workload Automation
              (params.{KEY})         - set params[KEY]=value (user-friendly interface via CMD)

              (extra_env)            - extra environment as string
              (extra_run_cmd)        - extra CMD (can use $#key#$ for autotuning)
              (debug_run_cmd)        - substitute CMD with this one - usually useful for debugging to pre-set env for all deps
              (run_cmd_substitutes)  - dict with substs ($#key#$=value) in run CMD (useful for CMD autotuning)

              (sudo)                 - if 'yes', force using sudo
                                       (otherwise, can use ${CK_SUDO_INIT}, ${CK_SUDO_PRE}, ${CK_SUDO_POST})

              (affinity)             - set processor affinity for tihs program run (if supported by OS - see \"affinity\" in OS)
                                       examples: 0 ; 0,1 ; 0-3 ; 4-7  (the last two can be useful for ARM big.LITTLE arhictecture

              (repeat)               - repeat kernel via environment CT_REPEAT_MAIN if supported
              (do_not_reuse_repeat)  - if 'yes', do not reuse repeat across iterations - needed for dataset exploration, for example
              (skip_calibration)     - if 'yes', skip execution time calibration (otherwise, make it around 4.0 sec)
              (calibration_time)     - calibration time in string, 4.0 sec. by default
              (calibration_max)      - max number of iterations for calibration, 10 by default

              (statistical_repetition_number) - current statistical repetition of experiment
                                                (for example, may be used to skip compilation, if >0)
              (autotuning_iteration)          - (int) current autotuning iteration (automatically updated during pipeline tuning)
              (the_same_dataset)              - if 'yes', the dataset stays the same across iterations
                                                   so skip copying dataset to remote from 2nd iteration

              (repeat_compilation)     - if 'yes', force compilation, even if \"statistical_repetition_number\">0

              (cpu_freq)               - set CPU frequency, if supported (using SUDO, if also supported)
                                           using script ck-set-cpu-online-and-frequency
                                         if \"max\" - try to set to maximum using script ck-set-cpu-performance
                                         if \"min\" - try to set to minimum using scrupt ck-set-cpu-powersave

              (gpu_freq)               - set GPU frequency, if supported (using SUDO, if also supported)
                                           using script ck-set-gpu-online-and-frequency
                                         if \"max\" - try to set to maximum using script ck-set-gpu-performance
                                         if \"min\" - try to set to minimum using scrupt ck-set-gpu-powersave

              (energy)                  - if 'yes', start energy monitoring (if supported) using script ck-set-power-sensors

              (gprof)                   - if 'yes', use gprof to collect profile info
              (perf)                    - if 'yes', use perf to collect hardware counters
              (vtune)                   - if 'yes', use Intel vtune to collect hardware counters
              (sim)                     - if 'yes', use architecture simulator (found by tags \"arch\",\"sim\")
              (valgrind)                - if 'yes', add valgrind

              (dvdt_prof)               - if 'yes', run program under dividiti's OpenCL profiler
              (mali_hwc)                - if 'yes', attempt to extract MALI GPU hardware counters

              (milepost)                - if 'yes', attempt to extract static program features using Milepost GCC and cTuning CC
              (milepost_out_file)       - if !='', record extracted MILEPOST features to this JSON file

              (compile_timeout)         - (sec.) - kill compile job if too long
              (run_timeout)             - (sec.) - kill run job if too long

              (post_process_script_uoa) - run script from this UOA
              (post_process_subscript)  - subscript name
              (post_process_params)     - (string) add params to CMD

              (dependencies)         - compilation dependencies
              (deps_cache)           - cache with resolved dependencies for reuse (if needed)
              (reuse_deps)           - if 'yes' reuse dependencies
              (force_resolve_deps)   - if 'yes', force resolve deps (useful for crowd-tuning)

              (choices)              - exposed choices (if any)
              (choices_order)        - vector of flattened choices (useful if optimizations need order
                                        such as LLVM or using our GCC plugin iterface to reorder passes,
                                        since 'choices' dict does not have order)

              (features)             - exposed features (if any)

              (characteristics)      - measured characteristics/features/properties (if any)

              (state)                - kept across pipeline iterations (for example, during autotuning/exploration)

                                       (tmp_dir)    - if temporal directory is used, return it
                                                      (useful if randomly generated, to be reused for run or further iterations)
                                       (repeat)     - kernel repeat ...
                                       (features.platform.cpu) - CPU features/properties obtained during iterations
                                                                 to check that state didn't change ...

              (skip_output_validation)        - skip validation of output (dangerous during auto-tuning -
                                                  some optimizations may break semantics or change accuracy)
              (output_validation_repo)        - output validation repo UOA (when recording new output)
              (program_output_uoa)            - use this UOA to check/record program output 
                                                (to have the same output entry for groups of similar programs)

              (overwrite_reference_output)    - if 'yes', overwrite reference output (useful if broken)

              (quiet)                - if 'yes', automatically provide default answer to all questions when resolving dependencies ...

              (last_md5)             - if !='', check if MD5 and fail if didn't change!
              (last_md5_fail_text)   - to recognize that pipeline failure is not really a failure,
                                       but MD5 is the same (useful when pruning compiler flags found
                                       during collaborative autotuning, particularly via mobile devices
                                       (less time to prune results))

              (skip_print_timers)          - if 'yes', skip printing fine-grain timers after execution

              (add_rnd_extension_to_bin)   - if 'yes', add random extension to binary and record list
              (add_save_extension_to_bin)  - if 'yes', add '.save' to bin to save during cleaning ...

              (install_to_env)       - install dependencies to env instead of CK-TOOLS (to keep it clean)!

              (safe)                 - safe mode when searching packages first instead of detecting already installed soft
                                       (to have more deterministic build)

              (skip_exec)            - if 'yes', do not clean output files and skip exec to be able to continue
                                       post-processing during debuging

    Output: {
              return       - return code =  0, if successful
                                         >  0, if error
              (error)      - error text if return > 0

              !!! The same as input, but with updated information !!!

              ready        - if 'yes', pipeline is ready (all obligatory choices are set)
                             if 'no', clean/compile/run program is postponed

              state        - should be preserved across autotuning, active (online) learning, exploration, validation iterations


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